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JOINT SESSION RDA/WDS IG Cost Recovery Models IG Domain Repositories RDA P6, Paris, 23-09-2015

This joint session will present the results of a survey on cost recovery models for data repositories. Breakout groups will conduct SWOT analysis of different funding models. Conclusions and recommendations will be shared.

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JOINT SESSION RDA/WDS IG Cost Recovery Models IG Domain Repositories RDA P6, Paris, 23-09-2015

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  1. JOINT SESSIONRDA/WDS IG Cost Recovery ModelsIG Domain RepositoriesRDA P6, Paris, 23-09-2015

  2. Session programme • 15.30 - 16.00       presentation of survey results (20 min) and questions (10 min) • 16.00 - 16.40       break-out groups: SWOT analysis of the different funding models • 16.40 - 17.00       plenary wrap-up

  3. The IG Cost Recovery objectives and deliverable Remit from the case statement: • A contribution to strategic thinking on cost recovery by conducting research to understand current and possible cost recovery strategies for data centres • Report providing conclusions and recommendations about the appropriateness of different cost recovery models to different situations and the potential of data publication initiatives fitting into a cost recovery strategy

  4. Motivation of the IG Cost Recovery • Why is this work important? • Long-term sustainability of data repositories is under threat in US and Europe “Stakeholder and data volumes are growing rapidly and funding not following.” • Many repositories are seeking alternative models for cost recovery • They would like to know about each other’s efforts

  5. What have we done? • Survey among digital repositories: • 22 repositories interviewed • done by volunteers over phone/Skype • Each interview took at least 1 hour, following a script

  6. Quantitative Survey Results

  7. Quantitative Survey Results

  8. Quantitative Survey Results

  9. Quantitative survey results

  10. Research Performing Organisation Researcher / PI / Project Research Project Funder Private Contracting (Structural) Infrastructure Funder Data Centre / Archive • Structural (central contract) • Hosting Support (indirect or direct support through institutional hosting) • Annual Contract (from depositing institution) • Data Deposit Fee (may be paid by researcher, RPO or publisher; may originate with funder) • Access Charge (for the data or for value-adding services) • R&D Projects (to develop infrastructure or value-adding services) • Private Contracting (services to parties other than core funder)

  11. Income streams in absolute numbers of repositories

  12. Term of funding for the main income stream (in %)

  13. Quantitative Survey Results

  14. Exploring alternative revenue streams

  15. Compatibility with the Open Access principle

  16. Funding options under consideration • Sponsorships • Contracts for specific services offered (hosting, archiving, curation) • Expanding the number of affiliated institutions • Deposit fees • Funders making more money available (given priority for data) • Specific services for the commercial sector (mentioned by one) • More services for national memory institutes

  17. Typology of funding models • Largely structurally funded • Reliant on data access charges • Exploring data deposit fees • Substantial diversification • Propped up by project funding • Supported by host institution

  18. Next steps • Finalising the draft survey report on the basis of the input at RDA P6 • Circulating the draft survey report among key stakeholders to get further input • Presenting the final conclusions and recommendations at RDA P7

  19. Breakout groups: SWOT analysis • Four broad funding models: • Largely structurally funded (including support by the host institution) • Reliant on data access charges • Exploring data deposit fees • Substantial diversification (including project funding) What are the plans, hopes and fears for the future (SWOT) if we look as these different funding models?

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  23. Diversified funding • Many sources, mostly short-term • Project funding • Fees for services • Additional services • Enhanced curation • Data visualization • Online analysis • Computational tools • Confidential data • Support for researchers during projects • Collaborative workspaces • Computational tools • Secure data services

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