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I2b2 grid integration with Ontology Mapper

I2b2 grid integration with Ontology Mapper. A description of the 2 methods that are currently under development Just a Summary by Rob Wynden (UCSF). There are 2 projects under way. SHRINE – a Harvard based project to create a new grid platform (Andy McMurray and the Harvard team)

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I2b2 grid integration with Ontology Mapper

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  1. I2b2 grid integrationwith Ontology Mapper A description of the 2 methods that are currently under development Just a Summary by Rob Wynden (UCSF)

  2. There are 2 projects under way • SHRINE – a Harvard based project to create a new grid platform (Andy McMurray and the Harvard team) • caGRID – the existing caBIG grid initiative and related tools. (Shannon Hastings and the OSU team)

  3. SHRINE • SHRINE is a new layer of Cells which sit between the existing i2b2 Workbench and the existing i2b2 server. • SHRINE queries are generated using i2b2 Workbench and since SHRINE emulates the SOAP(REST) interface to i2b2 the Workbench code is not even aware of the new SHRINE cells that sit between it and the server.

  4. No Major Modifications Necessary • Since SHRINE uses the existing i2b2 Workbench in an unmodified form it is possible to provide semantic interoperability for SHRINE using a single database view. • The i2b2 workbench displays concepts from the Concept Dimension after filtering by the i2b2 table. The Ontology Mapper extends the Concept Dimension but does not alter any of the existing fields. Therefore i2b2 Workbench (and SHRINE) will work with Ontology Mapper without modification.

  5. SHRINE Layered Integration • The i2b2 Workbench (and SHRINE) query and display data from the Obs Fact Table. • The Ontology Mapper adds 2 additional fact tables, the Mapped Data and Mapped Aggregate fact tables. • Therefore to fully integrate Workbench to Ontology Mapper we have created a simple database View which is a UNION the 3 fact tables and which presents a table definition that is identical to the Obs Fact Table. • The only mod to Workbench that is required is that Workbench needs to reference that Obs Fact View instead of directly accessing the Obs Fact Table.

  6. The Old and New Database Access Methods

  7. caGRID Integration • SHRINE only supports distributed query. However caGRID is a general purpose distributed networking protocol. • caGRID is MUCH more secure than SHRINE. • The integration with i2b2 under way at OSU uses the OSU Introduce Tool.

  8. Encoding Tables • The Ontology Mapper extends the Concept Dimension in i2b2 by adding keys to a new table called Encoding. The Encoding table(s) store information about which Common Data Element (CDR) within the caDSR(ctsDSR,openMDR) each row in the Concept Dimension references. • Therefore the Encoding Table makes it possible (optional) for concept paths to be correlated with specific CDR’s from formal ISO111-79 data models (the flattened form on a formal ontology).

  9. Leveraging Introduce • OSU has modified the caGRID Introduce tool OSU to allow Introduce to connect directly to the i2b2 database and view the Concept Dimension and the associated rows within the Encoding Table(s). • Introduce therefore only reads data from the Mapped Data and Mapped Aggregate Fact tables as all information that it consumes MUST reference CDR’s. Introduce ONLY exposes semantically interoperable data: it does not allow exposure of data directly from the Obs Fact Table.

  10. Introduce Integration

  11. Conclusion and Note • The Ontology Mapper extends i2b2 so that it can contain formally encoded information in a semantically interoperable way. • Both of these projects leverage that functionality for grid based semantic interoperability. • A 3rd method is possible where the SHRINE network protocol can be implemented as a caGRID web service type (just as cQL was). That may be the most platform independent solution but no one is working on that at present.

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