1. Summary of RDA Outputs so far dr. Ir. Herman Stehouwer 22 September 2015

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4. 4  Neutral Forum for discussing issues  Generates global discussions  Very diverse  Roles  Disciplines  -> Increased insight (e.g. Jamie)  -> Increased needs alignment (e.g. Antonio) Intangible Outcomes

5. 5 RDA Working Groups  Form the Foundation for RDA Community Impact!  Working Groups envisioned as accelerants to data sharing practice and infrastructure in the short-term with the overarching goal of advancing global data-driven discovery and innovation  RDA Working Group profile:  Short-term: 12-18 months  Focused efforts with specific actions adopted by specific communities  International participation  Open, voluntary, consensus-driven  Complementary to effective efforts elsewhere 5 Potential outcomes / deliverables: New data standards or harmonization of existing standards. Greater data sharing, exchange, interoperability, usability and re-usability. Greater discoverability of research data sets. Better management, stewardship, and preservation of research data.

6. 6 An Interest Group (IGs) can be established prior to a Working Group for community discussion of issues and areas that facilitate data-driven research. IGs are longer-term groups defining common issues and interests. WGs and IGs are collaborating intensively with groups in comparable initiatives such as IETF, CODATA, WDS, W3C.  Possible functions  Create new WGs  Communication/Coordination  Domains  Themes  External pariets (WDS, CODATA, etc.) RDA Interest Groups

7. 7  Presented at P4 in Amsterdam  Far along in adoption, all have ratified recommendations 1.DFT 2.DTR 3.PIT 4.PP First Four Outputs

8. 8 RDA Results I: common data model PIDs at the beginning of trust chain need a worldwide, independent and robust PID system worldwide metadata are essential in anonymous data world taken from RDA WG Data Foundation & Terminology

9. 9  result: a registry for data types  simple example: you get an unknown file, pull it on DTR and content is being visualized  DTR can also be used to describe and re-use semantic content  no free lunch: someone needs to register and define type  PIT Demo already working with DTR RDA Results II: Data Type Registry

10. 10  result: a generic API and a set of basic attributes  a PID Record is like a Passport (Number, Photo, Exp-Date, etc.)  if all PID Service-Provider agree on one API and talk the same language (registered terms) SW development will become easy  Test-Installation in operation together with DTR RDA Results III: PID Information Types

11. 11  due to unforeseen circumstances need until P5  Practical Policies = executable Workflow Statements  result at P5: a set of Best Practice PPs for a number of typical DM/DP tasks (Integrity Check, Replication, etc.)  currently a large collection of PPs, currently being evaluated huge simplification for data stewards finally feasible quality checks and certification huge step in trust improvement RDA Results IV: Practical Policies

12. 12  Presented at the last Plenary in San Diego  Working on Adoption / Recommendations 1.Citation of Dynamic Data 2.DDRI 3.Metadata Standards Directory 4.Wheat Data Interoperability Second Group of Outcomes

13. 13 RDA Results V: Citation of Dynamic Data We have: Data + Means-of-access Dynamic Data Citation: Cite data dynamically via query! Steps / Principles: 1.Data  versioned (history, with time-stamps) Researcher creates working-set via some interface: 2.Access  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  Many prototypes and pilot impletmentations

14. 14  Enabling cross-platform discovery between research data registries  Interoperability projects between ANDS, CERN, Dryad based on DataCite and ORCID services  Research Data Switchboard  Interoperability between da-ra and DataPASS based on Dataverse  De-duplication project; a collaboration between Data Curation Unit and DANS  This infrastructure enables anyone to query and find links between registries. It can be used by universities, repositories, registries and funders. RDA Results VI: DDRI

15. 15  Standards are a good thing  But, only works when people use the same standards  Too few standards -> People do their own thing  Too many standards -> Fragmentation  Goal: Develop a directory listing Metadata standards  Comprehensive  Easy to contribute to  Extend DCC Metadata Directory  Make it community-updatable RDA Results VII: Metadata Standards Directory

16. 16  Wheat is a major food-staple  Need data interoperability to increase production  Encourage Interoperability by:  Creating an Interoperability framework  Providing guidelines on Wheat data (cookbook)  Repository of linked vocabularies  Adoption by WheatIS (Wheat Initiative), FAO, etc.  Currently in community validation RDA Results VIII: Wheat

17. 17 1.DSA-WDS Audit and Certification 2.Publishing: 1.Bibliometrics 2.Workflows 3.Services  Will be presented at this plenary Upcoming wave of Outputs