Abstract
We describe an application of the BIRN mediator to the integration of neuroscience experimental data sources. The BIRN mediator is a general purpose solution to the problem of providing integrated, semantically-consistent access to biomedical data from multiple, distributed, heterogeneous data sources. The system follows the mediation approach, where the data remains at the sources, providers maintain control of the data, and the integration system retrieves data from the sources in real-time in response to client queries. Our aim with this paper is to illustrate how domain-specific data integration applications can be developed quickly and in a principled way by using our general mediation technology. We describe in detail the integration of two leading, but radically different, experimental neuroscience sources, namely, the human imaging database, a relational database, and the eXtensible neuroimaging archive toolkit, an XML web services system. We discuss the steps, sources of complexity, effort, and time required to build such applications, as well as outline directions of ongoing and future research on biomedical data integration.
Highlights
Our work in information integration is in the context of the Biomedical Information Research Network (BIRN)1 and reflects a cross institutional collaboration to address a key practical problem, that of integrated information access to information in multiple sources
In this paper we describe our technology solution and approach, taking the context of a data integration application from the Function BIRN (FBIRN) domain (Keator et al, 2008) which is focused on making multi-site functional MRI studies a reality
We developed a wrapper for XNAT over the search REST web service which essentially takes a mediator query in SQL, translates it to an equivalent XML document that is transmitted to XNAT using the REST API, and translates back the XML results from the web service into a relational form
Summary
By integrated data access we broadly mean that a user, for instance a scientific investigator, is abstracted from the fact that data of interest to her may reside in heterogeneous and geographically distributed data sources. Rather she is able to go to a single interface and access data seamlessly as if it were one single harmonized data source. We have explored many diverse data integration applications in neuroscience, nonhuman primate, and cardiovascular informatics, demonstrating the general purpose applicability of our technology and approach
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