DAMES - Data Management through e-Social Science

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DAMES: Data Management through e-Social Science

e-Science approaches in DAMES

Simon JonesDepartment of Computing Science and Mathematics

University of Stirling

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RationaleWe aim to investigate and develop:• ‘e-Infrastructure’ services targeted to data

management requirements across a rich range of social science data resources

• An internet ‘portal’ that will make available a variety of specific data resources as Grid services– augmented with portfolios of tools for supporting the

processes involved in data management

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Approaches (on-going!)

• Social science data resources are distributed, disaggregated and heterogeneous– Metadata description– Semantically-based discovery– Data abstraction/virtual fusion

• Easy but secure access is required– "Virtualization"/"fusion", workflow support for SS– Fine grained authorisation infrastructures

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Meta-data support• Existing metadata standards have been

assessed– Data Documentation Initiative, DDI– Statistical Data and Metadata eXchange, SDMX– UK Data Archive– Nesstar

• Focussing continuing work on exploiting DDI3 – DAMES must engineer compatibility with currently

used metadata aproaches

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Semantically based data discovery

• To extend data discovery through metadata DAMES will develop techniques for data discovery through semantic queries

• OWL ontology framework: to give meaning to data resources

• OWL-S: for developing semantic grid services

• DAMES will support a Grid service for registration and discovery of data resources using semantic grid techniques

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Data from heterogeneous sources• Data abstraction can help with

heterogeneity:– Support for accessing data content without

regard to detailed representation– Metadata support is essential

• Extending current work using OGSA-DAI to deal with a wider variety of SS formats: e.g. SPSS, Stata

• A Grid service to give uniform access to underlying data

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Data from multiple sources• Related data sources may need processing as

if combined– The sources may be distributed and heterogeneous

• DAMES will investigate "virtual fusion" techniques– Leveraging data abstraction and effective metadata

support

• Uniform query processing Grid services will be developed– Related to DQP

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Support for e-Social Science:Workflows

• This research will focus on adapting and extending workflow modelling approaches– BPEL, ebXML, Taverna, WHIP

• Typical social science applications will be supported by workflows, e.g.– Occupational analysis, census analysis, social care

• A visual design tool will be developed for defining new workflows in e-Social Science– Integrated into the DAMES Portal– With execution support

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GEODE: Grid Enabled Occupational Data Environment

• Previous SS/CS collaboration at Stirling• Occupational scheme linking is a common

practice for researchers• Geode enables a virtual community of

occupational information researchers– Portal gateway for occupational information– Data abstraction– Uniform access to resources– Occupational matching services

• Demonstrates viability of the DAMES approach

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GEODE prototype• Windows environment• Java• GridSphere Portal Framework• Globus Toolkit 4

– Index Service (Virtual Organization)– OGSA-DAI WSRF (Data Access Middleware)

• Custom OGSA-DAI resources and activities• Accesses CSV, Relational data resources

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Example: Grid Enabled Occupational Data Environment (GEODE)

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Summary• Distributed, disaggregated, heterogeneous

data sources need:– Metadata– Semantically-based discovery– Data abstraction/virtual fusion– Specialised SS workflows– Security (later in workshop)

• GEODE gives a springboard for GE*DE