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)
• caGRID – the existing caBIG grid initiative
and related tools. (Shannon Hastings and
the OSU team)
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.
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.
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.
The Old and New Database Access
Methods
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.
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).
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.
Introduce Integration
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.