Fast and Accurate Metadata Authoring Using Ontology-Based Recommendations

Marcos Martinez-Romero presented "Fast and Accurate Metadata Authoring Using Ontology-Based Recommendations" at the 2017 American Medical Informatics Association (AMIA).

Abstract: In biomedicine, high-quality metadata are crucial for finding experimental datasets, for understanding how experiments were performed, and for reproducing those experiments. Despite the recent focus on metadata, the quality of metadata available in public repositories continues to be extremely poor. A key difficulty is that the typical metadata acquisition process is time-consuming and error prone, with weak or nonexistent support for linking metadata to ontologies. There is a pressing need for methods and tools to speed up the metadata acquisition process and to increase the quality of metadata that are entered. In this paper, we describe a methodology and set of associated tools that we developed to address this challenge. A core component of this approach is a value recommendation framework that uses analysis of previously entered metadata and ontology-based metadata specifications to help users rapidly and accurately enter their metadata. We performed an initial evaluation of this approach using metadata from a public metadata repository.

Release Date: 
November 8, 2017
Presentation slides for AMIA 2017
Author List: 
Martínez-Romero M, O’Connor MJ, Shankar R, Panahiazar M, Willrett D, Egyedi AL, Gevaert O, Graybeal J, Musen MA
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Last Updated: 
Nov 9 2017 - 11:14am