Institutional Repositories and geospatial data : the GRADE survey

1. Institutional Repositories and geospatial data : the GRADE survey Pauline Simpson National Oceanography Centre, Southampton GRADE Project Meeting 30 Oct 2006

2. Overview • Work Package 4 • Survey • Results • SWOT • Conclusions

3. WP 4 : scoping the role of institutional repositories for geospatial data • Predetermined views • Audit • SWOT • Recommendations on geospatial data management within institutional repositories

4. What is the real GRADE question? • IRs and Datasets with geospatial attributes • Data = numeric, imagery, graphic etc • IR versus Subject IRs (project poster; feedback on SWOT analysis)

5. Survey : Jan – Mar 2006

6. Survey • Call: GRADE Partners; JISC Repositories; SHERPA List; American Scientist; every UK Repository listed in ROAR • 35 Responses • 24 x UK Uni – 7 x Overseas – 2 x data centres – 1 x Research Council + anon • Low • I confess I thought twice about filling in the questionnaire originally as it was so specific and sounded vaguely scary!(now I've done it again, I remember I definitely did fill it in last time). So I guess the specificity of the topic may account for the low response… • Question formulation • Is your repository publicly available, if not who are your depositors and users?

7. Survey Responses • Handout – discussion • Software used • Majority either EPrints or DSPace • Accept geospatial datasets • ? Possibly answering for datasets per se • IRs treatment of geospatial data • Too busy with publications • Discussed as future activity • Not really been offered any • Software not designed ***** • No special metadata fields • Long Term access • Acknowledgement of preservation needs • Repository was first step • No guidance at present

8. IR Software • DSpace overtly publicises treatment of datasets • EPrints does not • anecdote • GRADE Demonstrator Repository – DSpace • Why not EPrints?

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10. Very different metadata fields - non Dublin Core

12. 6. Generally, do you think that archiving and providingaccess to research data is something institutions (institutional repositories) should do or specialist data centres? • Depends on the dataset • Role for both, not mutually exclusive • Specialist data centres have the skills • In the absence of a data centre IRs provide institutional level archive • Showcase for all research • It does not matter who does it as long as it is done

13. SWOT analysis • Should Institutional Repositories have a role in geospatial data ? • What are the • Strengths • Weaknesses • Opportunities • Threats • (handout)

14. Storage Preservation Metadata Visibility? Dataset integrity Storage Preservation Metadata Visibility ? Data disaggregated Quality control Information products IR as a Data Archive vs Data Centre

15. SWOT - Strengths • One repository – less admin overhead • Linking text, dataset, images easier • Showcase for all institutional research • IR Software - Open Access – interoperability - visibility • International Standards • Metadata skills from Information community • Dataset citation • Citation analysis, personal promotion

16. SWOT - Weaknesses • Software not designed to cope with data – additional metadata parameters required eg geospatial data = location coordinates, instrument etc • No IR metadata schema for data • IR staff without Data Processing skills • IRs do not quality control content • Production of information products? • Storage – Preservation (all media types) • OA culture not yet extended to data altho OEDC, EU etc. Some Research Councils mandate deposit of data from funded research into designated data centres.

17. SWOT - Opportunities • Offers a data archive (where non exists) • Treats ‘orphan’ dataset not accepted by DCs • Expansion of IR staff skills • Showcase in one digital repository of all research output • Mandate for datasets also • Integration – joined up research • Funding – e-Research • Data citation model • Data and Information communities working together • Dataset harvesting from IRs to data centres

18. SWOT - Threats • Turf war • Will funding follow – will funding stream for data reduce? • Too large an undertaking for IR • Data lost in publication ‘bucket’ • ‘Thematic’ datasets distributed • No migration/preservation • Datasets fall ‘between stools’

19. Conclusions • IRs are not dealing with geospatial data • but not adverse to try • IR Software not specifically designed for data • but demonstrators show it can cope but … • IRs could operate as a Data Archive • but questions re funding • Where there are thematic Designated Data Centres these should be the repository of choice • ‘Orphan’ datasets not accepted by DDCs should be deposited into an IR to ensure preservation and visibility • Ultimate goal is that datasets are permanently visible and available: Data Centres and IRs both have a role - should work together.

20. Thanks Pauline Simpson ps@noc.soton.ac.uk