BDE SC2 Workshop 3: e-ROSA: infrastructures and stakeholders

WWW.EROSA.AGINFRA.EU
e-ROSA has received funding from the European
Union’s Horizon 2020 research and innovation
programme under grant agreement No 730988
eRosa
Infrastructures and Stakeholders
Brussels, March 31 2017
Odile Hologne, Johannes Keizer
eRosa, Project Coordination

Theproject

Horizon 2020 research and innovation programme - grant agreement No 730988
eROSA in brief
Coordination and support action (infrasupp 3
2016)
18 months
started january 2017
Consortium : INRA (FR), WUR Alterra (NL),
Agroknow (GR)
Main goals: creating community and
roadmaps
 Support small-size foresight roadmaps for research and education communities and
operators of e-infrastructure services.
 Identification of potential collaboration from stakeholders across different geographic
areas and scientific domains.

The need for a roadmap
A puzzle of different component
Need to build a shared vision
Need of a community of practice
No real research infrastructure in agri-food
(ESFRI in environment, genomics, earth
observation …)

Objectives
Community building : researchers, education
and practitioners ; international ; agricultural
sciences
Improve the knowledge of the landscape :
infra/e-infra, projects, policies … relevant for
an « e-infra for open science in agriculture »
Roadmap : vision, conception,
implementation roadmaps,advocacy

Methodology, Work packages

Definition of eInfrastructures
Presentation Title 7

a combination of digital technologies (hardware and
software), resources (data, services, digital libraries),
communications (protocols, access rights and networks), and
the people and organisational structures
They are keys in future development of research
infrastructures, as activities go increasingly "online" and produce
vast amounts of data and are at the heart of the Digital Agenda of the
European Commission to support Open Science and the link between
researchers, citizens or private companies
They are becoming a part of the research
infrastructure
EC description of «e-Infrastructure»

WWW.EROSA.AGINFRA.EUPresentation Title 9
Synthesis Paper on eInfrastructure
definitions
https://docs.google.com/docu
ment/d/1MYZhRAelcdTu59
YjE-
5ZTkgQzfDuihIULBTNw-
FaMgo/edit#

It is based on and useful for a Community
It needs a business model and governance
for sustainability
A technical backbone that easily can host a
variety of services
a variety of services, useful for the
community, interoperable, but not
necessarily connected or dependent from
each other
Infrastructure has various components

stakeholders

RDA: Research
Data Alliance
Data Ecosystem for Agriculture and Food
12
EOSC
EDI
Stake-
holders
Citizens /
Communities
Farmers Associations
Networks
NGOs, etc
Public Sector
Food Agencies
Ministries
EU DGs, etc
Scientific Users
Universities
Research Centres, etc
Industry
Bayer
Syngenta, etc
IoF2
020
Data
Bio
GACS

Stock taking

Topic Clusters
big data
sensors
semantics
modeling
knowledge transfer
information systems
decision support
WebOfScience
2005-201
TS=("information technolog*" or "information management" or “meta-information” or “e-infra*” or "big
data" or “linked data” or “data linkage” or “web data” or “data reliability” or “data infrastructure*” or
“data cyberinfrastructure*” or “data harmonization” or “data warehouse$” or “data management” or
“data model?ing” or “data intensive computing” or “distributed computing” or “high performance
computing” or “digital data” or “research data” or "open data" or “data lake“ or “public dataset*” or “web
collaborative” or “web based system*” or "open science" or "IoT" or "Internet of things" or “Internet
technol*” or “Cloud based” or "sensor-based system*" or RDF or RDFs or OWL or XML or SPARQL or
Hadoop or MapReduce or Spark or NoSQL or “MIEL system” or “conceptual graph*” or “semantic*” or
“ontolog*” or NLP or “natural language process*” or “vocabular*” or “term alignment” or “term
extraction” or “term recognition” or “terminological resource*” or “real-time analysis” or “knowledge
engineering” or “knowledge retrieval” or “knowledge base*” or “knowledge representation” or
((knowledge or “graph-based”) near/3 reasoning) or “distributed graph*” or “learning agent*” or “e-
learning” or “machine learning” or “algorithm learning” or “agricultural model?ing” or “agricultural
database*” OR “digital sensor*”) and TS=(“agricultur*” or “agronom*” or “agrifood” or
“agro?environmental” or “cultural system*” or “crop system*” or “supply chain*” or “farming” or “farm$”
OR cattle OR livestock) OR TS=((“agricultur*” or “agronom*” or “agrifood” or “agro?environmental” or
“cultural system*” or “crop system*” or “supply chain*” or “farming” or “farm$” OR cattle OR livestock)
near/3 (“information system$” ))5
6409 publications for
analysis
Bibliometric Study

The most active institutions

Links between institutions and categries

Data repositories, Organizations,
facilities
http://www.aginfra.eu/discover

Mapping data repositories and facilities

https://goo.gl/O3Fk4R

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