Presentation at the Weaving the Internet of Data Conference in Amsterdam

1. Unless otherwise noted, the slides in this presentation are licensed by Mark A. Parsons under a Creative Commons Attribution-Share Alike 3.0 License
Stories of “Glocality"—Nations in a Global
Infrastructure
Mark A. Parsons
0000-0002-7723-0950
Secretary General
Weaving The Internet Of Data
Amsterdam, The Netherlands
6 April 2016

2. research infrastructure vs. e-infrastructure

3. research infrastructure vs. e-infrastructure
a false dichotomy

4. e-Infrastructure is research infrastructure.
Modern research infrastructure is (or at least
requires) e-Infrastructure.
It’s about the data

5. Infrastructure is hard to conceive and describe
because when it works, it’s transparent,
ubiquitous, and embedded in our daily work.

6. Research Data Alliance
Vision
Researchers and innovators openly share data across
technologies, disciplines, and countries to address the
grand challenges of society.
Mission
RDA builds the social and technical bridges that enable
open sharing of data.

7. Glocality—Bridging across scales
Glocalization “means the simultaneity—the co-presence—
of both universalizing and and particularizing tendencies.”
— Roland Robertson
Glocalism is playing at multiple scales at once.

8. rd-alliance.org
South America
1%
North America
34%
Europe
49%
Australasia
4%
Asia
9%
Africa
3%
Organizational Type
Members
(Feb 2016)
Press & Media 22
Policy/Funding Agency 58
Large Enterprise 85
IT Consultancy/Development 119
Small and Medium Enterprise 212
Other 198
Government/Public Services 583
Academia/Research 2447
TOTAL 3724
The RDA Community:
3700+ members from 110 countries
(February 2016)
May - July Aug - Oct Nov - Jan Feb - Apr May - July Aug - Oct Nov - Jan Feb -Apr May - July Aug -Oct Nov - Jan Feb- Apr
392
991
1274
1656
2048
2404
2636
2881
3126
3434
3698 3724
65+ Working and Interest Groups

9. RDA
Organisational
Members
RDA Affiliate
Members
https://rd-alliance.org/organisation/rda-organisation-affiliate-members.html
RDA Organisational & Affiliate
members
Represent the interests of RDA’s organisational members and ensure that their
input and needs play a role in guiding the programs and activities of the RDA.

10. Fran Berman, Research Data Alliance
“Create - Adopt - Use”
(in 12-18 months)
Systems
Interoperability
Adopted Policy
Sustainable Economics
Common Types,
Standards, Metadata
Traffic Image:
Mike Gonzalez
Adopted Community
Practice
Training, Education,
Workforce

11. Fran Berman, Research Data Alliance
RDA: Accelerate Data Sharing and Interoperability Across
Cultures, Communities,
Scales, Technologies
▪ Technical parts of the data engine:
▪ Data type registries reference model
▪ Wheat data interoperability framework
▪ Rules of the road:
▪ Common agreement on data citation
▪ Common practice for data repositories
▪ Principles of legal interoperability
▪ Better drivers
• Summer schools in data science and cloud
computing in the developing world (with
CODATA)
• Active data management plan
development and monitoring
Policy and Practice
Systems
Interoperability
Sustainable
Economics
Common Types,
Standards, Metadata
Training, Education,
Workforce

12. ‹#›
An Area of Convergence and Agreement
Internet Domain
nodes with IP numbers
packages being exchanged
standardized protocols
Data Domain
objects with PID numbers
objects being exchanged
standardized protocols
Slide courtesy P. Wittenberg from L. Lannom from D. Clark

13. How to feed the world RDA Agriculture Interest Group
image courtesy National Farmers Union

14. The Wheat Data Interoperability WG
Active members: Alaux Michael (INRA, France), Aubin Sophie (INRA, France), Arnaud Elizabeth (Bioversity,
France), Baumann Ute (Adelaide Uni, Australia), Buche Patrice (INRA, France), Cooper Laurel (Planteome,
USA), Fulss Richard (CIMMYT, Mexico), Hologne Odile (INRA, France), Laporte Marie-Angélique (Bioversity,
France), Larmand Pierre (IRD, France), Letellier Thomas (INRA, France), Lucas Hélène (INRA, France),
Pommier Cyril (INRA, France), Protonotarios Vassilis (Agro-Know, Greece), Quesneville Hadi (INRA, France),
Shrestha Rosemary (INRA, France), Subirats Imma (FAO of the United Nations, Italy), Aravind Venkatesan
(IBC, France), Whan Alex (CSIRO, Australia)
Co-chairs: Esther Dzalé Yeumo Kaboré (INRA, France), Richard Allan Fulss (CIMMYT, Mexico)
Aims: contribute to the improvement of Wheat related data interoperability
by
Building a common interoperability framework (metadata, data formats and vocabularies)
Providing guidelines for describing, representing and linking Wheat related data
Contributors
Sponsors
slide courtesy Esther Dzalé

15. Guidelines (http://wheatis.org/DataStandards.php)
Data exchange formats
Example: VCF (Variant Call Format) for sequence variation data, GFF3 for genome
annotation data, etc.
Data description best practices
Consistent use of ontologies, consistent use of external database cross references
Data sharing best practices
Share data matrices along with relevant metadata (example: trait along with
method, units and scales or environmental ones)
Useful tools and use cases that highlight data formats and vocabularies issues
A portal of wheat related ontologies and vocabularies
(http://agroportal.lirmm.fr/ontologies?filter=WHEAT)
Allows the access to the ontologies and vocabularies through APIs.
A prototype
Implementation of use cases of wheat data integration within the AgroLD
(Agronomic Linked Data) tool: http://volvestre.cirad.fr:8080/agrold/
The deliverables
slide courtesy Esther Dzalé

16. For data managers, data providers
One stop shop for relevant information related to data management
arise awareness, avoid duplicated efforts, foster adoption of common
practices
Facilitate the use of common data exchange formats easy data
sharing/submission to international repositories
Foster a standardized description of datasets with consistent use of
ontologies and metadata increase the identification, the findability and
the usability of the datasets
For data scientists, bioinfomaticians
Facilitate the access, integration and analysis of data from various
sources
Access to data of higher quality
For top management, researchers
Increase the chance to answer complex questions
Benefits for many target users
slide courtesy Esther Dzalé

17. Crisis of Confidence in
Research
Data Citation

18. Joint Declaration of Data Citation Principles
(Overview)
The Noble Eight-Fold Path to Citing Data
1. Importance
2. Credit and attribution
3. Evidence
4. Unique Identification
5. Access
6. Persistence
7. Specificity and verifiability
8. Interoperability and flexibility
Principles are supplemented with a glossary, references and examples
http://force11.org/datacitation

19. ‹#›Citing Dynamic Data
Data Citation: Data + Means-of-access
▪ Data à time-stamped & versioned (aka history)
Researcher creates working-set via some interface:
▪ Access à assign PID to QUERY, enhanced with
− Time-stamping for re-execution against versioned DB
− Re-writing for normalization, unique-sort, mapping to history
− Hashing result-set: verifying identity/correctness
leading to landing page
S. Pröll, A. Rauber. Scalable Data Citation in Dynamic Large Databases: Model and Reference Implementation. In IEEE Intl.
Conf. on Big Data 2013 (IEEE BigData2013), 2013
http://www.ifs.tuwien.ac.at/~andi/publications/pdf/pro_ieeebigdata13.pdf

20. ‹#›
Output / Results
▪ 14 Recommendations
grouped into 4 phases:
- Preparing data and query store
- Persistently identifying specific data
sets
- Resolving PIDs
- Upon modifications to the data
infrastructure
▪ 2-page flyer
▪ Technical Report to follow
▪ Reference implementations
(SQL, CSV, XML)
▪ Pilots

21. ‹#›
WG Pilots
▪ Pilots and implementations by
▪ LNEC: Critical Infrastructure Monitoring System
▪ Virtual Atomic and Molecular Data Centre
▪ NERC (UK Natural Environment Research Council
Data Centres)
▪ ARGO Buoy Network
▪ River Flow Dataset
▪ ESIP (Earth Science Information Partners)
▪ BCO-DMO
▪ DEXHELPP – Social Security Data
▪ ENVRIplus: Carbon Observation System
▪ Million Song Database, IR Benchmark DBs
▪ Several others under discussion…

22. More stories of interconnection and
glocality in RDA
• Unplanned interconnection Data Registries, Data Publishing and OpenAire
• Two for the price of one in WUSTL Air Quality portal.
• Data types for carbon geology across continent (plus materials science,
hydrology, more)
• EOSC?

23. Moving forward
• Future Directions—communication, engagement, and coordination
• Bridging the bridges—ever more interconnection, reference implementations,
engagement with ESOC and national data services.
• Diversifying the funding portfolio

24. • The group of government and non-profit science funding organisations that
support the data and science communities to participate in RDA activities:
• European Commission (DG CNCT)
• US Government (NSF and NIST)
• Australian Government
• Japanese Government (JST)
• UK Government (Jisc)
• Sloan Foundation
• MacArthur Foundation
• Allows agencies the opportunity to share policies and funding program plans that
support data sharing across the globe, and thereby amplify their impact.
• Explore actual policy impacts.
• Related to but distinct from RDA. A parallel informal organisation.
RDA Funders Forum

25. The Yin and Yang of national and international support

26. • personnel—encourage your staff and grantees to participate in
RDA
• projects and use cases
• make local concerns global concerns
• establish niches or areas of excellence
How the national can help the global
(and thereby the national)

27. • networks and connections to organisations, countries, resources
• amplification of local effort
• access to diverse experts
• efficiency and cost savings
How the global can help the national
(and thereby the global)

28. 12-16 September 2016
in
Denver, Colorado, USA

29. Info:
enquiries@rd-alliance.org
@resdatall