Ontology-Based Federated Data Access to Human Studies Information

Human studies are one of the most valuable sources of knowledge in biomedical research, but data about their design and results are currently widely dispersed in siloed systems. Federation of these data is needed to facilitate large-scale data analysis to realize the goals of evidence-based medicine. The Human Studies Database project has developed an informatics infrastructure for federated query of human studies databases, using a generalizable approach to ontology-based data access. Our approach has three main components. First, the Ontology of Clinical Research (OCRe) provides the reference semantics. Second, a data model, automatically derived from OCRe into XSD, maintains semantic synchrony of the underlying representations while facilitating data acquisition using common XML technologies. Finally, the Query Integrator issues queries distributed over the data, OCRe, and other ontologies such as SNOMED in BioPortal. We report on a demonstration of this infrastructure on data acquired from institutional systems and from ClinicalTrials.gov.

[1]  I. Sim,et al.  Clinical trial registration: transparency is the watchword , 2006, The Lancet.

[2]  Renée J. Miller,et al.  LinkedCT: A Linked Data Space for Clinical Trials , 2009, ArXiv.

[3]  Ricardo Pietrobon,et al.  The Database for Aggregate Analysis of ClinicalTrials.gov (AACT) and Subsequent Regrouping by Clinical Specialty , 2012, PloS one.

[4]  Dan Suciu,et al.  Neuroinformatics Original Research Article Distributed Xquery-based Integration and Visualization of Multimodality Brain Mapping Data , 2022 .

[5]  Julie Evans,et al.  Model Formulation: The BRIDG Project: A Technical Report , 2008, J. Am. Medical Informatics Assoc..

[6]  Diego Calvanese,et al.  The MASTRO system for ontology-based data access , 2011, Semantic Web.

[7]  D. Altman,et al.  Preparing raw clinical data for publication: guidance for journal editors, authors, and peer reviewers , 2010, BMJ : British Medical Journal.

[8]  Mor Peleg,et al.  A practical method for transforming free-text eligibility criteria into computable criteria , 2011, J. Biomed. Informatics.

[9]  Hyo Jong Lee,et al.  Application of Neuroanatomical Ontologies for Neuroimaging Data Annotation , 2010, Front. Neuroinform..

[10]  James F. Brinkley,et al.  Distributed Queries for Quality Control Checks in Clinical Trials , 2010 .

[11]  Xiaoying Wu,et al.  EliXR: an approach to eligibility criteria extraction and representation , 2011, J. Am. Medical Informatics Assoc..

[12]  Richard H. Scheuermann,et al.  The Human Studies Database Project: Federating Human Studies Design Data Using the Ontology of Clinical Research , 2010, Summit on translational bioinformatics.

[13]  James F. Brinkley,et al.  A Query Integrator and Manager for the Query Web , 2012, J. Biomed. Informatics.

[14]  Ida Sim,et al.  Network analysis of clinical trials on depression: implications for comparative effectiveness research. , 2010, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[15]  Marianne Shaw,et al.  Ontology View Query Management , 2010 .

[16]  Nicholas C. Ide,et al.  The ClinicalTrials.gov results database--update and key issues. , 2011, The New England journal of medicine.

[17]  E. Prud hommeaux,et al.  SPARQL query language for RDF , 2011 .

[18]  Jocelyn Kaiser,et al.  Making Clinical Data Widely Available , 2008, Science.