Chemical Species Ontology for Data Integration and Knowledge Discovery

Web ontologies are important tools in modern scientific research because they provide a standardized way to represent and manage web-scale amounts of complex data. In chemistry, a semantic database for chemical species is indispensable for its ability to interrelate and infer relationships, enabling...

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Bibliographic Details
Published in:Journal of chemical information and modeling 2023-11, Vol.63 (21), p.6569-6586
Main Authors: Pascazio, Laura, Rihm, Simon, Naseri, Ali, Mosbach, Sebastian, Akroyd, Jethro, Kraft, Markus
Format: Article
Language:English
Subjects:
Chemical Information
Data integration
Data management
Data search
Knowledge representation
Ontology
Physical properties
Semantics
Software agents
Task complexity
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Summary:Web ontologies are important tools in modern scientific research because they provide a standardized way to represent and manage web-scale amounts of complex data. In chemistry, a semantic database for chemical species is indispensable for its ability to interrelate and infer relationships, enabling a more precise analysis and prediction of chemical behavior. This paper presents OntoSpecies, a web ontology designed to represent chemical species and their properties. The ontology serves as a core component of The World Avatar knowledge graph chemistry domain and includes a wide range of identifiers, chemical and physical properties, chemical classifications and applications, and spectral information associated with each species. The ontology includes provenance and attribution metadata, ensuring the reliability and traceability of data. Most of the information about chemical species are sourced from PubChem and ChEBI data on the respective compound Web pages using a software agent, making OntoSpecies a comprehensive semantic database of chemical species able to solve novel types of problems in the field. Access to this reliable source of chemical data is provided through a SPARQL end point. The paper presents example use cases to demonstrate the contribution of OntoSpecies in solving complex tasks that require integrated semantically searchable chemical data. The approach presented in this paper represents a significant advancement in the field of chemical data management, offering a powerful tool for representing, navigating, and analyzing chemical information to support scientific research.
ISSN:1549-9596
1549-960X
DOI:10.1021/acs.jcim.3c00820