d2.7 analysis of potential ever-est sustainability model · 05/02/2018 fulvio marelli second draft:...
TRANSCRIPT
H2020 – EINFRA – 2015 – 1 Page 1 of 75
D2.7
Analysis of potential EVER-EST sustainability model
Workpackage 2 Community building and dissemination
Task 2.5 Research on VRE sustainability and takeover
Author (s) Marco Romani ALMA Sistemi
Reviewer (s) Pedro Gonçalves
Simone Mantovani
T2
MEEO
Approver (s) Cristiano Silvagni ESA
Authorizer Mirko Albani ESA
Document Identifier EVER-EST DEL WP2 D2.7
Dissemination Level Public
Status Draft to be approved by the EC
Version 1.6
Date of issue 24-10-2018
H2020 – EINFRA – 2015 – 1 Page 2 of 75
Document Log
Date Author Changes Version Status
20/01/2018 Marco Romani First draft 1.0 Internal draft
05/02/2018 Fulvio Marelli Second Draft: Vision integrated 1.1 Internal draft
06/02/2018 Marco Romani Third Draft: document structure reviewed
1.2 Internal draft
07/02/2018 Fulvio Marelli Ready for internal check 1.3 Internal draft
07/02/2018 Cristiano Silvagni Internal review 1.4 Internal draft
20/07/2018 Marco Romani Review of chapters 3, 5, and 6 according to EC Expert assessment report recommendations (from 7 to 12) of 07/03/2018
1.5 Internal draft
3/08/2018
Marco Romani
Add of annex A – Stakeholders data collection and annex C about Value Proposition survey results in the
1.5
Internal draft
3/10/2018 Marco Romani All chapters were reviewed including the Final Plenary Review outcomes
1.6 Internal draft
22/10/2018 Pedro Goncalves
Simone Mantovani
Comments from formal reviewers implemented
1.6 Draft to be approved by the EC
H2020 – EINFRA – 2015 – 1 Page 3 of 75
Table of contents
1 Introduction ........................................................................................................................................... 8
Summary ......................................................................................................................................... 8
How this document is organized....................................................................................................... 8
2 Sustainability: context and purpose ........................................................................................................ 9
A first take on sustainability ............................................................................................................. 9
2.1.1 Definitions ...................................................................................................................................... 10
Sustainability: fundamental pillars ................................................................................................. 10
2.2.1 Social............................................................................................................................................... 10
2.2.2 Environment ................................................................................................................................... 11
2.2.3 Economic ........................................................................................................................................ 11
Norms, Recommendations, Standards and Guideline ...................................................................... 11
2.3.1 Social norms ................................................................................................................................... 11
2.3.2 Standards and Guidelines............................................................................................................... 12
3 Open Science environment ................................................................................................................... 14
Open Science main players ............................................................................................................ 17
3.1.1 Virtual Laboratory .......................................................................................................................... 18
3.1.2 Science Gateways ........................................................................................................................... 18
3.1.3 Virtual Research Environment ....................................................................................................... 18
3.1.4 e-infrastructure .............................................................................................................................. 19
3.1.5 Data provider.................................................................................................................................. 20
Data Business models in Open Science ........................................................................................... 21
Sustainability pillars tendencies ..................................................................................................... 22
3.3.1 GEANT - Storing data in a secure environment ............................................................................. 22
3.3.2 EUDAT - Seamless access & connectivity ....................................................................................... 22
3.3.3 CLARIN ERIC .................................................................................................................................... 23
3.3.4 ELIXIR .............................................................................................................................................. 23
3.3.5 ZENODO .......................................................................................................................................... 23
3.3.6 LTER ................................................................................................................................................ 24
3.3.7 NECTAR ........................................................................................................................................... 24
4 The Vision for the EVER-EST Infrastructure ............................................................................................ 25
What is EVER-EST ........................................................................................................................... 25
EVER-EST in the European Open Science Context ............................................................................ 25
EVER-EST Vision ............................................................................................................................. 26
4.3.1 What we value ................................................................................................................................ 26
4.3.2 Who we are .................................................................................................................................... 26
4.3.3 Governance Model ......................................................................................................................... 27
4.3.4 Positioning in Open Science ........................................................................................................... 27
4.3.5 Choosing the EVER-EST solution .................................................................................................... 29
H2020 – EINFRA – 2015 – 1 Page 4 of 75
5 EVER-EST Sustainability model .............................................................................................................. 30
Goals ............................................................................................................................................. 30
Methodology and approach ........................................................................................................... 31
Main Stakeholders ......................................................................................................................... 32
Short-term and long-term potential competitors ............................................................................ 33
Data Value Chain ........................................................................................................................... 34
EVER-EST Services platform ............................................................................................................ 35
5.6.1 Service Portfolio ............................................................................................................................. 36
5.6.2 The Governance ............................................................................................................................. 37
5.6.3 Service Level Agreement ................................................................................................................ 38
SWOT Analysis ............................................................................................................................... 38
EVER-EST in sustainable pillars ....................................................................................................... 39
5.8.1 Social responsibility ........................................................................................................................ 39
5.8.2 Environment ................................................................................................................................... 42
5.8.3 Economic ........................................................................................................................................ 42
6 EVER-EST Business Models ................................................................................................................... 44
Customer Segments ....................................................................................................................... 44
Value Proposition .......................................................................................................................... 45
Channels ....................................................................................................................................... 49
Customer Relationships ................................................................................................................. 50
Revenues Stream ........................................................................................................................... 50
Key Resources ............................................................................................................................... 51
Key Activities ................................................................................................................................. 51
Key Partnerships ............................................................................................................................ 51
Cost Structure ................................................................................................................................ 52
CANVAS Business model by Customer segments ............................................................................. 52
7 Sustainability roadmap......................................................................................................................... 56
Approaching sustainability aspects ................................................................................................. 56
A roadmap to sustainability ........................................................................................................... 56
From sustainability to takeover ...................................................................................................... 57
8 Conclusions .......................................................................................................................................... 58
H2020 – EINFRA – 2015 – 1 Page 5 of 75
List of Figures
Figure 1 Sustainability pillars ....................................................................................................................................... 10
Figure 2 Governance / Reputation cycle ..................................................................................................................... 12
Figure 3 Scientific articles publishing in the domain of Open Science ....................................................................... 15
Figure 4 Open Science monitoring indicators ............................................................................................................. 17
Figure 5 Sustainability methodology model ............................................................................................................... 32
Figure 6 EVER-EST data value-chain ............................................................................................................................ 35
Figure 7 Service infrastructure logic............................................................................................................................ 36
Figure 8 EVER-EST Added-value, service category and HMI ....................................................................................... 37
Figure 9 EVER-EST Governance ................................................................................................................................... 37
Figure 10 Potential SLA schemas................................................................................................................................. 38
Figure 11 Value Proposition Business Model to Research Organization .................................................................... 53
Figure 12 Value Proposition Business Model to Data Providers & Distributors ......................................................... 54
Figure 13 Value Proposition Business Model to European Service Providers ............................................................ 54
Figure 14 Partnership Business Model to Research Infrastructures ........................................................................... 55
Figure 15 EVER-EST sustainability to takeover roadmap ............................................................................................ 56
List of Tables
Table 1 Open science initiative comparison matrix .................................................................................................... 28
Table 2 Potential competitors in Cloud computing service ........................................................................................ 34
Table 3 Service portfolio ............................................................................................................................................. 36
Table 4 EVER-EST VRE SWOT analysis ......................................................................................................................... 39
Table 5 Social responsibility EVER-EST compliant analysis – part 1 ............................................................................ 40
Table 6 Social and Environment EVER-EST compliant analysis – part 2 ..................................................................... 41
Table 7 Research Organization value proposition ...................................................................................................... 46
Table 8 European Added-Value Service Provider value proposition .......................................................................... 48
Table 9 Data Providers & Distributors value proposition ........................................................................................... 49
H2020 – EINFRA – 2015 – 1 Page 6 of 75
Definitions and Acronyms
Acronym Description
CNR-ISMAR Consiglio Nazionale delle Ricerche – Istituto di Scienze Marine
ES Earth Science
EO Earth Observation
ESA European Space Agency
EVER-EST European Virtual Environment for Research - Earth Science Themes
GUI Graphical User Interface
RIA Research and Innovation Action
RDA Research Data Alliance
RO Research Objects
SATCEN European Union Satellite Center
SMART Specific, Measurable, Achievable, Relevant, Time-bound
VRC Virtual Research Community
VRE Virtual Research Environment
H2020 – EINFRA – 2015 – 1 Page 7 of 75
Applicable Documents
Document ID Document Title
AD1 D1.1 - Project and Quality Management Plan
AD2 D2.2 - Dissemination Strategy and Plan
AD3 D2.6 – Contribution to the international Best Practices of VRE
AD4 D2.7 - Sustainability Models (including Stakeholder data collection)
AD5 EVER-EST SUS_VIS-SURV - Vision Survey – Action WP02-A050
AD7 EVER-EST RO_STD-SURV- ROs Standard Entities Survey – Action WP02-A063
AD7 D4.1 - Workflows and Research Objects in Earth Science - Concepts and Definitions
AD8 D5.11 – Infrastructure and Services
AD9 D6.4 – Data Management Plan
AD10 D2.8 – Plan to takeover
Reference Documents
Document ID Document Title
RD1 GA- Grant Agreement N° 674906
RD2 CA- Consortium Agreement of October 29, 2015
RD3 Transforming our world: the 2030 Agenda for Sustainable Development, UN Resolution 70/1, 21 October 2015
RD4 GEO/CEOS joint report on “Earth Observations in support of the 2030 Agenda for Sustainable Development”
RD5 Katherine Anderson, Barbara Ryan, William Sonntag, Argyro Kavvada & Lawrence Friedl (2017): Earth observation in service of the 2030 Agenda for Sustainable Development, Geo-spatial Information Science
H2020 – EINFRA – 2015 – 1 Page 8 of 75
1 Introduction
Summary
The EVER-EST H2020 project aims at providing the Earth Science domain with an innovative framework which will allow Scientists, Researchers and future Stakeholders (e.g. Public Authorities, Citizen Scientists, etc.) to rely on advanced means to share, re-use, re-purpose and enhance scientific research processes and workflows.
The EVER-EST consortium is approaching the work with the goal to make scientific research compliant to FAIR principles (make research data Findable, Accessible, Interoperable and Reusable) by the adoption of Research Objects – and putting people/users at the centre of the paradigm.
During the project lifecycle (first 24 months) the main attention of the partners has been focused on the design and development of e-infrastructure and the constant assessment of its effective adoption by the Virtual Research Communities – VRC (last 6 months). Meaning a continuous internal monitoring of the gaps limiting the usage by current VRC users and to identify the keys for potential success of the EVER-EST platform in its future adoption by new external communities.
This document covers the analysis of sustainability aspects related to the EVER-EST Virtual Research Environment - VRE: it summarises the different aspects which are concerned with the sustainability philosophy and strategy, while the implementation and the resulting outcomes of sustainability model are reported in the D3.7 Overall Assessment.
The document provides the Vision of the EVER-EST members about the future of the technology: an overview of the understanding that the Consortium has matured and agreed during the first two years of the project (design, development and deployment of e-infrastructure) about the potential of the infrastructure and the way to ensure its usage after the end of the funding by the different VRC’s. At the same time, it provides an overview of the external environment: the other VRE initiatives, the market and the potential customer segments.
The business models according with the customer segments is presented and detailed, going through the primary aspects concerned with the takeover process from the project context to the operations.
The present document was refined by taking into account the EC Reviewers recommendations #7 to #12. The potential customer’s interviews are not reported as suggested in recommendations #7 and #8 because they are addressed in a separate document.
How this document is organized
This document describes all the aspects concerned with the various streams underpinning the sustainability model. It is the result of the analysis and elaboration of the following items:
• Studies of sustainability context and purpose in terms of international norms, recommendations, standards (e.g. ISO 26000) and guideline (e.g. GRI G4) on the matter of sustainability;
• EVER-EST mission, vision and approach to sustainability aspects;
• Analysis of worldwide on-going initiatives in the Open Science, such as Science Gateway (SGs), Virtual Labs (Vls) and Virtual Research Environments (VRE);
• Analysis of EO Data providers and Distributors, offering access and tools to scientific communities;
• EVER-EST sustainability model on market.
H2020 – EINFRA – 2015 – 1 Page 9 of 75
2 Sustainability: context and purpose Today the European Union has 1.7 million researchers and about 70 million science and technology professionals engaged in the creation of new knowledge, innovation of products, service and processes. Digital infrastructures are the virtual backbone of European research and a vital driver for innovation.
EU invests more than 850 million euros in digital infrastructure through the H2020 programme. European Cloud initiative will contribute for a competitive data and knowledge economy in Europe.
Digital single market is a fundamental step towards the reinforcement of the EU’s competitiveness in digital technologies and in innovation. Cloud initiative will provide European science, industry and public authorities with world-class data infrastructures.
The European Commission has recently made the European Open Science Cloud (EOSC) Declaration available to all scientific stakeholders, for their endorsement and commitments to the realization of the EOSC by 2020.
The EOSC aims to accelerate and support the current transition to more effective Open Science and Open Innovation in the Digital Single Market. It should enable trusted access to services, systems and the re-use of shared scientific data across disciplinary, social and geographical borders.
The EOSC is indeed a European infrastructure, but it should be globally interoperable and accessible. It includes the required human expertise, resources, standards, best practices as well as the underpinning technical infrastructures. An important aspect of the EOSC is systematic data management and long-term stewardship of scientific data assets and services in Europe and globally.
The guiding concept of sustainability model is the delivery of a project following the mantra “build-to-run”, which means that the EVER-EST sustainability model is built caring of the operational needs taking in mind the operational environment and social impact into the science organization. Sustainability model will contribute to increase research competitiveness leveraging on to the following aspects:
1) Reducing the cost of the research infrastructures by scaling-up and sharing among many researchers the necessary bases;
2) Improving the quality of data sharing and research outcomes; 3) Improving the cooperative working in order to pave the way to new discoveries; 4) Enable long-term preservation concept aimed to guarantee the long term saving of scientific data tools,
procedures and outcomes.
A first take on sustainability
There is no universally agreed definition on what sustainability means. There are many different views on what it is and how it can be achieved. The idea of sustainability stems from the concept of sustainable development which became common language at the World's first Earth Summit in Rio in 19921: “Sustainability development that meets the needs of the present without compromising the ability of future generations to meet their own needs2“. Since then, there have been many variations and extensions on this basic definition.
Sustainable development is, also linked to the overall goal of the UN Decade of Education for Sustainable Development - DESD3. It aims to integrate the principles, values and practices of sustainable development into all aspects of education and learning. This educational effort will encourage changes in behaviour that will create a
1 Declaration available at: http://www.unesco.org/education/pdf/RIO_E.PDF 2 Bruntland Report for the World Commission on Environment and Development (1992) 3 Available at: http://unesdoc.unesco.org/images/0014/001416/141629e.pdf
H2020 – EINFRA – 2015 – 1 Page 10 of 75
more sustainable future in terms of environmental integrity, economic viability and a just society for present and future generations.
2.1.1 Definitions
In order, to ensure a common language and understanding about sustainability concept in the EVER-EST community, the most suitable definition is provided: “Sustainability is the use of various strategies for employing existing or future resources optimally so that a responsible and beneficial balance can be achieved over the longer term. It is based on the economic, social and environment main pillars that contribute to find the most suitable solution to reach the sustainability goal.”
In the EVER-EST context, being a research-oriented approach sustainability involves the analysis of intangible values (e.g. sharing, collaboration, preservation and cross-fertilization) together with economic and organisational aspects.
Sustainability: fundamental pillars
The fundamental elements of sustainability taken into consideration are the following three main pillars: Social responsibility, the Environment impact and the Economic viability.
Figure 1 Sustainability pillars
These three pillars of sustainability are a powerful tool for defining the complete sustainability problem. If anyone of pillars is weak then the system as a whole is unsustainable.
Moreover, being sustainability the ability to continue an agreed behaviour indefinitely. Along-the-time analysis is fundamental in order to understand what changes, will affect positively or negatively the project and its operational context.
2.2.1 Social
Social, measures the level of quality, capabilities and performances provided to people and their grade of satisfaction in using it and willing to use without coercively. Very often this aspect is the most difficult to achieve
H2020 – EINFRA – 2015 – 1 Page 11 of 75
being difficult to define the optimal level of quality of use depending by the different actual uses, by different culture of users, different activities of organisations.
A brief list about sustainability goals based on Social responsibility:
• Social: (all issue related to people and related impact on organization) o Create a long-term open science sustainability model. o Promote actions in support of stable employment. o Contribute to creating the European Open Science Cloud o Contribute to strengthening both the scientists and citizen's awareness of the benefits of Earth
Science.
2.2.2 Environment
Environment – all related aspects concerned with utilisation of resources (e.g. hardware, software, tools, data, services, networking, help and training, etc.) and their availability is analysed to ensure the optimal balance between the use and the availability, between the innovation and the obsolescence.
A brief list about sustainability goals based on Environment:
• Environment (all aspects related to resources exploitation) o Contribute to reduce or mitigate the environment natural hazard effects. o Contribute to reach UN goals for sustainable development
2.2.3 Economic
Economic, considering all the aspects from cost of items to the cost of the maintenance of systems. From the cost of services to their reliability, time resilience and adaptation, to the cost of the architecture and the cost of the overall governance.
A brief list about sustainability goals based on Economic viability.
• Economic (all aspects relate of business model, funds and financial): o Cost model based on Service-based approach combined with Cost-driven model; o Revenue Stream as mix of more financial funds; o Business development action aiming to support the Open Innovation and Open science. o Supporting actions to promote sustainable growth in terms of:
▪ Employment; ▪ Economic development of the territory and European countries.
Norms, Recommendations, Standards and Guideline
Social norms are a vital tool for promoting pro-environmental behaviour, but deploying them is more complex than may first appear. Social norms are a fantastic method of amplifying the influence of existing good behaviours, but they cannot bring about these good behaviours on their own. This means that social norm approaches have to be combined with more direct engagement strategies to be effective. For these reasons when sustainability concept need to be applied on organizations and in detail to science environment, social norms need to be supported by standards and guidelines provided by domain entities.
2.3.1 Social norms
Social norms are also the standards that are used to judge the appropriateness of our own actions, and it is now widely acknowledged that making pro-environmental social norms more visible is an important part of the challenge of promoting sustainable behaviour. In science such as laboratory studies and more applied, practical
H2020 – EINFRA – 2015 – 1 Page 12 of 75
settings, providing people with evidence of what others around them are doing has been shown to have a significant effect on behaviour. However, although social norms are a tried and tested method of influencing behaviour, their effectiveness hinges on positive norms being available for promoting in the first place. For many sustainable behaviours, the problem is not that positive social norms are not being highlighted, but that the norms are simply not there to promote. This means that social norm approaches have to be combined with more direct engagement strategies to be effective.
2.3.2 Standards and Guidelines
Sustainability standards and certifications are voluntary, usually third party-assessed, norms and standards relating to environmental, social, ethical and safety issues, adopted by companies to demonstrate the performance of their organizations or products in specific areas.
A short list of major entities dealing about sustainability aspects standardization follows:
• State of Sustainability Initiatives (SSI);
• United Nations Conference on Trade and Development (UNCTAD);
• International Institute for Sustainable Development (IISD);
• Sustainable Commodity Initiative (SCI);
• International Organization of standardization (ISO).
In detail, here the ISO standards to promote sustainable growth that enable businesses to plan their future growth around meeting consumer expectations. Furthermore, they enable transparency about products and best practices for limiting their impacts.
1. ISO 26000:2010 - provides harmonized, globally relevant guidance for private and public sector organizations of all types based on international consensus among expert representatives of the main stakeholder groups, and so encourage the implementation of best practice in social responsibility worldwide. This standard provides guidance on how business and organizations can operate in a socially responsibility way.
Figure 2 Governance / Reputation cycle
H2020 – EINFRA – 2015 – 1 Page 13 of 75
Above figure reports how the standard's application can help the organizations to reach sustainable business goals. Good governance affects Stakeholders perception and contributes to generate organization’s reputation as enable to sustainable development.
2. GRI G4 Guidelines – promote the use of sustainability reporting as a way for organizations to become more sustainable and contribute to sustainability development. GRI’s mission is to make sustainability reporting standard practice. To enable all companies and organizations to report their economic, environment, social and governance performance. GRI produces free sustainability reporting guidelines.
3. ISO 37101 – specifies requirements and provides guidance for establishing, implementing, maintaining, reviewing and improving an anti-bribery management system. The system can be stand-alone or can be integrated into an overall management system. Sustainable development in communities.
4. ISO 14000 - provide family of standards and practical tools for companies and organizations of all kinds looking to manage their environmental responsibilities. ISO 14001:2015 and its supporting standards such as ISO 14006:2011 focus on environmental systems to achieve this. The other standards in the family focus on specific approaches such as audits, communications, labelling and life cycle analysis, as well as environmental challenges such as climate change.
H2020 – EINFRA – 2015 – 1 Page 14 of 75
3 Open Science environment According with the OECD report 2015 “Making Open Science a reality” 4 the Open Science commonly refers to efforts to make the output of publicly funded research more widely accessible in digital format to the scientific community, the business sector, or society more generally. Open science is the encounter between the age-old tradition of openness in science and the tools of information and communications technologies (ICTs) that have reshaped the scientific enterprise and require a critical look from policy makers seeking to promote long-term research as well as innovation.
The term “Open Science” was coined by economist Paul David (2003) in an attempt to describe the properties of scientific goods generated by the public sector and in opposition to the perceived extension of intellectual property rights (IPR), into the area of information goods.
Economists consider scientific knowledge generated by public research as a public good, which means that everyone can make use of that knowledge at no additional cost once it is made public, generating higher social returns. The particularities of Open Science provide the policy and economic rationales for supporting it.
In the context of Open Science are summarized the following aspects: 1. Open Discovery, tools able to increase the efficiency of research as well as of its diffusion;
2. Open Access to scientific inputs and outputs as research outcomes;
3. Open Data, freely to available to everyone to use and publish, without restrictions from copyright, patents
or other mechanisms of control;
4. Open Methodology related to research strategy that outlines the way in which research is to be
undertaken;
5. Open Educational, allowing the broadens access to the learning and training traditionally offered through
formal education systems
All these aspects contribute to improve the effectiveness and productivity of the scientific and research system, by:
• Reducing duplication costs in collecting, creating, transferring and reusing data and scientific material;
• Allowing more research from the same data;
• Multiplying opportunities for domestic and global participation in the research process.
Scientific advice can also benefit from the greater scrutiny offered by open science, as it allows a more accurate verification of research results. In addition, increased access to research results (in the forms of both publications and data) can foster spill-overs not only to scientific systems but also innovation systems more broadly.
With increased access to publications and data, firms and individuals may use and reuse scientific outputs to produce new products and services. Open science also allows the closer involvement and participation of citizens.
There is growing evidence that Open Science has an impact on the research enterprise, business and innovation, and society more generally. Open Science is one of three priority areas for European research, science and innovation policy.
Today the European Union has 1.7 million researchers and about 70 million science and technology professionals engaged in the creation of new knowledge, innovation of products, service and processes. Digital infrastructures are the virtual backbone of European research and a vital driver for innovation. EU invests more than 850 million euros in digital infrastructure through the H2020 programme.
4 Available at: http://wiki.lib.sun.ac.za/images/0/02/Open-science-oecd.pdf
H2020 – EINFRA – 2015 – 1 Page 15 of 75
Recent analysis reveals that enhanced public access to scientific publications and research data increases the visibility of, and spill-overs arising from, science and research.
The calculation of economic value of research articles only and the related contribution to economic development is more problematic. Here some estimation based on regional studies are reported:
• In Australia the increasing accessibility generates a return of AUD 9 billion over 20 years (Houghton,
Rasmussen and Sheehan 2010).
• US federal research agencies over a transitional period of 30 years may be worth around USD 1.6 billion.
Around USD 1 billion would benefit the US economy directly, and the remaining amount would translate
in economic spill-overs to other countries.
• The European Commission Open data initiatives are expected to generate a yearly income of EUR 140
billion.
• OECD area could be around USD 500 billion plus an additional USD 200 billion if barriers to use were
removed, skills enhanced, and data infrastructure improved.
• UK organisations such as Royal Society and CEBR estimated that data were worth approximately GBP 25
billion to UK private and public sector organisations in 2016. The estimate is the cumulative result of GBP
17.4 billion gained in business efficiency, GBP 2.8 billion derived by business innovation and GBP 4.8 billion
gained from business creation.
Based on recent trends in the following figure the Open Access to scientific articles are reported for categories. Higher percentage of access is found in physics and astronomy, earth and environmental sciences; mathematics and social sciences as green open access. Gold open access is more common in Medicine, biochemistry or biology and related areas to medicine.
Source: UNESCO (2012), Policy Guidelines for the Development and Promotion of Open Access, UNESCO Publishing, and Björk et al. (2010), “Open Access to the scientific journal literature: Situation 2009”, PloS ONE, Vol. 5, No. 6.
Figure 3 Scientific articles publishing in the domain of Open Science
The key actors of Open Science are Researchers, Government entities; Research agencies; Universities; Public research institutes; Libraries; Repositories; Data centres; Private non-profit organizations; Foundations; Private scientific publishers; Business and finally the sopra-national entities such as OECD, UNESCO, EU and ESA in the
H2020 – EINFRA – 2015 – 1 Page 16 of 75
space sector. In the European Open Science context, the EOSC5 supported by EDI (European Data Infrastructure) is leading networking, data and computing service closer to European researcher and innovators.
European Cloud initiative will contribute for a competitive data and knowledge economy in Europe. Digital single market is a fundamental step towards the reinforcement of the EU’s competitiveness in digital technologies and in innovation. Cloud initiative will provide European science, industry and public authorities with world-class data infrastructures. The European vision about Open Science including Innovation6, report two main policy challenges.
1. Maximize RTD investment potential for science: a. Scientific processes, quality and effectiveness; b. Interconnecting computing & data infrastructures; c. Sharing data and data-driven science.
2. Increase innovation and contribute to prosperity: a. Data usage across scientific disciplines and between the public and private sector; b. Increasing exploitation of public data (research & big data).
According with the Open Innovation7, Open Science and Open the world8 publication, there are three major challenges:
1. We are too rarely succeeding in getting research results to market. Technologies developed in Europe are most of the time commercialised elsewhere.
2. Although Europe generates more scientific output than any other region in the world, in some areas we fall behind on the very best science. At the same time, there is a revolution happening in the way science works. Every part of the scientific method is becoming an open, collaborative and participative process.
3. Europe punches below its weight in international science and science diplomacy. EU collective scientific importance should be matched by a more active voice in global debates.
The EOSC initiative is the action carried out by the EC to foster and develop the Open science. It recently moves from a vision based on e-infrastructure based model, addressed to provide a set of tools and services on specific domains to an integrated eco-system of infrastructure – cloud computing – based on common service and data access. The new vision principles are:
• Open research data and Open science;
• Affecting the whole research science cycle and stakeholders;
• Addressing fragmentation issues (for data and service);
• Enabling multi-disciplinary and innovation;
• Widening to other constituencies (user & providers);
• Creating new policy issues, such as, copyright, data protection, text and data mining, open access policies and rights.
The expected impact of EOSC is addressed to:
• New paradigm for the public e-infrastructure community
• Removing the burden for scientific institutes
• Cross-fertilization of data coming from heterogeneous sources into the EOSC
5 Available at: https://ec.europa.eu/digital-single-market/en/%20european-cloud-initiative 6 Available at: https://ec.europa.eu/research/openscience/index.cfm?pg=home 7 Open innovation is the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively 8 Available at: https://publications.europa.eu/en/publication-detail/-/publication/3213b335-1cbc-11e6-ba9a-01aa75ed71a1
H2020 – EINFRA – 2015 – 1 Page 17 of 75
• Creation of market opportunities for EO data services
Monitoring Open Science worldwide now is possible with a new website9 launched as part of ongoing work for the European Commission. The monitor is going to provide policymakers and stakeholders with access to data and trends on Open Science. In the following figure is shows the wheel mechanism to explore Open Science characteristics and indicators.
Figure 4 Open Science monitoring indicators
The new website hosts a monitor developed by RAND Europe, Deloitte, Digital Science, Altmetric and figshare, which provides stakeholders, including researchers, policymakers, funders, libraries and publishers with access to data and trends on Open Science.
Open Science main players The worldwide players operating in the Open Science environment can be grouped in the following main categories: VRE, Virtual Laboratory, Science Gateway and e-infrastructure. These are relatively new concept of research organizations and associated technologies have maturated in the last 10 years. They are addressed to create a heterogeneous working environment in support of Scientists and Researchers. In additions, e-
9 See: https://ec.europa.eu/info/research-and-innovation/strategy/goals-research-and-innovation-policy/open-science/open-science-monitor_en
H2020 – EINFRA – 2015 – 1 Page 18 of 75
infrastructure experience and Government and not-Government Data and Service Providers, complete the Open research environment.
3.1.1 Virtual Laboratory
The Virtual Laboratory (Vl), is a network enabling Scientists in a number of different physical locations, each with unique expertise, computing resources, and/or data to collaborate efficiently not simply at a meeting but in an ongoing way. Overview of main players here below is reported:
• XSEDE (USA) - https://www.xsede.org/ is a single virtual system that scientists can use to interactively share computing resources, data and expertise. People around the world use these resources and services. Designed like supercomputers, collections of data and new tools.
• LTER (USA) - https://lternet.edu/ The largest and longest-lived ecological network in the United States
• NCRIS (Australian) - National Collaborative Research Infrastructure Strategy drives research excellence and collaboration between 35,000 researchers, government and industry to deliver practical outcomes.
• SHARE (USA) - http://www.share-research.org/about/stakeholders/ - SHARE is a higher education initiative whose mission is to maximize research impact by making research widely accessible, discoverable, and reusable. Now in SHARE 2.0.
3.1.2 Science Gateways
The Science Gateway (SG), is a "community-development set of tools”, applications, and data that is integrated via a portal or a suite of applications, usually in a graphical user interface, that is further customized to meet the needs of a specific community".
• CYVERSE (UK) – http://www.cyverse.org/ design, deploy and expand a national cyberinfrastructure for life sciences research and to train scientists in its use.
• NeCTAR (Australian) - https://nectar.org.au/about/ based on concept of term e-Research refers to the use of information technology to support existing and new forms of research. E-research extends e-Science and cyberinfrastructure to other disciplines, including the humanities and social sciences.
• NBDC (J) - https://biosciencedbc.jp/en/ national database center of Japan, integrating the scattered life science related databases all around the world, with an aim to optimize the value of the scientific data.
• SGCI - http://www.sgciafrica.org/ aims to strengthen the capacities of science granting councils in sub-Saharan Africa in order to support research and evidence-based policies that will contribute to the continent’s economic and social development.
3.1.3 Virtual Research Environment
The Virtual Research Environment (VRE) is a “set of online tools”, systems and processes interoperating to facilitate or enhance the research process within and without institutional boundaries. VRE provides a community of practice with the whole array of commodities needed to accomplish the community’s goal.
VRE Main features:
1. Research administration; 2. Resource discovery & access management; 3. Data creation, use and analysis; 4. Collaboration and communication; 5. Research publication, curation and preservation.
H2020 – EINFRA – 2015 – 1 Page 19 of 75
VRE project current experiences10:
• West-Life* - https://portal.west-life.eu/ World-wide E-infrastructure for structural biology.
• BlueBRIDGE* – http://www.bluebridge-vres.eu/ Building Research environments for fostering Innovation, Decision making, Governance and Education to support Blue growth.
• VRE4EIC* – https://www.vre4eic.eu/ A Europe-wide Interoperable Virtual Research Environment to Empower Multidisciplinary Research Communities and Accelerate Innovation and Collaboration.
• PhenoMeNal** – http://phenomenal-h2020.eu/home/ A comprehensive and standardised e-infrastructure for analysing medical metabolic.
• VI-SEEM* - https://vi-seem.eu/ VRE for regional Interdisciplinary communities in Southeast Europe and the Eastern Mediterranean.
• MuG* – https://www.multiscalegenomics.eu/MuGVRE/ Virtual Research Environment supports the expanding 3D/4D genomics community.
• OpenDreamKit* - http://opendreamkit.org/ Open Digital Research Environment Toolkit for the Advancement of Mathematics.
• LEARN*** - http://learn-rdm.eu/en/about/ Resources and toolkit of Best Practice for Research Data Management to help Research Performing Institutions manage their research data. Based on LERU method (League of European Research Universities)
3.1.4 e-infrastructure
The e-infrastructure is a combination of a set of resources such as: computing, data, networking, software, server and people (in the view of European Open Science Cloud – EOSC concept).
Main EU common e-infrastructure of services addressed to:
Seamless access and connectivity:
• EUDAT - https://www.eudat.eu/ Research Data Services, Expertise & Technology Solutions, CDI – Collaborative Data Infrastructure.
• CLARIN - https://www.clarin.eu/ European Research Infrastructure for Language Resources and Technology. CLARIN is an ERIC - European Research Infrastructure Consortium.
• ELIXIR - https://www.elixir-europe.org/ intergovernmental organization that brings together life science resources from across Europe. These resources include databases, software tools, training materials, cloud storage and supercomputers.
• ENES - https://portal.enes.org/ Network of European institutions about meteorological services to discuss strategies to accelerate progress in climate and Earth system modelling and understanding.
• EPOS – https://www.epos-ip.org/ Pan-European infrastructure for solid Earth science to support a safe and sustainable society
• ICOS - https://www.icos-ri.eu/ Pan-European research infrastructure which provides harmonized and high precision scientific data on carbon cycle and greenhouse gas budget and perturbations.
• LifeWatch - https://www.lifewatch.eu/ Data infrastructure for biodiversity and ecosystem community
• JADDS - Jülich Atmospheric Data Distribution Service of air quality model to science community. A performant and easy-to-use web service for sharing individually tailored model results on-demand
Storing data in a secure environment:
10 *Co-funded by EINFRA-9-2015 - e-Infrastructures for virtual research environments (VRE) ** Co-funded by EINFRA-1-2014 - Managing, preserving and computing with big research data *** Co-funded by NFRASUPP-7-2014 - e-Infrastructure policy development and international cooperation
H2020 – EINFRA – 2015 – 1 Page 20 of 75
• GEANT - https://www.geant.org/ Interconnects research, education and innovation communities worldwide, with secure, high-capacity networks.
• Network operations of GÉANT networks, ensure reliability, security and integrity. The operations are supported by collaboration with the following network infrastructures:
• EUMEDCONNECT - https://www.eumedconnect3.net/Pages/Home.aspx Connecting the research and education communities across eastern Mediterranean
• FED4FIRE - https://www.fed4fire.eu/ Federation For the Future Internet Research and Experimentation.
Computational resources:
• EGI - https://www.egi.eu/ is a federated e-Infrastructure set up to provide advanced computing services for research and innovation. The EGI e-infrastructure is publicly-funded and comprises over 300 data centres and cloud providers spread across Europe and worldwide.
• PRACE - http://www.prace-ri.eu/ enable high impact scientific discovery and engineering research and development across all disciplines to enhance European competitiveness for the benefit of society. PRACE seeks to realize this mission by offering world class computing and data management resources and services through a peer review process.
• INDIGO - https://www.indigo-datacloud.eu/ open source data and computing platform targeted at scientific communities, deployable on multiple hardware and provisioned over hybrid, private or public, e-infrastructures. By filling existing gaps in PaaS and SaaS levels, INDIGO-DataCloud will help developers, resources providers, e-infrastructures and scientific communities to overcome current challenges in the Cloud computing, storage and network areas.
• OpenMinTeD – http://openminted.eu/ OpenMinted sets out to create an open, service-oriented e-Infrastructure for Text and Data Mining (TDM) of scientific and scholarly content. Researchers can collaboratively create, discover, share and re-use Knowledge from a wide range of text-based scientific related sources in a seamless way.
Collaborative research:
• D4Science - https://www.d4science.org/ is an organisation offering a Hybrid Data Infrastructure service and a number of Virtual Research Environments.
• EarthServer2 - http://www.earthserver.eu/ provides Copernicus services by new vision of Big Earth Data through a disruptive paradigm.
• RDA – https://www.rd-alliance.org/ (Research Data Alliance) builds the social and technical bridges that enable open sharing of data. Researchers and innovators openly sharing data across technologies, disciplines, and countries to address the grand challenges of society.
3.1.5 Data provider
Data providers are the industrial organizations, providing EO data by remote sensing to the end-users.
• VITO – https://vito.be/en/about-vito VITO is a leading European independent research and technology organisation in the areas of cleantech and sustainable development, elaborating solutions for the large societal challenges of today.
• E-Geos - http://www.e-geos.it/ e-GEOS offers a unique portfolio of application services, also thanks to the superior monitoring capabilities of COSMO-SkyMed constellation, and has acquired leading position within European Copernicus Program. Application services include: monitoring for environmental protection, rush mapping in support to natural disaster management, specialized products for defense and intelligence, oil spill and ship detection for maritime surveillance, interferometric measurements for landslides and ground subsidence analysis, thematic mapping for agriculture and forestry.
• AIRBUS - http://www.intelligence-airbusds.com/en/5752-data-access-management As the amount and quality of available geospatial data grow, easy data access and efficient data management become the key
H2020 – EINFRA – 2015 – 1 Page 21 of 75
to successful operations. Hence Airbus Defence and Space offers a range of sophisticated data access and data management solutions, suitable for a variety of business needs.
• CNES - https://presse.cnes.fr/en/cnes-opens-access-copernicus-satellite-data-through-peps-platform With its unique fleet of six families of dedicated Sentinel satellites and payloads on Eumetsat satellites, Copernicus is set to generate a wealth of very-high-quality data with unequalled spatial and temporal coverage. To meet France’s needs, CNES is offering free access to these data via its Sentinel Product Exploitation Platform (PEPS).
• TerraNIS - http://terranis.fr/en/ world operator and distributor of Pixagri® et Oenoview® services, respectively in the agriculture and the wine-making sectors.
• CloudEO - http://www.cloudeo-ag.com/ with world-leading content and software providers, intends offer a unique geo-infrastructure as a Service bringing together data, software and processing power.
• SPACEBEL - https://www.spacebel.be/geospatial-information-systems/earth-observation-services/ relies upon numerous EO satellites to offer advanced services and consultancy support in optical (VHR), radar and hyperspectral technologies in several key domains: Forest, Natural & Mineral resources, Air, Territory, Industrial risks.
• AWS – https://aws.amazon.com/it/government-education/research-and-technical-computing/research-cloud-program/ AWS Research Cloud Program was designed by researchers to researchers to help them on science aspects, with minimal commitment and maximum confidence that data and budget are protected in the AWS cloud.
• MICROSOFT - https://enterprise.microsoft.com/en-au/digital-transformation/ Digital transformation is about reimagining how you bring together people, data and processes to create value for your customers and maintain a competitive advantage in a digital-first world.
• SAP – https://www.sap.com/products/technology-platforms.html# Redefine how your business operates and delivers products and services with cloud and data platforms. Explore new possibilities with real-time access to information, actionable decisions, and transformational innovation.
• Google - https://earthengine.google.com/ Google Earth Engine combines a multi-petabyte catalogue of satellite imagery and geospatial datasets with planetary-scale analysis capabilities and makes it available for scientists, researchers, and developers to detect changes, map trends, and quantify differences on the Earth's surface.
• USGS - https://www.usgs.gov/products/maps/overview Produce accurate geologic maps and 3-D geologic frameworks that provide critical data for sustaining and improving the quality of life and economic vitality of the Nation. They also organize, maintain, and publish the geospatial baseline of the Nation's topography, natural landscape, built environment and more.
• JAXA - http://www.eorc.jaxa.jp/en/research/ Observation data acquired by Earth-observing satellites, develop algorithms to derive geophysical parameters and to calibrate and validate satellite data, and try to maintain the quality of the data. JAXA thought Research Centre promotes research and application of satellite data in the fields of meteorology, control of forestry and fisheries resources, disaster prevention and national land use, and global environmental changes.
Data Business models in Open Science
The Open Data (including EO) market emerging Business Models in the contest of e-businesses or Virtual Organizations, including scientific initiative can be summarize as the following:
• Premium products / service (i.e. e-Geos, TerraNIS, Added-value products & services)
• Freemium product / service (i.e. mobile Apps, Google Pay Store, user pays for added-value service)
• Open Source (i.e. Red Hat free SW and support services under fee)
• Infrastructure capacity (i.e. Amazon Web Service, EUDAT, GEANT, EGI)
• Demand-oriented platform-based (i.e. SAP, AWS)
H2020 – EINFRA – 2015 – 1 Page 22 of 75
• Supply-oriented platform-based (i.e. Microsoft Open Government Data)
• Free as branded advertising (i.e. IBM May Eyes or Google Public Data Explorer – advertiser pays to sustain service.
Sustainability pillars tendencies
Based on the main Open Science players analysis, an overview about sustainability tendencies and common approaches follows.
From the Social responsibility point of view and available data, there a tendency to follow the common ISO 26000 main clauses of be partially compliant.
Environmental aspect is addressed to support a IT service infrastructure as distributed network of centres that aims to provide a set of tools and services addressed to end-user community. Or organized as a network of independent centres from each other but working within a common framework to develop and operate services on a pan-European level.
The Economic pillar is typically based on finance coming by the member countries. Each member country is committed to setting up and funding at national. In addition:
• Service portfolio, offering free-of-charge services (e.g. FREMIUM service) and a set of payment services (e.g. Professional services and training services).
• External Sponsorship is not usual.
• Membership subscriptions are present only in a few cases.
Here, in the following, a list of most significant use-cases around the world considered close to EVER-EST proposition.
3.3.1 GEANT - Storing data in a secure environment
Environmental: 38 National Research and Education Network (NREN) partners, the GÉANT network is the largest and most advanced R&E network in the world, connecting over 50 million users at 10,000 institutions across Europe and supporting all scientific disciplines. The backbone network operates at speeds of up to 500Gbps and reaches over 100 national networks worldwide.
Economic: GÉANT is an association of members with operations managed through its legal entities in the Netherlands and the United Kingdom. Funding comes primarily from the following sources:
• The European Union (EU), via the European Commission (EC), for the management of networking and related projects, or to participate in them.
• NREN network service subscriptions to co-fund the GÉANT Project (GN4-2). More about the GÉANT Project...
• Membership subscriptions (NREN and Associate).
• Earnings from the provision of administrative, consultancy and training services.
• Sponsorship for specific activities such as REFEDS and TNC.
3.3.2 EUDAT - Seamless access & connectivity
Environmental: EUDAT is currently organized as a network of independent centres from each other but working within a common framework to develop and operate services on a pan-European level
Economic:
• B2DROP, B2SHARE, and B2FIND are offered free of charge at the point of use to anybody and are available through the web.
H2020 – EINFRA – 2015 – 1 Page 23 of 75
• B2SAFE and B2STAGE typically require agreements between the user and the service provider. Such agreements can build upon existing relationships between some research communities and data centers, in particular when long standing agreements have been made with national funders to support a specific community through a national center or a designated service provider. Co-founded by H2020 programme.
• Individual agreements can also be concluded between a research community and individual EUDAT centre offering SLA-based services as part of the EUDAT collaborative framework.
3.3.3 CLARIN ERIC
European Research Infrastructure for Language Resources and Technology. CLARIN is an ERIC - European Research Infrastructure Consortium.
Environmental: structure based on distributed network of centres that host language resources and related services. Currently there are 38 of these Centres – mostly in Europe – each with its own expertise.
Economic: financed by the member countries. Each member country is committed to setting up and funding a national CLARIN Consortium, which may consist of various types of Centres.
3.3.4 ELIXIR
Intergovernmental organisation that brings together life science resources from across Europe. These resources include databases, software tools, training materials, cloud storage and supercomputers. The platform is oriented to the following use cases (VRCs): Human data, Rare disease, Marine metagenomics and Plant sciences.
Environmental: includes 21 members and over 180 research organisations. It was founded in 2014 and is currently implementing its first five-year scientific programme.
Economic: resource for of the ELIXIR Hub is provided by Member States. This budget is used to fund the secretariat in the ELIXIR Hub and commissioned services, which are carried out by ELIXIR Nodes. Short-term commissioned services are known as Implementation Studies, and longer-term commissioned services are known as Infrastructure Services.
• ELIXIR Nodes are typically funded through national investments, often made by countries as part of their membership in ELIXIR. For example, “Computerome” has been funded by Denmark as part of their investments in ELIXIR Denmark. The TeSS training portal has been supported through funding from BBSRC as part of its commitment to ELIXIR UK.
• The databases and services run by ELIXIR Nodes are usually pre-existing, and funded through a number of different sources including national grant funding, EU grants and charitable foundations.
3.3.5 ZENODO
Zenodo is developed and supported as a marginal activity and hosted on top of existing infrastructure and services at CERN, in order to reduce operational costs and rely on existing efforts for High Energy Physics. CERN has some of the world’s top experts in running large-scale research data infrastructures and digital repositories that we rely on in order to deliver a trusted digital repository.
Zenodo is funded by:
• European Commission via the OpenAIRE projects:
• FP7: OpenAIRE (246686), OpenAIREplus (283595)
• Horizon 2020: OpenAIRE2020 (643410) and OpenAIRE-Connect (731011).
• CERN
• Alfred P. Sloan Foundation
• Donations via CERN & Society Foundation
H2020 – EINFRA – 2015 – 1 Page 24 of 75
3.3.6 LTER
The Long Term Ecological Research network brings together a multi-disciplinary group of more than 2000 scientists and graduate students. The 25 sites encompass diverse ecosystems in the continental United States, Alaska, Antarctica and islands in the Caribbean and the Pacific—including deserts, estuaries, lakes, oceans, coral reefs, prairies, forests, alpine and Arctic tundra, urban areas, and production agriculture.
Service Model: by means of a Network Information System Data Portal contains ecological data packages contributed by past and present LTER sites.
Sustainability: The LTER Network receives its greatest funding from NSF (National Science Foundation – Government Agency). It is also supported by other Federal agencies such as:
• USDA Forest Service and Agricultural Research Services,
• National Aeronautics and Space Administration – NASA
• US Geological Survey,
• US Environmental Protection Agency
• US Department of the Interior’s National Park Service and Fish and Wildlife Service also support various projects at site and network levels.
Funding is given by NSF in the form of renewable six-year grants, which are independently peer-reviewed and are renewed based on the soundness of science and network participation. NSF conducts rigorous reviews of sites at the midpoint of each grant cycle, as well as a comprehensive review of the entire Network every 10 years.
In receiving funding from NSF, LTER agrees to conduct research on comparable ecological processes; make data accessible to the broader scientific community using common data management protocols; participate in cross-site and cross-agency research; and participate in network level and science synthesis activities.
3.3.7 NECTAR
Nectar (National eResearch Collaboration Tools and Resources project), provides an online infrastructure that supports more than 5000 researchers in Australia and around the world to collaborate and share ideas and research outcomes, and ultimately contribute to our collective knowledge.
Service Model: Nectar Virtual Labs are rich domain-oriented online environments that draw together research data, models, analysis tools and workflows to support collaborative research across institutional and discipline boundaries. They are built and led by the Australian research sector and are used nationally and internationally by the research community.
Sustainability: July 1, 2016 NeCTAR Research Computing Cloud moved to a consumption model to sustain its future in the national eResearch landscape.
The NeCTAR Cloud operating model is predicated on NCRIS funding augmented by the co-contribution of eight participating nodes, nominated roughly on a geographic basis and selected by competitive process. Intersect (twelve university members) initially contracted node model was based on member opt-in prepaid capacity plus operating expenses via consolidated revenue for the term of the original agreement.
H2020 – EINFRA – 2015 – 1 Page 25 of 75
4 The Vision for the EVER-EST Infrastructure11
What is EVER-EST
The EVER-EST H2020 project as Research and Innovation Action (RIA) in the framework programme of H2020, aims at developing a generic Virtual Research Environment (VRE) in Earth Science (objective 1) with the means to manage both the data involved in their disciplines and the scientific methods applied in their observations and modelling.
Through the VRE, the Scientists and Researchers can develop their research and attribute their findings, validate and share them within the scientific community or the general public (objective 2).
Central to this approach is the use of Research Objects (ROs) as semantically rich aggregations of data, methods and people in scientific investigations (objective 3). ROs allow encapsulating scientific knowledge and provide a mechanism for preserving, sharing and discovering assets of reusable and reproducible research.
The project is following a user-centric approach with four real use cases driving the implementation of the VRE. The EVER-EST project has a duration of 36 months and is implemented by a Consortium consisting of 12 partners with different expertise (i.e. EO Data providers, Infrastructure/Services/Technology Providers, Institutions and Research Communities).
EVER-EST in the European Open Science Context
The European Commission has recently made the European Open Science Cloud (EOSC) Declaration12 available to all scientific stakeholders, for their endorsement and commitments to the realization of the EOSC by 2020. The European Open Science Cloud (EOSC) aims to accelerate and support the current transition to more effective Open Science and Open Innovation in the Digital Single Market. It should enable trusted access to services, systems and the re-use of shared scientific data across disciplinary, social and geographical borders. The EOSC is indeed a European infrastructure, but it should be globally interoperable and accessible. It includes the required human expertise, resources, standards, best practices as well as the underpinning technical infrastructures. An important aspect of the EOSC is systematic data management and long-term stewardship of scientific data assets and services in Europe and globally.
The Commission intends to come forward with the implementation roadmap for the EOSC, and provide the necessary financial support under the Horizon 2020 work programme for 2018-20. Among others, the Research Infrastructures (including e-Infrastructures) part of the Work Programme 2018-202013 will contribute to EOSC implementation together with other EU and Member States initiatives. One key contribution comes from the Copernicus Data and Information Access Services (DIAS) aimed at providing Copernicus data and information access alongside processing resources, tools and other relevant data, with the objective to boost user uptake, stimulate innovation and the creation of new business models based on Earth Observation data and information as shown in the following image.
11 The entire section has been discussed by the whole consortium across the end of 2017 and beginning of 2018. Kicked off at the Reykjavik meeting (Oct.2017) the discussion has led to the conclusions which are reported as a consortium statement in its entirety in this chapter and paragraphs. 12 https://ec.europa.eu/research/openscience/pdf/eosc_declaration.pdf 13 http://ec.europa.eu/research/participants/data/ref/h2020/wp/2018-2020/main/h2020-wp1820-infrastructures_en.pdf
H2020 – EINFRA – 2015 – 1 Page 26 of 75
EVER-EST Vision
4.3.1 What we value
EVER-EST Virtual Research Communities will address grand challenges in Earth Science and nurture open science research toward a sustainable environment. Earth Science is becoming increasingly prominent as humanity confronts daunting challenges in finding natural resources to sustain Earth's burgeoning population, in mitigating natural hazards that impact life and infrastructures, and, more in general, in achieving sustainable environmental stewardship. EVER-EST VRE will sustain multi-disciplinary international research life cycle paradigms and support
Data Management Plan implementation in accordance with European data management requirements to plan, organize and document, store, protect, quality control, archive and peer review and publish sustainable research results content and make research results “FAIRest”14 . The efficient use of ROs through the EVER-EST VRE which is the environment integrating the use of ROs in a variety of different services, will allow achieving all these goals. The implementation of RO’s geospatial location will moreover boost innovation and facilitate responding to end-user and stakeholders challenges (e.g. policy makers).
4.3.2 Who we are
The EVER-EST Vision is to “Boost implementation of open science through innovation in the management and sharing of scientific information with the ultimate goal of ensuring Planet Earth sustainability”.
The EVER-EST Partnership will be described through a Position Paper that defines its intents, principles and governance model. In the partnership model under discussion we are assessing the possibility for each Partner Shareholder to contribute to the implementation of the EVER-EST Vision with:
• Making data, information and knowledge accessible through the VRE and engaging user communities advocating the use of the VRE for open science implementation (e.g. National and European institutions represented by the VRC's, Data Providers such as ESA, DLR);
• Infrastructure for virtual research environment and development platforms (e.g. MEEO, Terradue, ACS, PSNC);
• Innovative technologies for data and knowledge mining, stewardship, valorisation, sharing, reproducibility and interdisciplinary cross fertilization based on and exploiting Research Object content and metadata (e.g. PSNC, ESI);
• Sustainability aspects and model analysis in Open science world (e.g. Alma Sistemi)
• and through transferring knowledge from applied research to day by day operations (VRCs) through synergies with existing initiatives and projects (e.g. Thematic Exploitation Platforms, EOSC Hub, NextGEOSS).
In addition, progress in the implementation of the UN Resolution for the 2030 Agenda for Sustainable Development and European Open Science Cloud (EOSC) initiative will be continuously monitored and considered in relation to the EVER-EST Vision. The assets listed in the above bullets contribute to the EVER-EST Vision and Goals and the measuring of its performance indicators (KPIs) for the success of EVER-EST Mission and the fulfilment of its objectives.
New Communities will be invited to join the EVER-EST experience after the project lifecycle as well, to sustain the EU innovation path and knowledge sharing in support of the European Open Science Cloud Declaration.
14 Available at: http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf
H2020 – EINFRA – 2015 – 1 Page 27 of 75
4.3.3 Governance Model
Governance has been defined, in a common way, to refer to structures and processes that are designed to ensure accountability, transparency, responsiveness, rule of law, stability, equity and inclusiveness, empowerment, and broad-based participation.
Governance also represents the norms, values and rules of the game through which public or private affairs are managed in a manner that is transparent, participatory, inclusive and responsive. Governance therefore can be subtle and may not be easily observable.
In a broad sense, governance is about the culture of organizational environment in which people and stakeholders interact among themselves and participate in organization mission and goals.
EVER-EST project organization it was designed with a three-layers governance model: strategic, operational and advisory boards.
• The strategic board is composed of shareholders-stakeholders that have joined the EVER-EST Partnership and are sustaining the VRE Mission with contribution of resources (e.g. data, infrastructure and services, research results in the form of Research Objects, innovative technologies, funding).
• The operational board is comprised of the EVER-EST Virtual Research Environment service providers. These providers will operate and maintain the VRE platform and services based on a formal industrial agreement for Infrastructure and Services management and provision based on the EVER-EST service portfolio.
• The user advisory board is comprised of direct end-user stakeholders (e.g. VRC and user communities) whose forum will be consulted to monitor Key Performance Indicators and Mission objectives achievement.
Members may sit on one or more boards (e.g. VRCs may be part of strategic and advisory boards).
4.3.4 Positioning in Open Science
Where do we position in the current context? (AS-IS)
EVER-EST provides a platform for Earth Science Research and Operational Applications Lifecycle Management based on the innovative use of Research Objects. The EVER-EST Virtual Research Environment (VRE) has been customised for four different Virtual Research Communities and currently:
• Supports interdisciplinary Earth Science research and applications
• Enables transparency, sharing, reproducibility and accountability of research results
• Is the only VRE or collaborative digital environment which integrates the use of ROs to promote open science
Through the EVER-EST VRE, scientists are able to develop their research and to attribute their findings, validate and share them within the scientific community or the public. Central to this approach is the concept of Research Objects (ROs) as semantically rich aggregations of data, methods and people in scientific investigations. ROs allow encapsulating scientific knowledge and provide a mechanism for preserving, sharing and discovering assets of reusable and reproducible research.
A brief comparison matrix among Open Science initiatives addressed to Earth science, is in the following:
H2020 – EINFRA – 2015 – 1 Page 28 of 75
Table 1 Open science initiative comparison matrix
The EVER-EST VRE follows a user-centric approach, currently focusing on four heterogeneous Earth Science user communities, which have driven the implementation of the VRE, and is open to address the needs of communities within but also outside the Earth Science domain.
Where we want to be and position in the next phase? (TO BE)
EVER-EST shall bridge the Technological and Knowledge Gap and Barriers for open science, EOSC and FAIR principles implementation and digital innovation. The EVER-EST Partners competences and VRE Services Portfolio will boost open science implementation and facilitate thematic and interdisciplinary Earth Science Research and Innovation in support of the 2030 Agenda for Sustainable Development and European Open Science Cloud declaration. It will boost scholarly machine-readable papers reproducibility, sharing of and e-collaborative intelligence and innovation, and capability to underpin global challenges management and environmental policy decision-making.
The EVER-EST VRE is looking forward to provide a data and services portfolio layer on top of Copernicus DIAS and/or in the context of the EU Research Infrastructure, boosting the use of Copernicus data. EVER-EST will provide a research working environment centred on Earth Science users and scientists exploiting the RO concept to implement innovative services for preservation / collaboration / reuse / reproducibility / sharing of research results.
Earth Science users will be able to exploit the EVER-EST VRE “as a service” in its standard configuration, or customized to cover specific thematic Earth Science needs (VRE “a-la-carte”). The overlaying collaboration and sharing layer will enable and ensure cross-fertilization and interdisciplinary applications within and outside the Earth Science domain.
H2020 – EINFRA – 2015 – 1 Page 29 of 75
4.3.5 Choosing the EVER-EST solution
The full implementation of the Open Science paradigm can only be obtained through the implementation of technological solutions for the sharing, reusability and reproducibility of scientific information (including data, results, software, methodologies, etc.). ROs are potentially one of the most useful methods to share all types of information pertaining to the scientific process. EVER-EST has implemented an innovative collaboration environment which allows to fully exploit the potential of the RO concept.
Ongoing assessments have demonstrated the relevance of EVER-EST VRE contribution to the UN SDGs and the uniqueness and competitiveness of its mission to respond to one of the major challenge for Earth sustainability: understanding (i.e. unraveling the processes behind) the major global and regional processes involving different subdisciplines in Earth science. EVER-EST has the unique capability to:
a) sustain domain specific communities research; b) make thematic communities and data interoperable when working in the same geographical area; c) boost multi-disciplinarity and cross-fertilization across various Earth Science domains and Earth
Observation data both in situ and from space; d) foster synergies with other European Platforms (e.g. NextGEOSS15, LifeWatch16, BlueBRIDGE17).
Advocating for open science research by promoting use of open data and open dissemination of results and knowledge, raising awareness through participation in Earth Science Conferences and through direct end user and Stakeholders engagement, federating with other Virtual Research Environments, becoming interoperable with Data Infrastructure (EU DIAS, ESA Exploitation Platforms, European Research Infrastructures, Member States Collaborative Environments).
15 Website available at: https://nextgeoss.eu/ 16 Website available at: https://www.lifewatch.eu/ 17 Website available at: https://www.bluebridge-vres.eu/
H2020 – EINFRA – 2015 – 1 Page 30 of 75
5 EVER-EST Sustainability model EVER-EST is addressing grand challenges in Earth Science and nurture Open Science research toward a sustainable environment. Earth science is becoming increasingly prominent as humanity confronts daunting challenges in finding natural resources to sustain Earth's burgeoning population, in mitigating natural hazards that affect life and infrastructures, and, more in general, in achieving sustainable environmental stewardship.
EVER-EST will sustain multi-disciplinary international research life cycle paradigms and support Data Management Plan implementation in accordance with European data management requirements to plan, organize and document, store, protect, quality control, archive and peer review and publish sustainable research results content and make research results “FAIRest”18 .
According with Open Science sustainability tendencies, described in the 3.3 paragraph, here, the main five points considered in the EVER-EST sustainability model.
1. Partner Contributions of resources in EVER-EST (e.g. data, infrastructure and services, research results in the form of Research Objects, innovative technologies, funding).
2. Business Model able to generate the Revenues stream by providing VRE services. 3. Research Grants from public institutions (e.g. national research councils) to sponsor specific user
communities. 4. R&D Grants and opportunities for digital innovation and infrastructure/services research & development
at national and European level. 5. Research Synergies with other Research e-infrastructure initiatives (e.g. BlueBRIDGE, LifeWatch and/or
EPOS ERIC Project)
Goals
According with the three EVER-EST main objectives, here, the project goals set by the partners as commitment. :
• Become a VRE for Earth Science communities
• Gather a significant number of scientists in Earth Science, increasing drastically the user base both vertically (from the EVER-EST VRCs) and horizontally (from new VRCs)
• Improve quality of Research Objects, clean test/empty research objects
• Standardisation of Research Objects model and approach
• Promote citation of Research Objects
• Be maintained fully operational for at least one year after the end of the project
• Become a component of the e-infrastructures network
• Become a standard de facto
• Reach the level (technology matureness, service provision reliability, service quality and offering) of the current market solutions offering similar services and/or capabilities
Whilst referring to the UN Sustainable Development Goals (SDGs), set by the United Nations as in the following figure.
18 See: http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf
H2020 – EINFRA – 2015 – 1 Page 31 of 75
EVER-EST is pursuing goals according to most of UN, among which, Quality education, Life below water, life on land, sustainability communities and industry innovation and infrastructure.
Talking about the SGD 4 - Quality education, EVER-EST contribute to inclusive and quality education for all and promote lifelong learning; data scientist environment (based on Jupyter notebook integrated into ROs); actionable insights through executable paper and geo-spatial reference results. EVER-EST service components functionalities: E-collaboration, RO, Natural language processing, Earth Science language model.
The EVER-EST support to SDG 14 – Life below water can be summarized in conserve and sustainably use the oceans sees and marine resources; support of COCONET19, AMAre, EMODnet20 HRSM (High Resolution Seabed Mapping project in the framework of EMODnet bathymetry monitoring) and IDEM (Immunity, DEvelopment and Microbiota – H2020 project). EVER-EST service component functionalities: RO, Hyper Cube Multi – Dimensional Array, OGC Open Standard interoperability service exploitation.
The total number of SDGs targets is 169. The SDGs cover a broad range of social and economic development issues. These include poverty, hunger, health, education, climate change, gender equality, water, sanitation, energy, environment and social justice. The SDGs are also known as "Transforming our World: the 2030 Agenda for Sustainable Development" or Agenda 2030 in short.
Methodology and approach
The methodology and approach chosen and applied are aimed to be used in different ways by organisations having dissimilar knowledge and levels of maturity concerned with governance of sustainability.
Hence, those having an already existing sustainability policy and strategy could find the model useful to verify different mind-set. Or, it can be found by organisations just coming into the matter using the model for more strategic service-wide sustainability planning.
The key elements governing the approach are:
1. Governance of the services and underpinning infrastructure;
19 COast to COast NETworks of marine protected areas, available at: https://www.msp-platform.eu/projects/coconet-towards-coast-coast-networks-marine-protected-areas-shore-high-and-deep-sea 20 European Marine Observation and Data Network, available at: http://www.emodnet.eu/
H2020 – EINFRA – 2015 – 1 Page 32 of 75
2. Relationships inside and outside the EVER-EST ecosystem; 3. Decision points; 4. Planning.
While for the sustainability model development, the following process-cycle in four steps was applied:
Figure 5 Sustainability methodology model
These concepts must be considered also in the frame of a continuous evolution according to the classing Deming cycle.21
Main Stakeholders Based on market research22, addressed mainly to the EVER-EST stakeholders the following estimation is reported about potential VRCs - users
1. Land monitoring community # of major institutions, about 26
2. See monitoring community # of major institutions, about 20
3. Natural hazard community # of major institutions, about 20
4. Supersite community # of major institutions, about 23
Potential partners with which pursue a network agreement to enlarge project end-user community
21 is an iterative four-step management method (Plan-Do-Check-Adjust) used in business for the control and continual improvement of processes and products. 22 Annex A - complete list of stakeholders / potential customers, including details, is available in a dedicate file: EVER-EST Stakeholders data
collection.
VRC’s user-needs
Service:
1) Portfolio model
2) Governance 3) Provisioning 4) SLA of
operations
Worldwide experiences on:
1) Research SW sustainability;
2) Research infrastructure sustainability;
3) Cost Benefit analysis on research infrastructure;
4) Business model generations as CANVAS;
5) Business model addressed to support technology innovation.
H2020 – EINFRA – 2015 – 1 Page 33 of 75
• VREs projects, about 13
• E-infrastructure, about 16 (European and no-European)
• World-wide data provided and distributors, about 14
The Stakeholders data collection represents a first assessment of potential customers to which address the Promotion strategy, already along the dissemination project actions and in the first year of business plan (pre-operations period) after project lifecycle.
Short-term and long-term potential competitors
Looking at the present market players, there are no direct competitors to perform a complete comparison, due to the fact we are in the science world. Taking into consideration digital services market, the operator offering Cloud computing services, seem to be the closest to the EVER-EST offer: in terms of delivery model and service approach, oriented to the user needs.
In the domain of Open Science, the services offered by e-Infrastructures, SG and Vls are for free, while professional services and advice are promoted. So, the comparison with cloud computing services that today provide, storage, editing, versioning, the sharing and preservation can be taken as potential competitors, although they are only partially comparable with the EVER-EST portfolio.
H2020 – EINFRA – 2015 – 1 Page 34 of 75
Table 2 Potential competitors in Cloud computing service
In long term, all the project experiences of e-infrastructures, such as EUDAT, EPOS, GEANT, developed in the Open Science environment, will can be potential competitors, sharing the market. Further the Data Providers, operating in the domain of EO such as: DIGITAL GLOBE, PLANET, GOOGLE, URTHECAST and AWS.
Data Value Chain
Recent technology advanced such as: free satellite EO data, new satellite constellations (i.e. Copernicus and Galileo), unmanned systems, remote sensing payloads and new data analysis techniques (i.e. big data and data analytics); open to new possibilities to new data value chain supporting new service portfolio addressed to scientists in a view of Open innovation and Open Science.
Creating value from data requires a new mindset. To holistically exploit the opportunity of big data tools and architectures, a new way of thinking is needed that frames data as a raw material of business. In case of science environment, raw material enabling development to the benefit for the Citizens.
The answer is to focus not on the functional components, what organizations do to the data, but on the outcomes and how they can be achieved. What they do with the data.
This novel approach can be cultivated through looking at the data value chain. From discovery and ingest through analysis and exposing results, this series takes a detailed look at these seven data value chain steps.
H2020 – EINFRA – 2015 – 1 Page 35 of 75
Each step receives an overview of the spectrum of strategies, tools, and architectures that are available today. The resulting understanding enables data scientists and other analysis professionals to analyse for suitable areas to make investments that can create new value from data. In the following figure, EVER-EST value chain is shown.
Figure 6 EVER-EST data value-chain
EVER-EST Services platform
EVER-EST IT service platform provides an ease and cheaper access to independent customer segments, allowing them seamless end-user's services, thereby strengthening the network’s effects. This kind of product/service organization can be considered into a platform-based model. This new business model use technology to connect people, organizations and resources in an interactive ecosystem in which unlimited amounts of value can be created and exchanged.
The EVER-EST platform can be summarized into the following main pillars:
• A Service Portal aimed an user interface and providing the entry points for service portfolio.
• An e-infrastructure aimed at maintains and let available the Virtual Research Environments tools, application and accesses of each scientific community.
• A Service portfolio aimed to put in place a set of services addressed to the end-user needs. In the EVER-EST vision the portfolio services were created on the base of the by added-value and provided by category of services and by the Human Machine Interface tools.
H2020 – EINFRA – 2015 – 1 Page 36 of 75
Figure 7 Service infrastructure logic
5.6.1 Service Portfolio
It is addressed to the Customer's and end-users needs and expectations. The portfolio aims to provide added-values services, according to the value proposition defined for each of them.
Here, the complete list of EVER-EST end-user services including description and technical partner’s involvement in the operations.
Table 3 Service portfolio
In the following, figure the liaison among, service added-value, category and the Human Machine Interface tools:
H2020 – EINFRA – 2015 – 1 Page 37 of 75
Figure 8 EVER-EST Added-value, service category and HMI
5.6.2 The Governance
As already mentioned, a three-layers governance model, taking into the account the strategic and operational governance and the advisory boards.
Figure 9 EVER-EST Governance
The Strategic board is composed of shareholders-stakeholders that have joined the EVER-EST Partnership and are sustaining the VRE Mission with contribution of resources.
H2020 – EINFRA – 2015 – 1 Page 38 of 75
The Operational board is comprised of the EVER-EST Virtual Research Environment service providers. These providers will operate and maintain the VRE platform and services based on a formal industrial agreement for Infrastructure and Services management and provision based on the EVER-EST service portfolio. The agreement should include return from R&D Grants and opportunities for digital innovation and infrastructure/services research & development at national and European level.
The Advisory board is comprised of direct end-user stakeholders, whose forum will be consulted to monitor EVER-EST Key Performance Indicators and Mission objectives achievement.
Governance model aims to reach the following goals:
1) Guarantee the Operations of ICT structure and Services delivery; 2) Respect of Policies and Standards; 3) Monitoring of services performance in respect of Service Level Agreement; 4) Maintenance of ICT structure; 5) Management of evolution and improvements.
5.6.3 Service Level Agreement
The EVER-EST service provisioning to VRC’s users complies with the following Service Level Agreement – SLA.
Figure 10 Potential SLA schemas
SWOT Analysis
At today, SWOT analysis about portfolio services is the following reported:
Strengths Weaknesses
o E-Collaboration Vs TEP
o E-Research Vs TEP
o Preservation Vs standard e-
infrastructure
o RO technology
o Domains service
o Platform-based business model o Industrial partner agreement
o Partnership agreement with LifeWatch
o Lack of networking robustness
o No funding scheme for service provisioning in a pre-commercial
phase
H2020 – EINFRA – 2015 – 1 Page 39 of 75
Opportunities Threats
• Collaboration with e-infrastructure (i.e.
GEANT, EUDAT, BlueBridge, )
• Agreement with Data providers (i.e.
AWS, Google Earth)
• Increasing market penetration by:
• new entities operating in the framework of 4 project VRC
• New VRCs interested in Earth Science VRE
• Agreement with Public Entities
• ……
• Multi-disciplinary e-infrastructure (i.e. VRE4EIC)
• Regional e-infrastructure (i.e. VI-SEEM) • Worldwide Data providers offering
products & service to science communities in a thematic
environment (i.e. Google Earth, Moon web services)
Table 4 EVER-EST VRE SWOT analysis
The analysis reports the following aspects to be considered in the future operations scenario at the end on project lifecycle. There are some weaknesses on: networking with European e-infrastructure i.e. such as: EUDAT, not yet investigate for funding strategy supporting pre-commercial phase and lack on reference standards. These aspects were taken into consideration in the EVER-EST vision process.
At the same time, some threats coming up from other Open Science initiative. These must to be considered in the service business model in order to mitigate theirs effect on EVER-EST service market penetration.
EVER-EST in sustainable pillars
The present paragraph reports the sustainability analysis based on the main pillars. Each topic was treated individually, but thanks to the ISO 26000:2010 standards it is possible to carry out a joint assessment.
5.8.1 Social responsibility
Here, in the following figure, the compliant matrix of EVER-EST according to ISO 26000:2010 standards and GRI G4 guidelines:
H2020 – EINFRA – 2015 – 1 Page 40 of 75
Table 5 Social responsibility EVER-EST compliant analysis – part 1
H2020 – EINFRA – 2015 – 1 Page 41 of 75
Table 6 Social and Environment EVER-EST compliant analysis – part 2
H2020 – EINFRA – 2015 – 1 Page 42 of 75
The assessment was carried out taking into account the following aspects:
• Create a long-term open science sustainability model;
• Promote actions in support of stable employment;
• Contribute to creating the European Open Science Cloud;
• Contribute to strengthening both the Scientists and citizen's awareness of the benefits of Earth Science.
5.8.2 Environment
As previously report, the ISO 26000:2010 help the organization to make their impact assessment in the environment. EVER-EST is based on service infrastructure model, distributed as a network of centres. EVER-EST aims to provide a set of tools and services addressed to end-user community. EVER-EST ICT platform was design to pay attention to:
• Reduce or mitigate the environment natural hazard effect.
• UN goals for sustainability development.
5.8.3 Economic
Main assumptions about economic analysis, consider the following business operation conditions:
• Forecast hypothesis of operations after completion of the project, about 5 years
• Typical ROI time frame from comparable industrial best practices, 5-8 years
• Comparison with similar initiatives.
The economic pillar is addressed to:
• Cost model based on the Service-based approach combined with Service Cost-driven.
• Revenues streams generated mainly by the following sales service models: 1. PREMIUM (Platform as a Service – PaaS) Exploitation of the VRE by large European Initiatives and
institutions (e.g. Research Institutions, Data Providers), which provide scientific data and services to third parties (e.g. their end users). Exploitation might be related to: o Organization internal needs (e.g. for data curation and valorisation and knowledge sharing); o Support to Organization End Users: End users would be able to exploit the EVER-EST VRE “as a
service” in its standard configuration or customized for the Research Institution or Service Provider to build thematic Earth Science VRE “a-la-carte”.
Revenue Streams are generated by the following service model features: ➢ Service access by subscription; ➢ Portfolio service: all functionalities; ➢ VRC Portal and Services with environment customization per customer; ➢ Condition to subscribe premium: payment of fee per user; ➢ €50k annual fee includes 50 end-users; ➢ €10k of annual fee includes additional 25 end-user. ➢ Service configuration;
o Authentication service. o Tools - open; o Computing Power open; o Storage open; o Users Using Published Content; o RO-HUB open access; o Standard Service Level Agreement guaranteed.
H2020 – EINFRA – 2015 – 1 Page 43 of 75
2. FREEMIUM (PaaS) Exploitation of the VRE focused on gathering a significant community of scientists around the globe and a critical mass of high-quality research objects. Revenue stream here will follow a “Freemium” model based on sponsor (to support user subscription), publicity (publications, scientific articles. If subscribed, a user would not be presented with publicity while using the platform but shall be asked to commit the provision of a minimum number of open and qualified Research Objects. This approach could also be sponsored by Research Institutions (e.g. inviting Principal Investigators to use the EVER-EST VRE to publish and peer-review their Research Objects). Service feature model:
➢ Service access max 10 end-users per each Customer segment; ➢ Portfolio service: addressed to adoption and content production; ➢ Condition to subscribe freemium: User Producing Content. ➢ Service configuration:
o Authentication; o Tools - JUPITER notebook for Research Object production; o Computing Power: 1 Virtual Machine; o Storage: 15 Tera (space on C-file; o Users Using Published Content; o RO-HUB open access; o No Service Level Agreement guaranteed.
Furthermore, others potential funding sources are considered:
• Partner Contributions of resources in EVER-EST (e.g. data, infrastructure and services, research results in the form of Research Objects, innovative technologies, funding).
• Private Sponsorship in support of researchers to which the offering will provide a suit of free-of-charge services (FREMIUM) and a set of payment services (PREMIUM).
• Research Grants from public institutions (e.g. national research councils) to sponsor specific user communities
• R&D Grants and opportunities for digital innovation and infrastructure/services research & development at national and European level.
• Research Synergies by strategic partnership with other Research e-infrastructure initiatives (e.g. Lifewatch and/or EPOS ERIC Project). In this framework can be explored the INNO_CENTIVE23 service model.
Research Synergies are based on the idea about Internet platform can offer an opportunity to make cooperation. INNO_CENTIVE works like a social network, connecting big companies or not-profit organizations such as Open Science bodies, with innovative thinkers in various fields. Seekers (e.g. Industry, Government) post the challenges on the webpage. People (e.g. Researchers, Scientists) who act as Solver, can post innovative solutions in different field on the platform and if chosen, will be rewarded by the Seeker. The Public-Private Partnership one additional way to make synergy, is a cooperative arrangement between two or more public and private sectors, typically of a long-term nature. This paradigm enabling creative minds to solve challenges in the Earth Science domain to sustain the UN Resolution for the 2030 Agenda for Sustainable Development and European Open Science Cloud (EOSC) initiative through sponsored calls for ideas and crowdsourcing to respond to Earth Science challenges from end-user stakeholders.
23 See: CEO interview: The InnoCentive model of open innovation by Robert J. Allio Brown University.
H2020 – EINFRA – 2015 – 1 Page 44 of 75
6 EVER-EST Business Models The Business Model describes the design or architecture of the value creation, delivery and capture mechanisms employed. The essence of a business model is:
1) Collect customer needs and it ability to pay; 2) Defines the manner by which the business enterprise responds to the needs and which values deliver to
customers; 3) Entices customers to pay for the values; 4) Converts those payments to profit through the proper design and operation of the various elements of the
value chain.
In the EVER-EST project, the CANVAS model24 was taken as reference to generate a sustainable business model addressed to the Customer Segments identified.
EVER-EST IT platform can be considered an e-infrastructure that support the platform-based business model25, with the peculiarity of co-existing more business models approaches such as:
• Multi-sided platform26 - In this approach, the value is created by facilitating interactions between two or more distinct but interdependent groups of customers; the generated values attract more users creating a network effect (i.e. Google, AWS).
• Free – in this approach at least one substantial customer segment is able to continuously benefit from a free-of-charge. The service portfolio is financed by other business model approaches or costs are supported by other customer segments (i.e. Dropbox, Urthecast).
Customer Segments
The customer segments building blocks defines the different groups of organizations an enterprise aims to reach and serve. Studying EVER-EST IT platform, there are more than one Customer group, because potential customers:
• needs require and justify a distinct offer;
• are reached through different distribution channels;
• require different types of relationships;
• have substantially different profitability;
• are willing to pay for different aspects of the offer.
The key Customers segments targeted by the EVER-EST portfolio service are:
1. Research Organizations Such as: INGV/ CNR-ISMAR. Representing the main customer segment driving the Open Science end-users Main added-value: “Research Lifecycle Management and Management of executable paper”. Executable paper management support re-use of research outcomes, resources and aim to funding optimization.
2. European Added-value Service Providers (Gov-not Gov) Such as: SatCEN, NHP. Main added-value: “Information as a service”
3. Data Providers & Distributors Such as: ESA/ DLR. Main added-value: “Data Stewardship27
24 See description at: https://en.wikipedia.org/wiki/Business_Model_Canvas 25 See: Harnessing platform-based business model to power disruptive innovation article at:
https://www.emeraldinsight.com/doi/pdfplus/10.1108/SL-07-2016-0061# 26 See: Business Model Generation, A. Osterwalder, Yves Pigneur, Alan Smith, and 470 practitioners from 45 countries, self published, 2010 at: https://profesores.virtual.uniandes.edu.co/~isis1404/dokuwiki/lib/exe/fetch.php?media=bibliografia:9_business_model_generation.pdf
H2020 – EINFRA – 2015 – 1 Page 45 of 75
Furthermore, there are in the Open Science environment scientific institutions with which to establish relationships and partnership to enlarge users:
4. European Research Infrastructures
Such as: LifeWatch, BlueBRIDGE (i.e. consortium and private organization)
Main added-value: “Research Content Management System”
5. Funding agencies
Such as: EC entities
Main added-value: “Support and Management Open Science”
Value Proposition
The Value Proposition building block describe the bundle of products and services that create value for a specific Customer segment. Value proposition analysis is around the following questions:
What are we offering to customers, what we can do for them and do they interest on it?
Value proposition process makes from one side the analysis of customer profile (job), the needs (pains) and expectations (gain). from the other side, on the base service portfolio, the value proposition created. Here, in the following tables the value proposition for the most significant Customer Segments of EVER-EST, is described:
Research Organization
Customer Profile Value Proposition Added-Values
Job
INGV (Functional job) Publishing scientific research. Stepping stones: Analysis and processing capacities; Intellectual property attribution and Data access. CNR-ISMAR (functional job)
Portfolio service
e-Research e-Collaboration e-Learning Preservation Free service o Cloud services
- RO hub access - RO management - Data Catalogue
o Common services
- Identity management
- ESB - Data analytics
Research lifecycle Mgmt. Citation; Cross fertilization; Machine read. / exec. Paper;
Pains
Undesired outcomes, problems, and characteristics o Insufficient or low-
Pain relievers
• RO can help to mitigate to lack of resources
• e-Research support
27 Data stewardship is the management and oversight of an organization's data assets to help provide business users with high-quality data that is easily accessible in a consistent manner.
H2020 – EINFRA – 2015 – 1 Page 46 of 75
quality data (severe) o Lack of resources
(severe) o Lack of expertise
(severe) o Difficult data access
(minor) o Difficulty in
collaboration (minor) Risks (undesired potential outcomes)
• Failure of scientific investigation (severe)
• Lack of resource support (minor)
the need of resources
• Data catalogue allows easy EO data access and improve quality of available data
• E-Collaboration supports teamwork and sharing of expertise and knowledge
Data scientist support; Citizen scientist support; Cloud sourcing; Research rating; Publication & DOI Mgmt.; Service customization; Peer review; Data processing and analysis; Data reusability Long- term preservation.
Gains
Required gains
• Easier access to data and computing resources
• Easier access to better education/training
• More collaborative environment for capacity building
Expected gains
• Easier access to data and resources
• Easier access to better education/training
• More collaborative environment for capacity building
Desired gains
• Unexpected
• Improve research funding capacities
Gain creator
Performance: o Service performance
Convenience: o Financially
convenient Cost reduction: o Free service pack
Accessibility: o Resources:
Customization: o Tailoring service
Risk reduction: o Cooperation with e-
infrastructure
Table 7 Research Organization value proposition
H2020 – EINFRA – 2015 – 1 Page 47 of 75
European Added-value Service Providers
Customer Profile Value Proposition Added-Values
Job
SatCEN (functional job) Perform imagery analysis, extract and interpret information, write reports. Extract information from satellite imagery and sharing information with stakeholders. Easy and reliable access to data, automatic processing tools and information sharing mechanisms. NHP (functional job) Creation of hazard impact models based on weather forecasts. Stepping stones Collaboration with all NHP partners; Regular meetings (physical or virtual): Data sharing; Method testing and development; Sharing of results
Portfolio service
Processing Campaign Executable Paper Organization workflow Free service
• Cloud services - RO hub access - RO management - Data Catalogue - Common services - Identity
management - ESB - Data analytics
Research lifecycle Mgmt. Data scientist support User-oriented service portfolio Software As a Service Web processing services High performance Gov-not Gov Citation Data scientist support Research rating Publication & DOI Mgmt. Pains
Undesired outcomes, problems, and characteristics o Difficulty to produce
predictive output – severe
o Difficulty to arrange physical meetings - minor
Risks (undesired potential outcomes)
• Failure of scientific resources and collaboration – severe
• Lack of resource support the travel and staff time - medium
Pain relievers
• EVER-EST service portfolio can help to mitigate to lack of resources
• e-Research support the need of expertise
• Data catalogue reduce difficult data access and quality of data
• E-Collaboration help to reduce the difficulty in collaboration
Gains Required gains
• Saving time taken up by Gain creator Customization:
• Tailoring product
H2020 – EINFRA – 2015 – 1 Page 48 of 75
holding face to face meeting
• Effective people collaboration
• Continuous sharing of data and method so that output
• Modelling output to specific stakeholders
Expected gains
• Visibility of work to potential stakeholders
• Improve services offered: quality
• More regular publishing to scientific community
Desired gains
• More guaranteed funding
• Tailoring service Cost reduction:
• Free service pack
• Synergy of resources
• Infrastructure sharing
Risk reduction:
• Supplier affiliation
• Cooperation with e-infrastructure
Accessibility:
• Resources Collaboration
Table 8 European Added-Value Service Provider value proposition
Data Providers & Distributors
Customer Profile Value Proposition Added-Values
Job
ESA (functional job)
Portfolio service
Processing Campaign Executable Paper Organization workflow DOI attribution dataset Free service o Cloud services
- RO hub access - RO management - Data Catalogue
o Common services
- Identity management
- ESB - Data analytics
Machine read. / exec. Paper;
Data scientists support; Mission Data valorisation & exploitation; Data Curation; Multi-mission Cross Data; Publication & DOI User-oriented service portfolio; Technology As a Service – RO High Service Performance
Pains
Undesired outcomes, problems, and characteristics o No efficient
preservation of data
Pain relievers
• EVER-EST service portfolio can help to mitigate to lack of resources
• e-Research support
H2020 – EINFRA – 2015 – 1 Page 49 of 75
o No efficient sharing of data
o No re-use of data Obstacles
• Not homogeneous protocols of data processing and sharing
• Old Scientists generation don’t share data in efficient way
Risks (undesired potential outcomes)
• Lack of funds needed to support research
• Loosing big amount of data due to lack of preservation strategy
the need of expertise
• Data catalogue reduce difficult data access and quality of data
• E-Collaboration help to reduce the difficulty in collaboration
Gains
Required gains
• Saving time in data processing
• Use friendly system to manage and preserve data
• Easier access to better education / training
Expected gains
• Increase of publications
• Visibility from public audience
Desired gains
• Contribution to quality of environment
• Collaboration environment without barriers in sharing data
• Decrease cost of computing capabilities and storage.
Gain creator
Performance: in terms of:
• New services
• New functionalities Customization:
• Tailoring service Cost reduction:
• Synergy of resources
• Infrastructure sharing
Accessibility:
• Service
• Open data, big data
• Resources Collaboration
Table 9 Data Providers & Distributors value proposition
Channels
The Channels building block describes how an organization communicates with and reaches its Customer segments to deliver a Value Proposition. Channels analysis answer to the following questions:
How does each Customer segment want to be reached? Through which interaction points?
H2020 – EINFRA – 2015 – 1 Page 50 of 75
EVER-EST service provisioning is based on two main channels:
1. Own channel (direct) – by the project consortium in the dissemination, exploitation activities and after lifecycle of project, during the commercialization phase. Project partners are already committed to collaborate each other for the development of EVER-EST infrastructure through the Consortium Agreement. This is a channel have higher margins but includes initial investment to put in place and to operate. Research organization is the customer segment achieved by this channel.
2. Partner channels (indirect) - by VRCs and EO private and public organization and communities engaged during the dissemination activities. This channel lead to lower margins but allows an organization to expand its reach and benefit from partner strengths. European service providers and Data providers are the customer segments achieved with this channel in addition of the first one.
A right balance between the different types of channels will integrate them in a way to create a great customer experience and to maximize revenues.
Customer Relationships
The Customer Relationship building block describes the types of relationships an organization establish with specific Customer Segments. This analysis answer to the following questions:
What relationships are you establishing with each segment?
Personal, automated – self-service, acquisitive as communities or co-creation? In the EVER-EST the following relationships are considered:
o Personal by digital communication; o Communities by VRCs players aim to build-up a network; o Co-creation inviting customers to promote and resell.
Revenues Stream
This CANVAS building block represents the cash an organization generates from each Customer segment. This analysis answer to the following questions:
What is customer really willing to pay? How?
Are we generating transactional or recurring revenues?
Further Revenues Stream model need to consider the price mechanisms: fixed pricing or dynamic pricing strategies. In the first price is determined in advance, whilst the second, the price can change based on market conditions.
Based on the EVER-EST service portfolio maturity level and the orientation for the sustainability models; in the following list the revenues streams scenarios:
• Main stream generated by VRE services provisioning based on PREMIUM service.
• Additionally, from: o Sponsorship of private Institutes or by Communities in support of Researchers – FREMIUM service
and a set of PREMIUM service. o Contributions by EVER-EST Partners (i.e. data, infrastructure and services, research results in the
form of Research Objects, innovative technologies, funding). o Research Grants from public institutions (i.e. national research councils). o R&D Grants and opportunities for digital innovation and infrastructure/services research &
development at national and European level.
H2020 – EINFRA – 2015 – 1 Page 51 of 75
o Synergies with other Research e-infrastructure initiatives (e.g. LifeWatch, BlueBRIDGE and/or EPOS ERIC Project) with the purpose to improve the collaborative working, share data and adoption of best practices.
Funding may come from the above sources to sustain the common vision and VRE. This will allow flexibility and diversification in the resource’s contribution.
Key Resources
The Key Resources describe the most important assets required to make a business model work. This analysis answer to the following questions:
Which resources underpin our business model?
Which assets are essential? Based on Platform-based model the following resources allow the EVER-EST to create a Value Proposition, reach markets, maintain Relationships with Customer and earn Revenues:
• Physical - IT infrastructure and network with other e-infrastructure initiatives;
• Intellettuale – Tools and Database;
• Human – knowledge;
• Financial – funds, sponsorships and revenues.
Key Activities
In the Key Activities building block are reported the most important things an organization must do to make its business model work. This building block answer to the following questions:
Which activities do you need to perform well in business model?
What is crucial?
In the EVER-EST services provisioning the following activities are identified: 1. Making - Service Production; service delivery and problem solving about customer needs; 2. Selling – Channels management and customers assistance; 3. Supporting - EO service platform Management, networking with other Open Science initiatives.
Key Partnerships
The Key Partnership represent the network of suppliers and partners that make the business model work. In this block, questions to answer are:
which partners and suppliers leverage your model? who do you need to rely on?
EVER-EST consortium is composed by a several companies and institutions that represent well-integrated and not replicated capacities. It represents the whole value network involved in the service production and provision: from infrastructure design to system deployment. Here the partnership approach defined in EVER-EST project and over the its lifecycle:
1. Strategic alliance in the Consortium partners. 2. Cooperation approach with:
• Universities;
• Research Accademie;
• Data Providers;
• Science Gateway;
H2020 – EINFRA – 2015 – 1 Page 52 of 75
• Virtual Labs;
• VRCs. 3. Buyer-Supplier relationship with IT solution providers.
Cost Structure
The Cost Structure is based on the estimation of cost model. It can be a mathematical algorithms or parametric equations used to estimate the costs of a Product / Service (Service-based) or Project (Project-based).
Modelling methodology includes the following steps:
1. Data gathering – collection of relevant data (i.e. Fixed and Variable costs). 2. Data preparation - removing and replacing missing data or standardize the data. 3. Model building - technique of costs prediction on the commodity cost through a time window and
economy approach (i.e. Economies of Scale or of Scope). 4. Dashboard - overview of forecast or prediction over the commodity price by manipulating the key variants
found in the model building.
According to the CANVAS business model, the followings cost approaches were to take into consideration: 4. Cost-Driven – This business model focuses on minimizing all costs and having no frills. (e.g. low-cost
services): ➢ Asset cost-base; ➢ Service production cost-base; ➢ Percentage of service production base.
5. Value-Driven – Less concerned with cost, this business model focuses on creating value for their products and services. (e.g. added-value services).
In the CANVAS business model, the Service-based approach combined with the Cost-driven model are considered as most appropriated to lead the service provisioning to Science community. In detail, the EVER-EST portfolio service costs account after the project lifecycle will be:
• Focussed on low-cost service concept - Asset cost-base, minimizing all costs and having no frills service - to support the Business Strategy of Market Development28.
• Addressed to new service production in an economy of scope to support the second phase of Business Strategy of Service Development.
CANVAS Business model by Customer segments
Considering the most relevant Customer Segments and the Business Model configuration literature29 in the following pictures are the business model defined by the CANVAS tool.
• Research Organizations - configurations link to Value proposition by means of “Incomparable services & Virtual community” The added-values are provided by the exploitation of proprietary technologies to offer unique and customer addressed portfolio of products and services, combined with a working virtual tool. Through the Value Proposition the EVER-EST communicates “What is the form of distinctions”.
28 See project deliverable D2.8 Plan to Takeover – paragraph 3.5.2 29 See: - Taran, Y., Nielsen, C., Montemari, M., Thomsen, P., & Paolone, F. (2016). Business model configurations: a five-V framework to map out potential innovation routes. European Journal of Innovation Management, 19(4), 492-527. Gassmann, O., Frankenberger, K., & Csik, M. (2014). The business model navigator: 55 models that will revolutionise your business. Pearson UK.
H2020 – EINFRA – 2015 – 1 Page 53 of 75
Figure 11 Value Proposition Business Model to Research Organization
• Both Data Providers & Distributors & European Service Providers configuration link to Value proposition by means of ”collaboration platform added-value” The related added-values are enabled by a set of tools addressed to collaboration and data exploitation, enabled by the mix of the key resources, key activities, portfolio of service provided and the adopted direct channel to the potential customers. Through the Value Proposition the EVER-EST communicates “What is the form of distinctions”. Alternatively: the configuration can link to Profit Model as well. Here, a basic access is offered for free – FREMIUM to users that are willing to pay for additional offering if they desire through the only “PREMIUM service model”
H2020 – EINFRA – 2015 – 1 Page 54 of 75
Figure 12 Value Proposition Business Model to Data Providers & Distributors
Figure 13 Value Proposition Business Model to European Service Providers
• Research Infrastructures - configuration link to Strategic Partnership by ”outside-in approach or adaptive”
H2020 – EINFRA – 2015 – 1 Page 55 of 75
Here, the related added-values are generated by the mix of Partners technologies and creating an ecosystem. Several aspects of CANVAS model are involved: Key Partners - who will engage in different kinds of cooperation; Key Resources; Key Activities; Value Proposition (Service Portfolio – what is offered), and Channels adopted, aim to establish a powerful networking to share end-users. Through the Strategic Partnership the EVER-EST communicates “Who play a central role to develop the form of distinctions”.
Figure 14 Partnership Business Model to Research Infrastructures
These models made it possible to study and define all aspects related to sustainability, both social and environmental that are affected by the Key partner, Activities, Resources which enable the Value Proposition. Whilst Customer Relationship and Channels as enablers to reach the defined customer segments.
The economic sustainability is defined by the leverage of cost model structure and revenues streams and fund. In other words, the three main pillars of sustainability model.
H2020 – EINFRA – 2015 – 1 Page 56 of 75
7 Sustainability roadmap This chapter report the overview about steps and activities performed by the EVER-EST consortium and addressed to project goals in a view of service sustainability after the project lifecycle.
Figure 15 EVER-EST sustainability to takeover roadmap
Approaching sustainability aspects
After the end of the current H2020 project, EVER-EST partners will continue to make available the EVER-EST VRE service, data and Research Object portfolios to stakeholders. Based on the VRE services maturity level, the sustainability model under definition is assessing different scenarios consisting of a combination of:
1. Contributions of resources from EVER-EST Partners (e.g. data, infrastructure and services, research results in the form of Research Objects, innovative technologies, funding).
2. Revenues generated by providing VRE services based on Freemium and pay-per-use business model schema.
3. Research Grants from public institutions (e.g. national research councils) to sponsor specific user communities.
4. R&D Grants and opportunities for digital innovation and infrastructure/services research & development at national and European level.
5. Synergies with other Research e-infrastructure initiatives (e.g. LifeWatch and/or EPOS ERIC Project).
A roadmap to sustainability
The EVER-EST roadmap to sustainability has the primary purpose to facilitate consensus to the implementation of established strategy. The roadmap orchestrating the sequence and aligning activities planned for the implementation EVER-EST goals. Both are important, but it is consensus that drives the most value. Values such as:
• Consensus of direction;
• Facilitate of decisions;
H2020 – EINFRA – 2015 – 1 Page 57 of 75
• Enabling efficient execution and improve the management.
EVER-EST project roadmap was built across the following activities:
1. EVER-EST VRE pre-operation (WP6); 2. Overall Gap Analysis/Impact Assessment (WP3); 3. Sustainability Model Refinement (WP2); 4. Review of KPI (WP1); 5. Roadmap from AS-IS to TO-BE: Identification of short and mid-term opportunities for funding and
evolution and planning.
The roadmap was developed throughout the following steps:
1) Consolidation of EVER-EST vision and mission statement for next phase: see above sections; 2) Analysis of overall impact (WP3); 3) Design of the sustainability model (WP2); 4) Review of impact by the KPIs based on EVER-EST vision.
From sustainability to takeover
In the sustainability model is envisaged also the step over the project lifecycle. The Takeover is the plan to EVER-EST service portfolio promotion and adoption by the customers as paid service. Takeover is the process to allow the consortium partners and coming-in of a new player having the interest and the responsibility in performing operational activities to provide the EVER-EST services to scientific communities. Conceptually it is at same time the hand-over for possession of goods and services and the start-up of the operational activities (i.e. transition to operations and operations).
This plan is fully treated and presented in the D2.8 Plan to Takeover [AD10]. It has taken into consideration the following aspects:
1. Business Risks analysis a. Technology performances b. Governance & Operations management c. Regulatory
2. Business & Marketing Strategies a. Market penetration strategy b. Market development VRCs / SGs /VLs players enlargement c. Service development
3. Promotion strategy a. Key Customers engagement b. Portfolio promotion (Market development strategy) c. Service Brand (Service development strategy
In addition, several future actions can be pursuit to support EVER-EST operations and services portfolio improvement, such as:
• Awareness campaign to potential shareholders, contact with new infrastructure partners, other VRE for interoperability, synergies;
• Assessment of H2020 technology/infrastructure driven calls (e.g. European research infrastructures, including e-infrastructures) work program 2018-2020);
• Assessment of science initiatives in each EU member state (e.g. Ministries / Dept. of Research, Space Agencies, etc)
• Assessment of ESA Open Science and block 4 ITTs; programs such as GSTP (General Support Technology Programme) a network of excellence, technology projects.
H2020 – EINFRA – 2015 – 1 Page 58 of 75
8 Conclusions The EVER-EST project has addressed central aspects of sustainability: the fundamental pillars. The balance of these identified main themes: social, environment and economic is the key to achieve sustainable services for the number users.
The pursued analysis of sustainability reports the flag about the equilibrium among these pillars. It is not a conservatory system while a continuous analysis, challenge and solution to the evolving user demand, is the main way to create and maintain the credibility of the EVER-EST service provider. Sustainability is a highly dynamic process in charge of the service management down to all the processes of delivery and operations in order to have the wider and deeper awareness of relationships and dependencies among the various aspects of sustainability.
Moreover, and as additional tool aimed at helping service governance in decision making a SMM - Service Maturity Model should be considered too. This model provides a mode to measure the methods and processes being used, against a clear set of external benchmarks. Maturity is indicated by the award of a particular "Maturity Level".
Based on the VRE Services Maturity Level approaches, the sustainability model under definition is assessing different scenarios:
• Contributions of resources from EVER-EST Partners (e.g. data, infrastructure and services, research results in the form of Research Objects, innovative technologies, funding)
• Revenues are generated by providing VRE offering based on PREMIUM service model
• Additionally, revenues could come by Sponsorship (Private funding)
• Research Grants from public institutions (e.g. national research councils) to sponsor specific user communities
• R&D Grants and opportunities for digital innovation and infrastructure/services research & development at national and European level.
• Synergies (Partnership) with other Research e-infrastructure initiatives (e.g. LifeWatch and/or EPOS ERIC Project)
However, today the European Open Science situation of the various infrastructures devoted to the different scientific communities is jeopardized. This situation does not help private investors in their selection of investments and neither helps in identification of the best solutions and balance of the various aspects is not an easy job.
Possible solutions to this issue, to increase the service subscription revenues stream could be pursued via a Public-Private Partnership (PPP) hence reducing the level of financial risks while engaging initial commitments on social and environmental aspects. Or, it could be addressed via a kind of operational incubator specific to this service for scientific researchers in order to allow starting of operational activities in a more protected environment and then starting maiden steps of the relevant sustainability plan.
Hence definition of this plan is of fundamental importance in any future development and should outlining where it is expected to be in a defined timeframe and how it is intended to get there. In any case, the initial challenge of sustainability is crucial, and it is of fundamental importance to focus on few pivotal elements defined through the sustainability plan, and strongly avoiding dozens of high priority elements to be addressed. This will help managers in focussing the key elements and being open to all possible and necessary changes in due time.
H2020 – EINFRA – 2015 – 1 Page 59 of 75
A. EVER-EST Stakeholders data collection
A dedicate file: EVER-EST Stakeholders data collection, is provided in excel format as annex A.
B. EVER-EST Sustainability Vision Survey The following survey has been carried out within the project participants. The results of the survey are shown below. Complete survey content is available in the doc: “EVER-EST SUS_VIS-SURV”.
EVER-EST vision in the Earth Science:
The assumption is that (for the present time) we will focus on EVER-EST as a Research service Infrastructure. Nevertheless, some aspects of EVER-EST as a commercial infrastructure could help in designing our identity. The next slide identifies the keywords for both areas as shown and discussed in Reykjavik. Please use the following slides to add your personal idea of EVER-EST.
H2020 – EINFRA – 2015 – 1 Page 60 of 75
A roadmap to sustainability:
Here, the meaning comments on the topics.
1. Mission
• Comments on the Commercial / Business domain: o Create an area to share research o Create an area to test and share method development o Eventually provide space for operational delivery of research results o Establish a reference VRE in support to Earth Science o Foster the publication of high quality, reproducible research outcomes o Promote the adoption of scientific workflows for the formalization and automation of research
methods o Facilitate the collaboration of researchers in Earth Science and other disciplines o Engage potential commercial organizations to identify opportunities for exploiting VRE added-value
services in their value chain o Create a collaborative environment which provides services supporting the sharing of scientific
knowledge o Provide an infrastructure to run EO processing services
H2020 – EINFRA – 2015 – 1 Page 61 of 75
o Allow to transfer technologies from research to an operational scenario o Create an area to preserve, share, get credit, and discover research o Support and facilitate the teamwork of scientists o Reduce the time for re-use and value adding on top of existing researches o Promote the entrance of new generations of scientists o Bridge the gap between science and industry o Facilitate the communication of scientific results toward the public o Support the univocal identification of scientific achievements o Help the definition of National and International policies on science o Create a common, more efficient (fast data access to multiple repository, cloud storage, cloud
processing capabilities) and multidisciplinary working area for EO scientists able to overcome the current limitation of working within closed “silos”
o Create an area to effectively share the entire research lifecycle o Promote a new way of doing science sustainable for the society. o Promote new scientific careers such as data scientists o Create an area to share research across NHP organizations o Allow NHP partners to take a more involved role in the development of new models, including ability to
trial different case study and parameter scenarios o Provide guided and structured access to ROs o Allow publication of model science via ROs
2. Strategy • Comments on the Science domain:
o Extend capability of system to support operational delivery via next H2020 project ▪ Focus on technology
✓ Extend capability to allow development of new methods e.g. use of VMs to incorporate wider activities
✓ Focus on the quality of RO, considering to create a peer review system to give more reliable scientific value to the RO that should become as important as a paper in the carrier of a scientist
✓ Raise the awareness of public decision makers on the need to adopt modern tools for creating, sharing and disseminating scientific results
▪ Focus on users ✓ Extend the user community, update the user requirements, have a support helpdesk,
provide training for the services ✓ Target wider research communities ✓ Build a large user community that use the platform continuously, focusing on creating an
attractive service offer depending on the user needs. ✓ Focus on the Earth Science community at large ✓ Engage and involve publishers ✓ Enlarge the VRCs and engage new users, increase the number of ROs with DOI and Data
RO (the system is not enough mature to be used at this stage). ✓ Ensure the buy-in of VRC partners and their support to promote the concept toward
other Earth Scientists ▪ Focus on services
✓ Leverage on modern marketing methodologies to promote a scientific service (digital storytelling)
✓ Focus on cross-fertilization, enlarging the multidisciplinary case studies. ✓ Focus on sharing use with an extended user community to increase impact beyond UK ✓ Focus on multiple repository data access to ensure multi-disciplinary and effective data
reuse. ✓ Approach Digital Innovation Hubs (DIH) that can leverage EO data/services with EVER-EST
service portfolio ▪ Focus on infrastructure
H2020 – EINFRA – 2015 – 1 Page 62 of 75
✓ Become part of EU infrastructure initiatives, such as HPC-Europe, EGI, EOSC, BDVA, which will allow us to identify and get involved in use case scenarios
✓ Be part of the EOSC initiative and concepts ✓ HPC- Europe, EOSC, BDVA, EGI and identify use case scenarios ✓ Maintaining a reliable, effective and continuous access to the infrastructure, ensuring
long-term interoperability ▪ Focus on data providers
✓ Integrate data providers (e.g. ESA, DLR) as a way to attract potential users of these data to the platform
✓ Create an offer tailored to institutional customers and data providers consisting of dashboards and detailed views regarding their research activity for the former and the use of the datasets for the latter
✓ Engage and involve several (large) data providers ✓ Become a component of one or more European Research Infrastructures, which provide
data services but not collaboration services ✓ Generate a critical mass of high-quality content (research objects)
• Comments on the Commercial / Business domain: o Definition of clear business model (freemium model, advertising, …)
3. Added-values • Comments on the Science domain:
o Re-use of formally tested methods by wider community o Preservation of results for later re-use and auditing o Early publication of results – DOIs attached to ROs – prior to published paper o Reusability, reproducibility, decay monitoring, semantic enrichment, recommendations, citation (DOIs),
research lifecycle, quality assessment o Enrich HPC and cloud services infrastructure (for PSNC organization) o Enhance open, full and easy access to space data through the VRE o Promote easier and rational sharing of scientific results through the RO paradigm o Innovate technologies, processes and communication models through the use of the VRE and the
available computing resources (e.g., VM) o Enhance data sharing and global scientific collaboration through the use of the VRE collaboration
services o Increased use of open data and tools o Easy-to-use (pre-validated) tools for information extraction from multiple sources o Operational use of EO processing chains o Single access point for the whole data chain workflow (from access to the data to results visualization o As preprint archive service (give visibility before publication) o To enhance reproducibility of papers (add data, and code) o To share research products and get credit o In the future to reuse others research o Access to collaborative research and development services o Structured storage of model inputs/outputs/context (via ROs) with DOIs o Online-workflow execution o Reproducible executions o Accessibility to partners who are not domain experts
• No comments on the Commercial / Business domain:
4. Portfolio • Comments on the Science domain:
o Service portfolio should be based on the services/applications, but in terms of ES specific language/wording:
▪ EO data discovery/visualization, e.g., digital information services (data discovery, RO manager, virtual globe, Seafile upload, WPS manager - VRE portal)
H2020 – EINFRA – 2015 – 1 Page 63 of 75
▪ Scientific collaboration, e.g., e-collaboration (forum, instant messaging, messaging, notification, calendar/scheduling - VRE portal)
▪ Research lifecycle management, e.g., e-research (ROHub, RO services (enrichment, recommendation, collaborations spheres, checklist, stability, preservation, publication via DOIs)
▪ E-learning (Jupyter) ▪ Base services, e.g., common services (Identity server, ESB - middleware API, Data Analytics
Server, Personal file storage (Seafile) ▪ Meta-Catalogues of existing EO data are a key service, as well as the catalogue of related
researches (ROHub)
• Comments on the Commercial / Business domain: o From a commercial point of view, EVER-EST could support the discovery of EO-based applications and
their adoption in commercial domains. This is an ongoing process, not always smooth. EVER-EST infrastructure has the potential to facilitate it. Opening to addition EO data, with higher resolution and revisit times should help the process. Additional data sources (Open Data, ground-based observations, aerial/drone data) could further facilitate the process.
5. Approach • Comments on the Science domain:
o Engage VRCs by offering a level of use for free or an extended ‘try’ period o Investigate option for hosting by existing in-country organizations that already host infrastructures. Cost
to these organizations may be minimal and may provide option for ongoing maintenance – could this be a contribution in-kind?
o Continue mass generation of research objects o Identification and engagement of potential publishers to adopt research objects o Hackathons o Provide and advertise API for development of external services/apps o Provide comprehensive hands on training sessions to targeted users o Showcasing EVER-EST capability at conferences, but with the goal of attracting scientists to in depth
training sessions o Propose the use of Research Objects to Scientific publishers, starting with academic ones and Open
Access journals o Increase the number of workflows which can be run from ROs o Archive of publications, scientific articles and materials of conferences and conferences o Engage VRCs in a Try & Buy (if this is a commercial solution I would move it to the next column) o Archive of publications, scientific articles and materials of conferences and conferences o Open publication of success cases and free sharing and access to sample data/ROs/resources. o Reaching a critical mass of researches (ROs) referenced in EVER-EST
o Give free access for a trial period to new VRCs
o Archive as much as possible scientific material that is currently available in theory but impossible to
search for (ESA conferences’ material is an excellent example)
• Comments on the Commercial / Business domain: o Define the value of science (social, industrial, economic) -> quantify
o Leverage on initiatives and cultural/political threads that can support the adoption and growth of EVER-
EST -> Knowledge Economy needs tools
o Identify possible partnerships to support the lobbying of the concept.-
o Library of EVER-EST success stories/case studies on website, and in print to distribute at
conferences/events
o EVER-EST story in relevant trade articles
o EVER-EST consultancy service? Assistance for potential new users (e.g. advice on EVER-EST/workflow
approaches, different types of RO etc.)
o Examples of executable papers (/Jupyter) linked to EVER-EST
6. Goals • Comments on the Science domain:
H2020 – EINFRA – 2015 – 1 Page 64 of 75
o Achieve longer term use by existing VRCs o Become VRE for earth science communities o Remain focused on what the VRE is good at – do not diversity too much and lose focus o Gather a significant number of scientists in Earth Science, increasing drastically the user base both
vertically (from the EVER-EST VRCs) and horizontally (from new VRCs) o Significant increase in the number of research objects o Standardization of research objects model and approach o Indexing of research objects in google and google scholars o Promote citation of research objects o Include the VRE in the scientific tools provided for ES by EU, e.g., EGI o Expand visibility of EVEREST beyond Europe o Be maintained fully operational for at least one year after the end of the project o Become a component of the EPOS RI o Create a loyal audience/public (% of promotors) o Become a standard de facto o Reach the level (technology matureness, service provision reliability, service quality and offering) of the
current market solutions offering similar services and/or capabilities o Promote the adoption of EVER-EST solutions as standards (de facto but also de jure) -> ROs first of all o Push for its dissemination in other communities, starting from the closest ones (astronomers,
climatologists) o Be the primary access point for workflow ROs (& Taverna workflow online execution long-term) o Link to other solutions – demonstrate how EVER-EST complements them (e.g. it would be great if
people could think of EVER-EST when they’re looking into machine-readable
• Comments on the Commercial / Business domain: o Definition of commercial policies o Definition of agreements and identification of roles for the commercial phase within the consortium o Evaluation of entrance of new supporting actors o Extension to other data providers, both commercial ones and scientific ones
7. Sustainability
• Comments on the Science domain: o VRCs subscriptions (make or buy) – highly unlikely for NHP partner organizations. o Possible participation in co-funded project with aim of introducing home organization to value of VRE.
Co-funding from UK research council o Co-funded project with new communities via overseas funding options GCRF/ODA This could a longer
term option but likely success unknown o Establish EVER-EST foundation/organisation o H2020 funds:
▪ Coordination and support actions to consolidate VRE ▪ Business development funds to develop further commercial strategy ▪ R&D projects to extend/scale VRE ▪ Collaboration programs with USA, Australia, Japan ▪ Data providers funding
o In the mid- to long-term funding might be sought in the framework of Research infrastructures (e.g. EPOS, etc.)
o Participation in other Projects which might make use of the platform o EU funds (different calls/instruments are applicable due to the cross-cutting nature of the concept)
o National and Regional funds
o Collaboration with other complementary work (e.g. other VRE’s component services)
• Comments on the Commercial / Business domain: o In the short term commercial sustainability will be mostly based on scientists (see left-hand column) o During phase 2 (medium term) we will develop a wider perspective for commercial sustainability,
analyzing the evolution of Knowledge Economy and the position of the relevant key players o Shared research with industry partners
H2020 – EINFRA – 2015 – 1 Page 65 of 75
What partners are looking for and ask for future? SatCen
• Fostered the use of open data and tools
• Simplified procedures for information extraction
• Automatized EO processing chains
• Created an environment able to deal with whole data chain
PSNC
• Reusability, reproducibility, decay monitoring, semantic enrichment, recommendations, citation (DOIs), research lifecycle, quality assessment
• Enrich HPC and cloud services infrastructure (for PSNC organisation)
BGS
• Re-use of formally tested methods by wider community
• Sharing of methods and results across the community
• Preservation of results for later re-use and auditing
HSL
• The need to communicate with other partners
• The need to develop models
INGV
• Need to manage large variety of data catalogues
• Have strong collaboration requirements
• Need to manage fast turnover of algorithms
• Need of single cartographic interface
• Need for community management tools
• Need for dissemination capabilities to the public/stakeholders
ESI
• More and more conference and journal reviewers increase their requirements regarding science reproducibility: therefore, ROs are the proper artefacts to attach to traditional academic publications.
ACS
• Comment from a non-scientific partner: the EVER-EST infrastructure appears as an instrument integrating a wide set of services in support to science (creation of experiments, execution, archive, sharing, search, publication, DOI management, preservation. E-learning). The richness of this bouquet and the direct involvement of scientists in its creation makes EVER-EST a unique tool.
CNR
• A Have a common environment (lab) to work with multi-disciplinary “big data”, ensuring a high level of cooperation not only between scientists but also with other institution (such as environmental agencies).
• Share the data and the methods (executable workflow) forcing the scientists to unsure reproducibility of its work.
• Preserve
C. EVER-EST Value Proposition Survey
H2020 – EINFRA – 2015 – 1 Page 66 of 75
H2020 – EINFRA – 2015 – 1 Page 67 of 75
H2020 – EINFRA – 2015 – 1 Page 68 of 75
H2020 – EINFRA – 2015 – 1 Page 69 of 75
H2020 – EINFRA – 2015 – 1 Page 70 of 75
H2020 – EINFRA – 2015 – 1 Page 71 of 75
D. Bibliography
[1] GRL2020 (Global Research Libraries 2020) A vision for global research data infrastructures http://www.grdi2020.eu/
[2] Research Software Sustainability, http://www.knowledge-exchange.info/event/software-sustainability
[3] Report on the Consultation on Long Term Sustainability of Research Infrastructures https://ec.europa.eu/research/infrastructures/pdf/lts_research_infrastructures_workshop_agenda.pdf
[4] The business of sustainability: McKinsey Global Survey results, http://www.mckinsey.com/business-functions/sustainability-and-resource-productivity/our-insights/the-business-of-sustainability-mckinsey-global-survey-results
[5] A Guide to Takeovers: Theory, Evidence and Regulation, Roberta Romano, Yale Law School http://digitalcommons.law.yale.edu/cgi/viewcontent.cgi?article=2991&context=fss_papers
[6] Cost Benefit Analysis of Research Infrastructures: a conceptual framework and main issues at stake http://www.eiburs.unimi.it/Downloads/Deliverabes/Paper%20outlines/CBA%20of%20research%20infrastructure_a%20conceptual%20framework.pdf
[7] Transforming our world: the 2030 Agenda for Sustainable Development, UN Resolution 70/1, 21 October 2015
http://www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E
[8] The Future We Want, Outcome document of the RIO+20 Conference UN Resolution 66/288, 27 July 2012
http://www.un.org/ga/search/view_doc.asp?symbol=A/RES/66/288&Lang=E
[9] Mainstreaming of the three dimensions of sustainable development throughout the United Nations system, A/71/76–E/2016/55, ECOSOC 71st session, 29 March 2016
http://www.un.org/ga/search/view_doc.asp?symbol=A/71/76&Lang=E
[10] Tier Classification for Global SDG Indicators, as of 20 April 2017
https://unstats.un.org/sdgs/files/Tier%20Classification%20of%20SDG%20Indicators_20%20April%202017_web.pdf
[11] Work Plans for Tier III indicators, 48th Session of the UN Statistical Commission (UNSC-48), as for 3 March 2017
https://unstats.un.org/sdgs/files/meetings/iaeg-sdgs-meeting-05/TierIII_Work_Plans_03_03_2017.pdf
[12] GEO/CEOS joint report on “Earth Observations in support of the 2030 Agenda for Sustainable Development”
https://www.earthobservations.org/documents/publications/201703_geo_eo_for_2030_agenda.pdf
[13] A World That Counts: Mobilising the Data Revolution for Sustainable Development
http://www.undatarevolution.org/report/
[14] Harnessing platform-based business model to power disruptive innovation article https://www.emeraldinsight.com/doi/pdfplus/10.1108/SL-07-2016-0061#
[15] Business Model Generation, A. Osterwalder, Yves Pigneur, Alan Smith, and 470 practitioners from 45 countries, self published, 2010
https://profesores.virtual.uniandes.edu.co/~isis1404/dokuwiki/lib/exe/fetch.php?media=bibliografia:9_business_model_generation.pdf
[16] Neielsen C., & Lund M. 2018 Building Scalable Business Models. MIT Sloan Management Review 59(2), 65-69 2018
[17] Gassman O. Frankenberger K. & Csik M. The business model navigator: 55 models that will revolutionise your business. Pearson UK 2014
H2020 – EINFRA – 2015 – 1 Page 72 of 75
[18] Tara Y. Nielsen C. Montemari M. Thomsen P. & Paolone F. Business model configurations: a five-V framework to map out potential innovation routes. European Journal of Innovation Management 19(2), 492-527 2016.
[19] Cape Town Global Action Plan for Sustainable Development Data
https://unstats.un.org/sdgs/hlg/Cape-Town-Global-Action-Plan/
[20] The Sustainable Development Goals Report 2016
https://unstats.un.org/sdgs/report/2016/The Sustainable Development Goals Report2016.pdf
[21] GEO Engagement Strategy, GEO-XIII Plenary, November 2016
https://www.earthobservations.org/documents/geo_xiii/GEO-XIII-4-1_GEOEngagement Strategy.pdf
[22] GEO Engagement Priorities for 2017-2019, November 2016
http://www.earthobservations.org/documents/excom/ec38/ExCom38_08(Rev1)_GEOEngagement Priorities for 2017-2019.pdf
[23] GEO EO4sDG initiative (formerly known as GI18): 2016-2020 Strategic Implementation Plan
http://www.earthobservations.org/documents/pb/me_201701/pb07_201701_4th_pb_gi_sdg_implementation_plan.pdf
[24] CEOS Earth Observations Handbook on satellite Earth Observations in support of Climate Information Challenges, Special 2015 edition for the UNFCCC COP21
http://eohandbook.com/cop21/
[25] CEOS Earth Observations Handbook on satellite Earth Observations in support of Disaster Risk Reduction,
Special 2015 edition for the 3rd UN World Conference on Disaster Risk Reduction (WCDRR)
http://www.eohandbook.com/eohb2015/
[26] ESA activities supporting Sustainable Development, Catalogue 2016
http://esamultimedia.esa.int/docs/spaceforearth/SD_Catalogue_COMPLETE_161128.pdf
[27] Earth Observation for Green Growth, an overview of European and Canadian Industrial
Capacity, 2013
http://esamultimedia.esa.int/multimedia/publications/EO_for_green_growth_complete/
[28] Earth Observation for Sustainable Development, ESA-World Bank Partnership Report,
September 2016
http://esamultimedia.esa.int/multimedia/publications/ESA_WB_Partnership_Report_2016/
[29] Earth Observation for a transforming Asia and Pacific, a portfolio of twelve EO projects supporting Asian Development Bank activities, 2017
http://esamultimedia.esa.int/multimedia/publications/EOTAP/
[30] Progress towards the Sustainable Development Goals Report of the Secretary-General 2017 session of the High-Level Political Forum (HLPF) on sustainable development,
E/2017/66, 11 May 2017
http://www.un.org/ga/search/view_doc.asp?symbol=E/2017/66&Lang=E
[31] Greg Scott & Abbas Rajabifard (2017): Sustainable development and geospatial information: a strategic framework for integrating a global policy agenda into national geospatial capabilities, Geo-spatial Information Science, DOI:10.1080/10095020.2017.1325594
http://www.tandfonline.com/doi/full/10.1080/10095020.2017.1325594
[32] Katherine Anderson, Barbara Ryan, William Sonntag, Argyro Kavvada & Lawrence Friedl (2017): Earth observation in service of the 2030 Agenda for Sustainable Development, Geo-spatial Information Science, DOI: 10.1080/10095020.2017.1333230
H2020 – EINFRA – 2015 – 1 Page 73 of 75
http://www.tandfonline.com/doi/pdf/10.1080/10095020.2017.1333230
[33] Report of the Global Working Group on Big Data for Official Statistics to the 48th session of the UN Statistical Commission, March 2017
https://unstats.un.org/unsd/statcom/48th-session/documents/2017-7-BigData-E.pdf
[34] Global Platform for Data, Services and Applications, 48th session of the UN Statistical Commission, March 2017
https://unstats.un.org/unsd/statcom/48th-session/documents/BG-3d-global-platformfor-
data-services-applications-E.pdf
[35] UN Decade of Education for Sustainable Development – DESD http://unesdoc.unesco.org/images/0014/001416/141629e.pdf
[36] ISO 26000:2010 Guidance on social responsibility https://www.iso.org/standard/42546.html
[37] ISO 37101:2016 Sustainable development in communities -- Management system for sustainable development -- Requirements with guidance for use https://www.iso.org/standard/61885.html
[38] ISO 14000 family - Environmental management https://www.iso.org/iso-14001-environmental-management.html
[39] GRI G4 Guidelines https://www.globalreporting.org/resourcelibrary/GRIG4-Part1-Reporting-Principles-and-Standard-Disclosures.pdf
E. Websites [URL-1] EU Open Science
https://ec.europa.eu/research/openscience/index.cfm?pg=home
[URL-2] The UN Sustainable Development Knowledge Platform
https://sustainabledevelopment.un.org
[URL-3] Sustainable Development Goal (SDGs) Indicators Portal
https://unstats.un.org/sdgs/
[URL-4] SDG Indicators Metadata Repository
https://unstats.un.org/sdgs/metadata/
[URL-5] UN Statistical Commission
https://unstats.un.org/unsd/statcom/
[URL-6] 48th session of the United Nations Statistical Commission (UNSC-48), 7-10 March 2017,
New York, US
https://unstats.un.org/unsd/statcom/48th-session/
[URL-7] Inter-Agency Expert Group on SDG Indicators (IAEG-SDGs)
https://unstats.un.org/sdgs/iaeg-sdgs/
[URL-8] 5th Meeting of the Inter-Agency Expert Group on SDG Indicators, 28-31 March 2017,
Ottawa, Canada
https://unstats.un.org/sdgs/meetings/iaeg-sdgs-meeting-05/
[URL-9] United Nations Committee of Experts on Global Geospatial Management (UN-GGIM)
http://ggim.un.org/
[URL-10] 2nd Expert Group Meeting of the IAEG-SDG Working Group on Geospatial Information,
12-14 December 2016, Mexico
H2020 – EINFRA – 2015 – 1 Page 74 of 75
http://ggim.un.org/1st_EGM_Mtg_WG_Geospatial_Information.html
[URL-11] 3rd Expert Group Meeting of the IAEG-SDG Working Group on Geospatial Information,
8-10 May 2017, Kunming, Yunnan, China
http://ggim.un.org/2nd_Mtg_IAEG%20SDG_Kunming.html
[URL-12] The Group on Earth Observations (GEO)
https://www.earthobservations.org/
[URL-13] The Committee on Earth Observation Satellites (CEOS)
http://ceos.org/
[URL-14] CEOS Ad-Hoc Team on Sustainable Development Goals (AHT-SDG)
http://ceos.org/ourwork/ad-hoc-teams/sustainable-development-goals/
[URL-15] CEOS Data Cube Platform
https://software.nasa.gov/featuredsoftware/ceos2
[URL-16] ESA activities on Sustainable Development and Migration
http://www.esa.int/Our_Activities/Preparing_for_the_Future/Space_for_Earth/Space
_for_Sustainable_Development/For_a_sustainable_future
[URL-17] WGGI report at the 5th meeting of the IAEG-SDGs
https://unstats.un.org/sdgs/files/meetings/iaeg-sdgs-meeting-05/4b.Geo-
Spatial%20Working%20Group%20Presentation_plenary.pdf
[URL-18] Earth System Data Cube (ESDC)
http://earthsystemdatacube.net
[URL-19] Copernicus Data and Information Access Service (DIAS)
http://www.copernicus.eu/news/upcoming-copernicus-data-and-information-accessservices-
dias
[URL-20] Global Working Group (GWG) on Big Data for Official Statistics
https://unstats.un.org/bigdata/
[URL-21] Global Working Group (GWG) on Big Data for Official Statistics, Task Team on Satellite
Imagery and Geo-Spatial Data
https://unstats.un.org/bigdata/taskteams/satellite/
[URL-22] UN Data Revolution
http://www.undatarevolution.org/
[URL-23] Australian Geoscience Data Cube
http://www.datacube.org.au
[URL-24] Earth Observation Data Cube (Earth Observation Data Service)
http://eodatacube.eu
[URL-25] Earth Server
http://www.earthserver.eu/
[URL-26] NEXTGEOSS
https://nextgeoss.eu/
[URL-26] LifeWatch project
https://www.lifewatch.eu/
H2020 – EINFRA – 2015 – 1 Page 75 of 75
[URL-27] BlueBRIDGE VRE
https://www.bluebridge-vres.eu/
[URL-28] European Marine Observation and Data Network
http://www.emodnet.eu/