Format

Send to

Choose Destination
J Am Med Inform Assoc. 2018 Jan 13. doi: 10.1093/jamia/ocx121. [Epub ahead of print]

DataMed - an open source discovery index for finding biomedical datasets.

Author information

1
School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
2
Center for Research in Biological Systems.
3
Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA.
4
e-Research Centre, University of Oxford, Oxford, UK.
5
National Institutes of Health, Bethesda, MD, USA.
6
University of Michigan, Ann Arbor, MI, USA.

Abstract

Objective:

Finding relevant datasets is important for promoting data reuse in the biomedical domain, but it is challenging given the volume and complexity of biomedical data. Here we describe the development of an open source biomedical data discovery system called DataMed, with the goal of promoting the building of additional data indexes in the biomedical domain.

Materials and Methods:

DataMed, which can efficiently index and search diverse types of biomedical datasets across repositories, is developed through the National Institutes of Health-funded biomedical and healthCAre Data Discovery Index Ecosystem (bioCADDIE) consortium. It consists of 2 main components: (1) a data ingestion pipeline that collects and transforms original metadata information to a unified metadata model, called DatA Tag Suite (DATS), and (2) a search engine that finds relevant datasets based on user-entered queries. In addition to describing its architecture and techniques, we evaluated individual components within DataMed, including the accuracy of the ingestion pipeline, the prevalence of the DATS model across repositories, and the overall performance of the dataset retrieval engine.

Results and Conclusion:

Our manual review shows that the ingestion pipeline could achieve an accuracy of 90% and core elements of DATS had varied frequency across repositories. On a manually curated benchmark dataset, the DataMed search engine achieved an inferred average precision of 0.2033 and a precision at 10 (P@10, the number of relevant results in the top 10 search results) of 0.6022, by implementing advanced natural language processing and terminology services. Currently, we have made the DataMed system publically available as an open source package for the biomedical community.

KEYWORDS:

data discovery index, metadata, dataset, information storage and retrieval, information dissemination

PMID:
29346583
DOI:
10.1093/jamia/ocx121

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center