For more than two decades, our laboratory has been studying technology to develop, manage, and use formal descriptions of biomedical concepts. The result of this work is Protege, a workbench that allows users to edit and apply controlled terminologies, ontologies, and knowledge bases to a wide range of information-management problems. To date, more than 50,000 people have registered as users of the system. Many diverse projects in biomedicine-supported by nearly every institute and center at NIH-have become critically dependent on this software and the knowledge-engineering principles that it supports. This P41 competing renewal application seeks to continue support for Protege, as a biomedical informatics resource that will benefit the system's entire user community. We propose technology research and development to expand the capabilities of the Protege system to meet the current and anticipated needs of the user community. We will re-engineer Protege with a service-oriented architecture that can adapt to the requirements of new ontology languages, large ontology repositories, and cutting-edge ontology-management-services, such as reasoning, alignment, and evolution. We will create support for collaborative ontology development, in the context of both large, centralized projects and open, decentralized efforts. We also will develop advanced support for using ontologies in application software development and as integral parts of software systems. As a biomedical informatics resource, we will expand our collaborative research projects with other Prot?g? users. We will provide service to the Protege user community through enhanced technical support, user documentation, tutorials, and workshops. These activities will serve to disseminate information about the resource and will aid research and development in many aspects of biomedical informatics both in the United States and internationally.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Biotechnology Resource Grants (P41)
Project #
5P41LM007885-08
Application #
8076789
Study Section
Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Ye, Jane
Project Start
2003-06-01
Project End
2011-12-31
Budget Start
2010-07-01
Budget End
2011-12-31
Support Year
8
Fiscal Year
2010
Total Cost
$956,625
Indirect Cost
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
McMurray, J; Zhu, L; McKillop, I et al. (2015) Ontological modeling of electronic health information exchange. J Biomed Inform 56:169-78
Sluka, James P; Shirinifard, Abbas; Swat, Maciej et al. (2014) The cell behavior ontology: describing the intrinsic biological behaviors of real and model cells seen as active agents. Bioinformatics 30:2367-74
Bilder, Robert M; Howe, Andrew G; Howe, Andrew S et al. (2013) Multilevel models from biology to psychology: mission impossible? J Abnorm Psychol 122:917-27
Tudorache, Tania; Nyulas, Csongor; Noy, Natalya F et al. (2013) WebProtégé: A Collaborative Ontology Editor and Knowledge Acquisition Tool for the Web. Semant Web 4:89-99
Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga et al. (2013) Automated detection of heuristics and biases among pathologists in a computer-based system. Adv Health Sci Educ Theory Pract 18:343-63
Bialas, Andrzej (2011) Common criteria related security design patterns for intelligent sensors--knowledge engineering-based implementation. Sensors (Basel) 11:8085-114
El Saadawi, Gilan M; Azevedo, Roger; Castine, Melissa et al. (2010) Factors affecting feeling-of-knowing in a medical intelligent tutoring system: the role of immediate feedback as a metacognitive scaffold. Adv Health Sci Educ Theory Pract 15:9-30
Boyce, Richard; Collins, Carol; Horn, John et al. (2009) Computing with evidence Part I: A drug-mechanism evidence taxonomy oriented toward confidence assignment. J Biomed Inform 42:979-89
Larson, Stephen D; Martone, Maryann E (2009) Ontologies for Neuroscience: What are they and What are they Good for? Front Neurosci 3:60-7
Boyce, Richard; Collins, Carol; Horn, John et al. (2009) Computing with evidence Part II: An evidential approach to predicting metabolic drug-drug interactions. J Biomed Inform 42:990-1003

Showing the most recent 10 out of 33 publications