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Ontology-Based Data Pipeline for Semantic Reaction Classification and Research Data Management

Tallennettuna:
Julkaisussa:Computers vol. 14, no. 8 (2025), p. 311-326
Päätekijä: Borgelt Hendrik
Muut tekijät: Kitel, Frederick Gabriel, Kockmann Norbert
Julkaistu:
MDPI AG
Aiheet:
Research data management
Data management
Terminology
Semantics
Metadata
Application programming interface
Classification
Ontology
Databases
Experiments
Knowledge
Chemical reactions
Oxidation
Catalysis
Functional groups
Machine learning
Knowledge representation
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Abstrakti:Catalysis research is complex and interdisciplinary, involving diverse physical effects and challenging data practices. Research data often captures only selected aspects, such as specific reactants and products, limiting its utility for machine learning and the implementation of FAIR (Findable, Accessible, Interoperable, Reusable) workflows. To improve this, semantic structuring through ontologies is essential. This work extends the established ontologies by refining logical relations and integrating semantic tools such as the Web Ontology Language or the Shape Constraint Language. It incorporates application programming interfaces from chemical databases, such as the Kyoto Encyclopedia of Genes and Genomes and the National Institute of Health’s PubChem database, and builds upon established ontologies. A key innovation lies in automatically decomposing chemical substances through database entries and chemical identifier representations to identify functional groups, enabling more generalized reaction classification. Using new semantic functionality, functional groups are flexibly addressed, improving the classification of reactions such as saponification and ester cleavage with simultaneous oxidation. A graphical interface (GUI) supports user interaction with the knowledge graph, enabling ontological reasoning and querying. This approach demonstrates improved specificity of the newly established ontology over its predecessors and offers a more user-friendly interface for engaging with structured chemical knowledge. Future work will focus on expanding ontology coverage to support a wider range of reactions in catalysis research.
ISSN:2073-431X
DOI:10.3390/computers14080311
Lähde:Advanced Technologies & Aerospace Database