The Ontology of Clinical Research (OCRe): an informatics foundation for the science of clinical research.
To date, the scientific process for generating, interpreting, and applying knowledge has received less informatics attention than operational processes for conducting clinical studies. The activities of these scientific processes - the science of clinical research - are centered on the study protocol, which is the abstract representation of the scientific design of a clinical study. The Ontology of Clinical Research (OCRe) is an OWL 2 model of the entities and relationships of study design protocols for the purpose of computationally supporting the design and analysis of human studies. OCRe's modeling is independent of any specific study design or clinical domain. It includes a study design typology and a specialized module called ERGO Annotation for capturing the meaning of eligibility criteria. In this paper, we describe the key informatics use cases of each phase of a study's scientific lifecycle, present OCRe and the principles behind its modeling, and describe applications of OCRe and associated technologies to a range of clinical research use cases. OCRe captures the central semantics that underlies the scientific processes of clinical research and can serve as an informatics foundation for supporting the entire range of knowledge activities that constitute the science of clinical research.
Department of Medicine, University of California, San Francisco, CA, United States. Electronic address: ida.sim@ucsf.edu.
Ida
I
Sim
Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, United States.
Samson W
SW
Tu
Department of Medicine, University of California, San Francisco, CA, United States.
Simona
S
Carini
Division of Health Sciences Informatics, Johns Hopkins University, Baltimore, MD, United States.
Harold P
HP
Lehmann
Department of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States.
Brad H
BH
Pollock
Department of Information Systems, University of Haifa, Haifa, Israel.
Mor
M
Peleg
Department of Research Design and Biostatistics, The Rockefeller University, New York, NY, United States.
Knut M
KM
Wittkowski
D064229:Biological Ontologies; D035843:Biomedical Research; D019295:Computational Biology; D019317:Evidence-Based Medicine; D006801:Humans; D008490:Medical Informatics; D008962:Models, Theoretical
Clinical research; Clinical research informatics; Eligibility criteria; Evidence-based medicine; Ontology; Trial registration