edison’datascience’champions’ conferencejuly2016...
TRANSCRIPT
EDISON Data Science Champions conference July 2016, Brockenhurst, UK
Welcome and introducEon
1. Welcome 2. First Champions Conference 3. Overview of EDISON 4. Background to EDISON 5. Aims and objecEves for conference 6. IntroducEons 7. Programme and surroundings
Welcome Welcome to Brockenhurst in the heart of the New Forest We are here to help you achieve your goals: • CerEfying and accrediEng • Teaching & training • RecruiEng • Delivering • Be bigger, beWer, • Stronger, faster
1st Champions Conference • Bringing together pioneer Champions • Talking to potenEal Champions • Refining the message to UniversiEes • How can Champion use the EDISON
outputs? • How can we support the creaEon and
evoluEon of Data Science Courses? • How can EDISON support and promote
Data Science courses? • How can Champions contribute to and
support EDISON? The New Forest © mr.southampton (Crea5ve Commons, A9ribu5on 2.0 Generic)
The Data Science supply chain
Industry
Research OrganisaEons
Research Infrastructures
Public AdministraEon
DS Employers -‐ DEMAND -‐
UniversiEes
Other Training Centres
In-‐house training centres
Self-‐made DS channels
Data Scien5st “Producers” -‐ SUPPLY-‐
“CompeEEve product”: Skilled DS
Poten5al Data Scien5sts
EDISON acEons and impact
Drama5cally increase the number of data scien5sts
Create a Data Science profession
Support for accreditaEon and cerEficaEon
Engage stakeholder communiEes
Service for collaboraEng and sharing experEse and materials
Design model curricula
Sustain pla_orms of communiEes of pracEce
Organise “champion” universiEes
Interact with Expert Liaison Groups
“Competence Framework” and “Body of Knowledge”
Services to educaEon and
training Data Science professional
profiles
Interact with demand and supply sides
Career path building and skills transferability
IMPACT
ACTIONS
Create a Data Science profession
Services to educaEon and
training
Engage stakeholder communiEes
ACTIONS
ACTORS
UniversiEes And Schools
Employers and their
AssociaEons
Governmental authoriEes
Visionaries and Drivers: Seminal works, High level reports, IniEaEves
The Fourth Paradigm: Data-‐Intensive ScienEfic Discovery. By Jim Gray, Microsod, 2009. Edited by Tony Hey, et al. hWp://research.microsod.com/en-‐us/collaboraEon/fourthparadigm/
Riding the wave: How Europe can gain from the rising Ede of scienEfic data. Final report of the High Level Expert Group on ScienEfic Data. October 2010. hWp://cordis.europa.eu/fp7/ict/e-‐infrastructure/docs/hlg-‐sdi-‐report.pdf
The Data Harvest: How sharing research data can yield knowledge, jobs and growth. An RDA Europe Report. December 2014 hWps://rd-‐alliance.org/data-‐harvest-‐report-‐sharing-‐data-‐knowledge-‐jobs-‐and-‐growth.html
hWps://www.rd-‐alliance.org/
NIST Big Data Working Group (NBD-‐WG) hWps://www.rd-‐alliance.org/ (since 2013)
ISO/IEC JTC1 Big Data Study Group (SGBD) hWp://jtc1bigdatasg.nist.gov/home.php (2014)
The Fourth Paradigm of ScienEfic Research
1. Theory and logical reasoning 2. ObservaEon or Experiment
– E.g. Newton observed apples falling to design his theory of mechanics
– But Gallileo Galilei made experiments with falling objects from the Pisa leaning tower
3. SimulaEon of theory or hypothesized model – Digital simulaEon can prove theory or model
4. Data-‐driven ScienEfic Discovery (aka Data Science) – More data beat hypnoEzed theory
KU KDM'16 Big Data and Data Science 10
EDISON: From Idea to Community IniEaEve to H2020 Project
• 1st RDA Plenary meeEng – 18-‐20 March 2013 – 1st BoF on EducaEon and Skills Development in Data Intensive Science – AWended by 16 representaEves from universiEes, libraries, e-‐Science, data centers,
research coordinaEon bodies
• 3rd RDA Plenary meeEng – 26-‐28 March 2014, Dublin – 3rd BoF on EducaEon and Skills Development in Data Intensive Science – EDISON (Educa-on for Data Intensive Science to Open New science fron-ers) Ini-a-ve
announced
• 4th RDA Plenary meeEng – 22-‐24 September 2014, Amsterdam – IG EducaEon and Training on Handling of Research Data (ETHRD) established – EDISON Workshop – 21 Sept 2014, Science Park Amsterdam – Decision to form a consorEum and submit a proposal to IINFRASUPP-‐4-‐2015 call
How did it start?
“Our vision is a scienEfic e-‐Infrastructure that supports seamless access, use, re-‐use and trust of data. In a sense, the physical and technical infrastructure becomes
invisible and the data themselves become the infrastructure.”
Vision 2030
Background to EDISON: Riding the Wave
Data are becoming infrastructure themselves (Report “Riding the Wave”) • This requires large infrastructure resources to collect, store, process and
archive heterogeneous mulE-‐faceted and linked data.
• Data centric/data driven infrastructure has to support different types of data, including text data, structured and unstructured data, relaEonal and vector data, linked data.
• Data appear in various contexts: large number strings from experiments or sensors, in sodware code, music, films, publicaEons, digital art, web pages, social media, public and business staEsEcs, and also orphan data.
• We need data scienEsts with the knowledge and skill to work with exisEng and future data intensive infrastructure and tools.
Background to EDISON: Riding the Wave
DisseminaEon and Engagement
• Expert Liaison Groups, Champions and the EDISON Network
• The roadmap has come to life: many achievements and plans
• Now we want to sow the seeds for many future successes
• Now we want to culEvate these seeds to grow and flourish
• We want to nurture a forest that can be seen from space
Credits: ONERA