data management plans based on digital workflow models: a report on a dmp project within the frame...
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Data Management Plans based on digital workflow models:
A report on a DMP project within the frame of e-Infrastructures Austria
Paolo Budroni, Barbara Sánchez Solís
University of Vienna
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WORLDS OF DATA :
ABOUT RESEARCH DATA
ABOUT DATA
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The LERU Roadmap for Research Data presents the following sets this context (*) :
“Research data, from the point of view of the institution with a responsibility for managing the data, includes:
•All data which is created by researchers in the course of their work, and for which the institution has a curational responsibility for at least as long as the code and relevant archives/ record keeping acts require, and
•third-party data which have originated within the institution or come from elsewhere.”
(*) LERU Research Data Workingg Group, Advice Paper No. 14 – December 2014
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The Australian Griffith University presents the following definition (*) :
“Research data are factual records, which may take the form of numbers, symbols, text, images or sounds, which are used as primary sources for research, which are commonly accepted in the research community as necessary to validate research findings.”
(*) Ingrid Dillo – Data Archiving and Networked Services (DANS), Certification as a means of providing trust, Florence, Fondazione Rinascimento Digitale, 2012
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The University of Minnesota about research data (*):
Research data are data in any format or medium that relate to or support research, scholarship, or artistic activity. They can be classified as: • Raw or primary data: information recorded as notes, images, video footage, paper surveys, computer files, etc.• Processed data: analyses, descriptions, and conclusions prepared as reports or papers• Published data: information distributed to people beyond those involved in data acquisition and administration
According to this logic we identify:
Different levels (or “layers”) of processing dataThis has an impact on the digital workflow model
(*) Ingrid Dillo – Data Archiving and Networked Services (DANS), Certification as a means of providing trust, Florence , Fondazione Rinascimento Digitale, 2012
World of data Raw data (primary data) World of data Raw data (primary data)
Processed Data Negative Results Processed Data Negative Results
Processed DataProcessed Data
Processed Data Inconclusive Results
Processed Data Inconclusive Results
Processed DataProcessed Data
Processed DataProcessed DataShared
DataShared
Data
Processed DataProcessed Data
Positive resultsPositive results
Positive resultsPositive results
Shared Data
Shared Data
Shared Data
Shared Data
Pub. DataPub. Data
OA
Pub. DataPub. DataReleased
DataReleased
Data
Different levels of processing of dataModel for digital archiving
Ensuring legal and ethical compliance is key issue in this context
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Levels / layers in processing of data
Raw data, primary data
Processed Data (positive, negative and inconclusive results)
Shared Data and Published Data
Open Access Published Data
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Open Data Shared Data and Reused Data
Published Data
Restricted Data
Strata of research data
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THE DIGITAL WORKFLOW
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WORKFLOW MODEL
SEGMENTS
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Digital workflow model
Preingest Ingest Rep-Management Re-Use
archives
Ensuring legal and ethical compliance is key issue in this context
Metadata
File
License
Persistent Identifier
#
ExternalSystems
All types of data
Processes
DA
TA
PR
OV
IDE
RS
DMP – along all processes
Ontology of ObjectsDifferent Types
COMMON LEGAL SPACE
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SETUP OF A REFERENCE
ARCHITECTURE
FOR RESEARCH DATA MANAGEMENT
ROLE MODELS
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FOUR MAIN ACTORS INVOLVED IN THE MGMT OF RESEARCH DATA
THE STAKEHOLDERS
Research LibrariesIT-Services
Researchers Funders / Funding Services
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FOUR MAIN ACTORS ARE INVOLVED IN THE MGMT OF RESEARCH DATA
FOUR STAKEHOLDERS
Research Libraries IT-Services
Researchers Funders / Funding services
Data Management Plans
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Different views – different roles, responsibilities, competencies
ARCHIVE SAFEGUARDING
CONTENT SUPPLIER
FUNDING BODY
QUALITY
SOCIAL RESPONSIBILITY
ROLE RESPONSIBILITY
INSTITUTION LEGAL SECURITY
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PUBLISHER ? SAFEGUARDING ?
ARCHIVE SAFEGUARDING
CONTENT SUPPLIER
FUNDING BODY
QUALITY
SOCIAL RESPONSIBILITY
ROLE RESPONSIBILITY
INSTITUTION LEGAL SECURITY
Different views – different roles, responsibilities, competencies
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DMP PILOT
ON A NATIONAL LEVEL
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Premises
• Univ. of Vienna: Document on the creation of DMPs Reasons for DMPs Consideration of different project stages (processes) Forms of DMPs Checklist
• 5 workshops in different partner institutions Target groups: librarians, IT, research support
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DMP pilot on national level
• DMP focussed on Horizon 2020
• Based on DCC checklist for a Data Management Plan, v4.0
• Customised to actual institution
• Goal: Align DMP with existing local infrastructures and services
• Procedure Run pilot with 7 different faculties at University of Vienna Optimisation according to feedback Extend pilot to other institutions in Austria
• 5 workshops in different partner institutions Target groups: librarians, IT, research support
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Characteristics
• Execution on a national level (20 Austrian universities)
• Support of dialogue with different scientific communities
• Common approach may lead to Development of national services in non-technical areas Pooling of competencies at a national level Development of systems apart from DMPonline
• Administration of data stays with institutions• Frame/design of DMP can be changed (e.g. inclusion of
text modules, drop down menus etc.)• Extraction of data can be optimised
• DMP requires constant adaptation and adjustment
• Archiving strategies involve more parties than originally assumed (planning of resources)
• Business re-engineering in research support services: Data security management, storage, metadata modelling,
ethical and legal issues
• New job profiles: data scientists, data librarian
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First Conclusions
• Extension of language area
• DMP requires constant adaptation and adjustment
• Archiving strategies involve more parties than originally assumed (planning of resources)
• Business re-engineering in research support services Data security management, storage, metadata modelling,
ethical and legal issues
• New job profiles: data scientists, data librarian
• Further support services required
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Challenges
• Who is the owner of DMPs?
• Who administrates DMPs?
• Who reviews DMPs (institutional/national/European level?)
• What about projects beyond H2020?
• What about existing projects and the preservation of the data?
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University of Vienna
Library and Archive ServicesPaolo Budroni, [email protected]
Barbara Sánchez Solís, [email protected]
Computer CentreRaman Ganguly, [email protected]
José Luis Preza, [email protected]
[email protected] www.e-infrastructures.at
e-Infrastructures Austria
Thanks!