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E-SI Theme: Exploiting Diverse Sources of Scientific Data Re-use or Re-invention - a Roadmap for Data Integration 27 th -28th November 2006 Prof. Jessie.

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Presentation on theme: "E-SI Theme: Exploiting Diverse Sources of Scientific Data Re-use or Re-invention - a Roadmap for Data Integration 27 th -28th November 2006 Prof. Jessie."— Presentation transcript:

1 e-SI Theme: Exploiting Diverse Sources of Scientific Data Re-use or Re-invention - a Roadmap for Data Integration 27 th -28th November 2006 Prof. Jessie Kennedy e-SI Research Theme Leader

2 Exploiting Diverse Sources of Scientific Data2 e-SI Research Theme  Exploiting Diverse Sources of Scientific Data  Aim of theme is to investigate some of the issues and solutions to exploiting diverse sources of scientific data.  Theme Wiki http://wiki.esi.ac.uk

3 Exploiting Diverse Sources of Scientific Data3 Workshops hosted in theme:  Spatiotemporal Databases for Geosciences, Biomedical Sciences and Physical sciences, eSI, 1-2 November 2005  Oracle Corporation and the e-Science Institute Seminar - Temporal Database in Depth: Time and the Data Warehouse, eSI, 3 November 2005  The Second Workshop on Scientific Data Mining, Integration and Visualization (SDMIV2), eSI, December 2005  DIALOGUE meeting, 9-10 February 2006  Integrated Health Records - Practice and Technology, 9-10 March 2006  Taxonomic Databases Working Group (TDWG) Technical Architecture Group meeting, 11 April 2006  Taxonomic Databases Working Group (TDWG) Core Ontology, 16-18 May  RDF, Ontologies and Meta-Data Workshop, 7-9 June 2006  Taxonomic Databases Working Group (TDWG) GUIDs-2, 10-12 June 2006  The Closed World of Databases Meets the Open World of the Semantic Web 12-13 th October 2006

4 Exploiting Diverse Sources of Scientific Data4 Workshops hosted in theme:  Spatiotemporal Databases for Geosciences, Biomedical Sciences and Physical sciences, eSI, 1-2 November 2005  Oracle Corporation and the e-Science Institute Seminar - Temporal Database in Depth: Time and the Data Warehouse, eSI, 3 November 2005  The Second Workshop on Scientific Data Mining, Integration and Visualization (SDMIV2), eSI, 14 December 2005  DIALOGUE meeting, 9-10 February 2006  Integrated Health Records - Practice and Technology, 9-10 March 2006  Taxonomic Databases Working Group (TDWG) Technical Architecture Group meeting, 11 April 2006  Taxonomic Databases Working Group (TDWG) Core Ontology, 16-18 May  RDF, Ontologies and Meta-Data Workshop, 7-9 June 2006  Taxonomic Databases Working Group (TDWG) GUIDs-2, 10-12 June 2006  The Closed World of Databases Meets the Open World of the Semantic Web, 12-13 October 2006

5 Exploiting Diverse Sources of Scientific Data5 Recurring Issues  Focus  Architectures for Data Integration  What strategies are used for data integration  workflow architectures  grid architectures  Globally Unique Identifiers  What gets a GUID? Who issues them? What technology?  Metadata, Terminologies and Ontologies needed…  Data discovery for sharing/analysis (integrating)  Understanding the content of data sets  Automatic transformations (semantic mediation)  Will these solve the problems?

6 Exploiting Diverse Sources of Scientific Data6 Metadata and Ontologies  Issues  Standardisation of formats  Creation of metadata and ontologies  Manual and automatic  For whom and by whom?  Many or one ontology (granularity)?  How do we integrate them or map between them?  How do we choose which to use/reuse?  How do we know data is suitable for our purpose?

7 Exploiting Diverse Sources of Scientific Data7 Re-use or Re-invention - a Roadmap for Data Integration  Investigate data integration issues in the Neuroscience community  Data  Collection across sites and populations  Integration of different types of data  Integration of data at different levels of granularity  Ontologies  Harmonisation or Integration  Day 1 - General issues  integration across sites and populations  Day 2 - Special areas of interest  ontologies + information governance  Format  Brief Introductory Talks followed by Roundtable discussions

8 e-SI Theme: Exploiting Diverse Sources of Scientific Data Enjoy the Workshop!


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