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Enabling Semantic Data Access for Toxicological Risk Assessment

Myklebust, E. B., Jimenez-Ruiz, E., Chen, J., Wolf, R. and Tollefsen, K. E. (2019). Enabling Semantic Data Access for Toxicological Risk Assessment. .

Abstract

Experimental effort and animal welfare are concerns when exploring the effects a compound has on an organism. Appropriate methods for extrapolating chemical effects can further mitigate these challenges. In this paper we present the efforts to (i) (pre)process and gather data from public and private sources, varying from tabular files to SPARQL endpoints, (ii) integrate the data and represent them as a knowledge graph with richer semantics. This knowledge graph is further applied to facilitate the retrieval of the relevant data for a ecological risk assessment task, extrapolation of effect data, where two prediction techniques are developed.

Publication Type: Monograph (Technical Report)
Publisher Keywords: Toxicology, Ecology, Risk Assessment, Knowledge Graph, Semantic Web, Effect Prediction
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
Related URLs:
Date Deposited: 07 Oct 2019 10:42
URI: https://openaccess.city.ac.uk/id/eprint/22931
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