Big Data in Predictive Toxicology
CHAPTER 4: Organisation of Toxicological Data in Databases
Published:04 Dec 2019
Special Collection: 2019 ebook collectionSeries: Issues in Toxicology
D. Bower, K. Cross, and G. Myatt, in Big Data in Predictive Toxicology, ed. D. Neagu and A. Richarz, The Royal Society of Chemistry, 2019, pp. 108-165.
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There are a wide variety of established toxicity databases being routinely used to support hazard and risk assessment. The increasing number and size of toxicology databases and methods for automatically recording toxicology studies has led to a diverse series of formats for organisation of the information. Currently, such approaches span from simple one-to-one data exchange formats to complex formats incorporating semantic representations and data models covering additional information (such as experimental design, results and findings). Such developments support the volume, variety and value of (big) data and the transition from insular, isolated and simple structures to big data technologies for big toxicology data resources. This chapter reviews current solutions for the most known resources and identifies opportunities and gaps that such resources show in the era of big data. It covers a variety of approaches to data exchange and database design for organising toxicity and related data, highlights a number of databases with toxicity data as well as information on alternative approaches, and discusses project management and regulatory compliance databases. The chapter concludes with reflections on how these systems can integrate diverse toxicology-related data in preparation for the adoption of new big data technologies.