A Compendium of Chemical Class and Use Type Open Access Databases

Niklas Heinemann, Sascha Bub, Jakob Wolfram, Sebastian Stehle, Lara L. Petschick and Ralf Schulz
Additional contact information
Niklas Heinemann: iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany
Sascha Bub: iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany
Jakob Wolfram: iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany
Sebastian Stehle: iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany
Lara L. Petschick: iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany
Ralf Schulz: iES Landau, Institute for Environmental Sciences, University of Koblenz-Landau, D-76829 Landau, Germany

Data, 2020, vol. 5, issue 4, 1-16

Abstract: With an ever-increasing production and registration of chemical substances, obtaining reliable and up to date information on their use types (UT) and chemical class (CC) is of crucial importance. We evaluated the current status of open access chemical substance databases (DBs) regarding UT and CC information using the “Meta-analysis of the Global Impact of Chemicals” (MAGIC) graph as a benchmark. A decision tree-based selection process was used to choose the most suitable out of 96 databases. To compare the DB content for 100 weighted, randomly selected chemical substances, an extensive quantitative and qualitative analysis was performed. It was found that four DBs yielded more qualitative and quantitative UT and CC results than the current MAGIC graph: The European Bioinformatics Institute DB, ChemSpider, the English Wikipedia page, and the National Center for Biotechnology Information (NCBI). The NCBI, along with its subsidiary DBs PubChem and Medical Subject Headings (MeSH), showed the best performance according to the defined criteria. To analyse large datasets, harmonisation of the available information might be beneficial, as the available DBs mostly aggregate information without harmonising them.

Keywords: ecotoxicology; graph database; environmental data; data harmonisation; chemical use types; chemical class; organic contaminants (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2306-5729/5/4/114/pdf (application/pdf)
https://www.mdpi.com/2306-5729/5/4/114/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jdataj:v:5:y:2020:i:4:p:114-:d:457205

Access Statistics for this article

Data is currently edited by Ms. Cecilia Yang

More articles in Data from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().