Affiliation:
1. MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol , Bristol, BS8 2BN, United Kingdom
2. NIHR Bristol Biomedical Research Centre, University of Bristol , Bristol, BS8 2BN, United Kingdom
Abstract
Abstract
Motivation
Integrating information from data sources representing different study designs has the potential to strengthen evidence in population health research. However, this concept of evidence “triangulation” presents a number of challenges for systematically identifying and integrating relevant information. These include the harmonization of heterogenous evidence with common semantic concepts and properties, as well as the priortization of the retrieved evidence for triangulation with the question of interest.
Results
We present Annotated Semantic Queries (ASQ), a natural language query interface to the integrated biomedical entities and epidemiological evidence in EpiGraphDB, which enables users to extract “claims” from a piece of unstructured text, and then investigate the evidence that could either support, contradict the claims, or offer additional information to the query. This approach has the potential to support the rapid review of preprints, grant applications, conference abstracts, and articles submitted for peer review. ASQ implements strategies to harmonize biomedical entities in different taxonomies and evidence from different sources, to facilitate evidence triangulation and interpretation.
Availability and implementation
ASQ is openly available at https://asq.epigraphdb.org and its source code is available at https://github.com/mrcieu/epigraphdb-asq under GPL-3.0 license.
Funder
UK Medical Research Council Integrative Epidemiology Unit
Publisher
Oxford University Press (OUP)