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© S.J. Coles 2006 Institutional Data Repositories for Chemistry Simon Coles School of Chemistry, University of Southampton, U.K.

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Presentation on theme: "© S.J. Coles 2006 Institutional Data Repositories for Chemistry Simon Coles School of Chemistry, University of Southampton, U.K."— Presentation transcript:

1 © S.J. Coles 2006 Institutional Data Repositories for Chemistry Simon Coles School of Chemistry, University of Southampton, U.K.

2 © S.J. Coles 2006 Why? Funding Body Viewpoint

3 © S.J. Coles 2006 Why? Curation in the Laboratory Data from experiments conducted as recently as six months ago might be suddenly deemed important, but those researchers may never find those numbers – or if they did might not know what those numbers meant Lost in some research assistants computer, the data are often irretrievable or an undecipherable string of digits To vet experiments, correct errors, or find new breakthroughs, scientists desperately need better ways to store and retrieve research data Data from Big Science is … easier to handle, understand and archive. Small Science is horribly heterogeneous and far more vast. In time Small Science will generate 2-3 times more data than Big Science. Lost in a Sea of Science Data S.Carlson, The Chronicle of Higher Education (23/06/2006)

4 © S.J. Coles 2006 Why? Publishing and the Data Deluge 30,000, ,000, ,000

5 © S.J. Coles 2006 Why? Publishing Data and Information Loss

6 © S.J. Coles 2006 Separating Data from Interpretations Underlying data (Institutional data repository) Intellect & Interpretation (Journal article, report, etc)

7 © S.J. Coles 2006 Data capture and curation at the point of generation in the laboratory The Repository for the Laboratory – R4L

8 © S.J. Coles 2006 Laboratory IRs and Information Management

9 © S.J. Coles 2006 The R4L Repository Deposit Search / Browse Create new compoundAdd experiment data and metadata

10 © S.J. Coles 2006 Data dissemination and curation by the scientist and host institution eBank-UK and the eCrystals Repository

11 © S.J. Coles 2006 The eCrystals Data Archive

12 © S.J. Coles 2006 Metadata Publication Using simple Dublin Core Crystal structure Title (Systematic IUPAC Name) Authors Affiliation Creation Date Additional chemical information through Qualified Dublin Core Empirical formula International Chemical Identifier (InChI) Compound Class & Keywords Specifies which datasets are present in an entry DOI Rights & Citation Application Profile

13 © S.J. Coles 2006 Metadata and Data Quality Control Data manipulation toolbox Associated Metadata Value added Format conversion

14 © S.J. Coles 2006 Laboratory Data Management and Archive

15 © S.J. Coles 2006 Institutional data repositories and harvesting, aggregation and curation by data centres and third party services eBank-UK Phase 3 – The eCrystals Federation

16 © S.J. Coles 2006 Aggregator services Institutional data repositories Validation Deposit Publication Validation Data analysis, transformation, mining, modelling Search, harvest Presentation services / portals Data discovery, linking, citation Laboratory repository Deposit The eCrystals Global Federation Model Publishers: peer- review journals, conference proceedings, etc Curation Preservation Subject Repository Institution Library & Information Services

17 © S.J. Coles 2006 Exploring the heterogeneous landscape of data repositories Different software platforms Different administrative domains Different Institutional structure Institutional vs Subject repositories Data Repository InteroperabilityORE

18 © S.J. Coles 2006 Preservation and curation by data centres & Institutions G bytes M bytes k bytes Institution Library & Information Services

19 © S.J. Coles 2006 Harvesting, aggregation, value addition and curation by data centres

20 © S.J. Coles 2006 The relationship with (conventional?) publication protocols and procedures Discipline-based publication Domain-based publication Open Access publication

21 © S.J. Coles 2006 Aggregation, linking and information provision by third party services Indexing and aggregating with other datasets Aggregating and linking between datasets and articles Integration into information portals


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