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A survey of systematic evidence mapping practice and the case for knowledge graphs in environmental health & toxicology

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A survey of systematic evidence mapping practice and the case for knowledge graphs in environmental health & toxicology. / Wolffe, Taylor; Vidler, John; Halsall, Crispin et al.
In: Toxicological sciences : an official journal of the Society of Toxicology, 25.02.2020.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Wolffe T, Vidler J, Halsall C, Hunt N, Whaley P. A survey of systematic evidence mapping practice and the case for knowledge graphs in environmental health & toxicology. Toxicological sciences : an official journal of the Society of Toxicology. 2020 Feb 25. Epub 2020 Feb 25. doi: 10.1093/toxsci/kfaa025

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@article{b5ff278b02924c05b5a78b73d5264658,
title = "A survey of systematic evidence mapping practice and the case for knowledge graphs in environmental health & toxicology",
abstract = "Systematic evidence mapping offers a robust and transparent methodology for facilitating evidence-based approaches to decision-making in chemicals policy and wider environmental health. Interest in the methodology is growing; however, its application in environmental health is still novel. To facilitate the production of effective systematic evidence maps for environmental health use cases, we survey the successful application of evidence mapping in other fields where the methodology is more established. Focusing on issues of “data storage technology”, “data integrity”, “data accessibility”, and “transparency”, we characterise current evidence-mapping practice and critically review its potential value for environmental health contexts. We note that rigid, flat data tables and schema-first approaches dominate current mapping methods and highlight how this practice is ill-suited to the highly connected, heterogeneous and complex nature of environmental health data. We propose this challenge is overcome by storing and structuring data as “knowledge graphs”. Knowledge graphs offer a flexible, schemaless and scalable model for systematically mapping the environmental health literature. Associated technologies such as ontologies are well-suited to the long-term goals of systematic mapping methodology in promoting resource-efficient access to the wider environmental health evidence base. Several graph storage implementations are readily available, with a variety of proven use cases in other fields. Thus, developing and adapting systematic evidence mapping for environmental health should utilise these graph-based resources to ensure the production of scalable, interoperable and robust maps to aid decision-making processes in chemicals policy and wider environmental health.",
keywords = "systematic evidence map, knowledge graph",
author = "Taylor Wolffe and John Vidler and Crispin Halsall and Neil Hunt and Paul Whaley",
year = "2020",
month = feb,
day = "25",
doi = "10.1093/toxsci/kfaa025",
language = "English",
journal = "Toxicological sciences : an official journal of the Society of Toxicology",
issn = "1096-0929",
publisher = "Oxford University Press",

}

RIS

TY - JOUR

T1 - A survey of systematic evidence mapping practice and the case for knowledge graphs in environmental health & toxicology

AU - Wolffe, Taylor

AU - Vidler, John

AU - Halsall, Crispin

AU - Hunt, Neil

AU - Whaley, Paul

PY - 2020/2/25

Y1 - 2020/2/25

N2 - Systematic evidence mapping offers a robust and transparent methodology for facilitating evidence-based approaches to decision-making in chemicals policy and wider environmental health. Interest in the methodology is growing; however, its application in environmental health is still novel. To facilitate the production of effective systematic evidence maps for environmental health use cases, we survey the successful application of evidence mapping in other fields where the methodology is more established. Focusing on issues of “data storage technology”, “data integrity”, “data accessibility”, and “transparency”, we characterise current evidence-mapping practice and critically review its potential value for environmental health contexts. We note that rigid, flat data tables and schema-first approaches dominate current mapping methods and highlight how this practice is ill-suited to the highly connected, heterogeneous and complex nature of environmental health data. We propose this challenge is overcome by storing and structuring data as “knowledge graphs”. Knowledge graphs offer a flexible, schemaless and scalable model for systematically mapping the environmental health literature. Associated technologies such as ontologies are well-suited to the long-term goals of systematic mapping methodology in promoting resource-efficient access to the wider environmental health evidence base. Several graph storage implementations are readily available, with a variety of proven use cases in other fields. Thus, developing and adapting systematic evidence mapping for environmental health should utilise these graph-based resources to ensure the production of scalable, interoperable and robust maps to aid decision-making processes in chemicals policy and wider environmental health.

AB - Systematic evidence mapping offers a robust and transparent methodology for facilitating evidence-based approaches to decision-making in chemicals policy and wider environmental health. Interest in the methodology is growing; however, its application in environmental health is still novel. To facilitate the production of effective systematic evidence maps for environmental health use cases, we survey the successful application of evidence mapping in other fields where the methodology is more established. Focusing on issues of “data storage technology”, “data integrity”, “data accessibility”, and “transparency”, we characterise current evidence-mapping practice and critically review its potential value for environmental health contexts. We note that rigid, flat data tables and schema-first approaches dominate current mapping methods and highlight how this practice is ill-suited to the highly connected, heterogeneous and complex nature of environmental health data. We propose this challenge is overcome by storing and structuring data as “knowledge graphs”. Knowledge graphs offer a flexible, schemaless and scalable model for systematically mapping the environmental health literature. Associated technologies such as ontologies are well-suited to the long-term goals of systematic mapping methodology in promoting resource-efficient access to the wider environmental health evidence base. Several graph storage implementations are readily available, with a variety of proven use cases in other fields. Thus, developing and adapting systematic evidence mapping for environmental health should utilise these graph-based resources to ensure the production of scalable, interoperable and robust maps to aid decision-making processes in chemicals policy and wider environmental health.

KW - systematic evidence map

KW - knowledge graph

U2 - 10.1093/toxsci/kfaa025

DO - 10.1093/toxsci/kfaa025

M3 - Journal article

JO - Toxicological sciences : an official journal of the Society of Toxicology

JF - Toxicological sciences : an official journal of the Society of Toxicology

SN - 1096-0929

ER -