The Chemistry Experiment: Building a Semantic Data

 
The Chemistry Experiment: Building a Semantic Datagrid over Multiple Stores,Two infrastructure enablers On demand transparently constructed multi-organisational federations of distributed services Distributed computing middleware Computational Integration
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Presentation Transcript
Slide1 : Presented by David De Roure dder@ecs.soton.ac.uk http://www.semanticgrid.org/presentations/RDFcombechem.ppt The Chemistry Experiment: Building a Semantic Datagrid over Multiple Stores
Two infrastructure enablers : Two infrastructure enablers On demand transparently constructed multi-organisational federations of distributed services Distributed computing middleware Computational Integration An automatically processable, machine understandable web Distributed knowledge and information management Information integration Goble
Origins of the Semantic Web : Origins of the Semantic Web The Semantic Web is an extension of the current Web in which information is given a well-defined meaning, better enabling computers and people to work in cooperation. It is the idea of having data on the Web defined and linked in a way that it can be used for more effective discovery, automation, integration and reuse across various applications. The Web can reach its full potential if it becomes a place where data can be processed by automated tools as well as people. W3C Activity Statement
Describing the Semantic Grid : Describing the Semantic Grid It’s the Web of Data. Data is what’s in databases. Imagine it’s linked up like documents are linked up on the Web Imagine a spreadsheet where you can import data about anything from anywhere RDF is to data what HTML is to documents
Rocket Science (not) : Rocket Science (not) Is this rocket science? Well, not really. The Semantic Web, like the World Wide Web, is just taking well established ideas, and making them work interoperably over the Internet. This is done with standards, which is what the World Wide Web Consortium is all about. We are not inventing relational models for data, or query systems or rule-based systems. We are just webizing them. We are just allowing them to work together in a decentralized system - without a human having to custom handcraft every connection. Tim Berners-Lee, Business Case for the Semantic Web, http://www.w3.org/DesignIssues/Business
Making Knowledge Explicit : Making Knowledge Explicit RDF DAML+OIL OIL OWL All influenced by RDF Ontology Inference Layer DAML OWL Lite (thesaurus) OWL DL (reason-able) OWL Full (anything goes) OWL Web Ontology Language RDF Resource Description Framework
The Semantic Grid Report 2001 : The Semantic Grid Report 2001 At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. www.semanticgrid.org NB Report updated – March 2005 issue of Proceedings of the IEEE D. De Roure, N.R. Jennings and N.R. Shadbolt. Research agenda for the Semantic Grid: A future e-science infrastructure. Technical Report UKeS-2002-02, National e-Science Centre, December 2001. D. De Roure, N.R. Jennings and N.R. Shadbolt. The Semantic Grid: Past, Present, and Future, Proceedings of the IEEE, Volume 93, Issue 3, March 2005, pages 669-681.
Combe Chem pilot project : X-Ray e-Lab Analysis Properties Properties e-Lab Simulation Video Diffractometer Grid Middleware Structures Database Combe Chem pilot project
Slide13 : Grid E-Scientists Entire E-Science Cycle Encompassing experimentation, analysis, publication, research, learning Digital Library E-Scientists Graduate Students Undergraduate Students E-Experimentation E-Scientists eBank
Characteristics of domain : Characteristics of domain Goals To do new science! To cope with the data deluge To use data in anticipated and unanticipated ways To be able to ask new questions Lots of relational databases and stores Some third party Difficult to change schema! Commercial information sources Instruments on the Grid
Characteristics of domain 2 : Characteristics of domain 2 Chemical Identifiers Domain is well structured in certain ways e.g. the periodic table! Provenance matters For interpretation of data For legal purposes Information is Incomplete Inconsistent Time-varying
Strategy : Strategy Grounding in established operational practice – our starting point is to study chemists at work Capturing a rich set of associations between all types of things, expressed pervasively in RDF and hence explicitly addressing the sharing of identifiers Metadata capture should be automated – our goal is augmentation not disruption Information will be reused in both anticipated and unanticipated ways
CombeChem Smart Tea : www.smarttea.org CombeChem Smart Tea
COSHH : COSHH
Slide20 : A digital lab book replacement that chemists were able to use, and liked.
Data model : Data model Process record Provenance record Measurements Processes Annotations Service invocations Secure time-stamps etc… Plan Intended actions: guide to chemist, or [later] workflow
Slide24 : Smart Lab Snapshot
AKTivity : AKTivity 3store AKT Reference data sources gatherers and mediators ontology knowledge repository (triplestore) applications
Triplestore Evaluation : Triplestore Evaluation
CombeChem Semantic Datagrid : CombeChem Semantic Datagrid Existing datastores linked by triplestores 80 million triples (and decreasing!) in 3store A social experiment! Folksomony? Chemists built ontology for units RDF used for metadata and data Chemists appreciate powerful queries and flexibility Metadata infrastructure is in place
Slide31 : KMI, AIAI
Slide32 : Images from NASA
Meeting Replay tool for Earth scientists, synchronising video of Mars crew’s discussion with their Compendium maps : Meeting Replay tool for Earth scientists, synchronising video of Mars crew’s discussion with their Compendium maps Copyright, 2004, RIACS/NASA Ames, Open University, Southampton University Not to be used without permission RIACS/NASA Ames Research Center Mobile Agents Project Maarten Sierhuis KMi Open University CoAKTinG Project Simon Buckingham-Shum & Al Selvin Southampton University CoAKTinG Project Kevin Page Danius Michaelides Dave De Roure Nigel Shadbolt
Completing the Digital Chain : Completing the Digital Chain Privacy issues Different (conflicting) interpretations are valid “Free the data” Semantic Web liberates it and provides mechanism for interpretaion and provenance Rule language may help
Scaling the triplestores : Scaling the triplestores Moved from… A model of harvesting data from multiple sources into one scalable store to A model of distributed RDF sources and caching what is needed for the task at hand into multiple stores fit-for-purpose
Scaling the triplestores : Scaling the triplestores Q. What’s the answer to scalable RDF? A. The Web 
Slide37 : Realising the network effect Moving beyond centralised stores Automated assembly Collaboration tools
Summary : Summary Semantic Web technologies can be applied off-the-shelf within a DataGrid context Chemists appreciate flexibility of semi-structured approach Grounding in operational practice is an effective implementation strategy Evaluate triplestores against purpose (lifecycle) It’s the Semantic Web! Now we’re ready to begin 
Contacts : Contacts David De Roure – Semantic Grid dder@ecs.soton.ac.uk Jeremy Frey – CombeChem j.g.frey@soton.ac.uk Carole Goble – Semantic Grid carole@cs.manchester.ac.uk See www.semanticgrid.org See www.aktors.org Thanks to: Jonathan Essex Jeremy Frey Stephen Harris Nick Gibbins Hugh Glaser Rob Gledhill Danius Michaelides Hugo Mills Kevin Page Jamie Robinson Michael Streatfield Kieron Taylor