A unified framework for managing provenance information in translational research

BMC Bioinformatics

Research Article

Todd Minning¹  Olivier Bodenreider²  Amit P Sheth³  Priti Parikh³  Vinh Nguyen³  Satya S Sahoo⁴ 

[1] Center for Tropical and Emerging Global Diseases, Univeristy of Georgia, Athens, GA, USA;Lister Hill National Center for Biomedical Communications, National Library of Medicine, NIH, Bethesda, MD, USA;The Kno.e.sis Center, Department of Computer Science and Engineering, Wright State University, Dayton, OH, USA;The Kno.e.sis Center, Department of Computer Science and Engineering, Wright State University, Dayton, OH, USA;Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, OH, USA;

关键词: Resource Description Framework;    Unify Medical Language System;    Query Operator;    Query Pattern;    Provenance Information;   

DOI  :  10.1186/1471-2105-12-461

 received in 2011-05-03, accepted in 2011-11-29,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundA critical aspect of the NIH Translational Research roadmap, which seeks to accelerate the delivery of "bench-side" discoveries to patient's "bedside," is the management of the provenance metadata that keeps track of the origin and history of data resources as they traverse the path from the bench to the bedside and back. A comprehensive provenance framework is essential for researchers to verify the quality of data, reproduce scientific results published in peer-reviewed literature, validate scientific process, and associate trust value with data and results. Traditional approaches to provenance management have focused on only partial sections of the translational research life cycle and they do not incorporate "domain semantics", which is essential to support domain-specific querying and analysis by scientists.ResultsWe identify a common set of challenges in managing provenance information across the pre-publication and post-publication phases of data in the translational research lifecycle. We define the semantic provenance framework (SPF), underpinned by the Provenir upper-level provenance ontology, to address these challenges in the four stages of provenance metadata:(a) Provenance collection - during data generation(b) Provenance representation - to support interoperability, reasoning, and incorporate domain semantics(c) Provenance storage and propagation - to allow efficient storage and seamless propagation of provenance as the data is transferred across applications(d) Provenance query - to support queries with increasing complexity over large data size and also support knowledge discovery applicationsWe apply the SPF to two exemplar translational research projects, namely the Semantic Problem Solving Environment for Trypanosoma cruzi (T.cruzi SPSE) and the Biomedical Knowledge Repository (BKR) project, to demonstrate its effectiveness.ConclusionsThe SPF provides a unified framework to effectively manage provenance of translational research data during pre and post-publication phases. This framework is underpinned by an upper-level provenance ontology called Provenir that is extended to create domain-specific provenance ontologies to facilitate provenance interoperability, seamless propagation of provenance, automated querying, and analysis.

【 授权许可】

CC BY   
© Sahoo et al; licensee BioMed Central Ltd. 2011