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The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products

Open access
Dionisio, Kathie L., Phillips, Katherine, Price, Paul S., Grulke, Christopher M., Williams, Antony, Biryol, Derya, Hong, Tao, Isaacs, Kristin K.·2018·Scientific Data

Abstract

Quantitative data on product chemical composition is a necessary parameter for characterizing near-field exposure. This data set comprises reported and predicted information on more than 75,000 chemicals and more than 15,000 consumer products. The data’s primary intended use is for exposure, risk, and safety assessments. The data set includes specific products with quantitative or qualitative ingredient information, which has been publicly disclosed through material safety data sheets (MSDS) and ingredient lists. A single product category from a refined and harmonized set of categories has been assigned to each product. The data set also contains information on the functional role of chemicals in products, which can inform predictions of the concentrations in which they occur. These data will be useful to exposure and risk assessors evaluating chemical and product safety.

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Metadata

Authors
Dionisio, K. L., Phillips, K., Price, P. S., Grulke, C. M., Williams, A., Biryol, D., Hong, T., & Isaacs, K. K.
Venue
Scientific Data
Published
2018-07-10
Volume
5
Issue
1
Pages
180125-180125
ISSN
2052-4463 (ISSN-L)
OpenAlex
W2811996766
Cited by
262
References
0
Type
data paper
Language
en
Open access
gold

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CoChat. (2026). Citation check: The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products. https://app.cochat.ai/papers/10.1038/sdata.2018.125
The paper
Dionisio, K. L., Phillips, K., Price, P. S., Grulke, C. M., Williams, A., Biryol, D., Hong, T., & Isaacs, K. K. (2018). The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products. Scientific Data. https://doi.org/10.1038/sdata.2018.125

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.