Ontocloud - a Clinical Information Ontology Based Data Integration System

Relevant biomedical research relies on finding enough subjects matching inclusion criteria. Researchers struggle to find eligible patients due to: information scattered in many different databases, incompatible data representation, and the technical knowledge required to work directly with databases. We identified the required features of a clinical data search system and used it to design and evaluate Ontocloud, a prototype based on open source software and open standards of a dynamic ontology based database integration system with inference capabilities. A comparison between Ontocloud and three other database integration system showed that our prototype fulfilled its purpose and can be improved to be used in production.

[1]  Olivier Curé,et al.  Integration of relational databases into OWL knowledge bases: demonstration of the DBOM system , 2008, 2008 IEEE 24th International Conference on Data Engineering Workshop.

[2]  Hua Min,et al.  Integration of prostate cancer clinical data using an ontology , 2009, J. Biomed. Informatics.

[3]  Heiner Stuckenschmidt,et al.  Ontology-Based Integration of Information - A Survey of Existing Approaches , 2001, OIS@IJCAI.

[4]  Richard Hull,et al.  Managing semantic heterogeneity in databases: a theoretical prospective , 1997, PODS.

[5]  Alon Y. Halevy,et al.  Answering queries using views: A survey , 2001, The VLDB Journal.

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

[7]  Isabel F. Cruz,et al.  The role of ontologies in data integration , 2005 .

[8]  Laura M. Haas,et al.  Data integration through database federation , 2002, IBM Syst. J..

[9]  Jérôme David,et al.  The Alignment API 4.0 , 2011, Semantic Web.

[10]  P. Smith,et al.  A review of ontology based query expansion , 2007, Inf. Process. Manag..

[11]  Maurizio Lenzerini,et al.  Data integration: a theoretical perspective , 2002, PODS.

[12]  Perry L. Miller,et al.  Model Formulation: QIS: A Framework for Biomedical Database Federation , 2004, J. Am. Medical Informatics Assoc..

[13]  Kyle Chard,et al.  A cloud-based approach to medical NLP. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[14]  Matteo Golfarelli.  Open Source BI Platforms: A Functional and Architectural Comparison , 2009, DaWaK.

[15]  Walter V. Sujansky,et al.  Heterogeneous Database Integration in Biomedicine , 2001, J. Biomed. Informatics.

[16]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[17]  Diego Calvanese,et al.  MASTRO-I: Efficient Integration of Relational Data through DL Ontologies , 2007, Description Logics.