Articles producció científica> Química Física i Inorgànica

Chemical reaction network knowledge graphs: the OntoRXN ontology

  • Identification data

    Identifier: imarina:9264773
    Authors:
    Garay-Ruiz DBo C
    Abstract:
    The organization and management of large amounts of data has become a major point in almost all areas of human knowledge. In this context, semantic approaches propose a structure for the target data, defining ontologies that state the types of entities on a certain field and how these entities are interrelated. In this work, we introduce OntoRXN, a novel ontology describing the reaction networks constructed from computational chemistry calculations. Under our paradigm, these networks are handled as undirected graphs, without assuming any traversal direction. From there, we propose a core class structure including reaction steps, network stages, chemical species, and the lower-level entities for the individual computational calculations. These individual calculations are founded on the OntoCompChem ontology and on the ioChem-BD database, where information is parsed and stored in CML format. OntoRXN is introduced through several examples in which knowledge graphs based on the ontology are generated for different chemical systems available on ioChem-BD. Finally, the resulting knowledge graphs are explored through SPARQL queries, illustrating the power of the semantic approach to standardize the analysis of intricate datasets and to simplify the development of complex workflows.© 2022. The Author(s).
  • Others:

    Author, as appears in the article.: Garay-Ruiz D; Bo C
    Department: Química Física i Inorgànica
    URV's Author/s: Bo Jané, Carles / Garay Ruiz, Diego
    Keywords: World-wide-web Semantics Reactivity Reaction networks Ontologies xml span model semantics reactivity reaction networks markup entities
    Abstract: The organization and management of large amounts of data has become a major point in almost all areas of human knowledge. In this context, semantic approaches propose a structure for the target data, defining ontologies that state the types of entities on a certain field and how these entities are interrelated. In this work, we introduce OntoRXN, a novel ontology describing the reaction networks constructed from computational chemistry calculations. Under our paradigm, these networks are handled as undirected graphs, without assuming any traversal direction. From there, we propose a core class structure including reaction steps, network stages, chemical species, and the lower-level entities for the individual computational calculations. These individual calculations are founded on the OntoCompChem ontology and on the ioChem-BD database, where information is parsed and stored in CML format. OntoRXN is introduced through several examples in which knowledge graphs based on the ontology are generated for different chemical systems available on ioChem-BD. Finally, the resulting knowledge graphs are explored through SPARQL queries, illustrating the power of the semantic approach to standardize the analysis of intricate datasets and to simplify the development of complex workflows.© 2022. The Author(s).
    Thematic Areas: Química Physical and theoretical chemistry Library and information sciences Computer science, interdisciplinary applications Computer science, information systems Computer science applications Computer graphics and computer-aided design Ciencias sociales Chemistry, multidisciplinary Biotecnología
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: carles.bo@urv.cat diego.garay@estudiants.urv.cat
    Author identifier: 0000-0001-9581-2922
    Record's date: 2024-09-07
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://jcheminf.biomedcentral.com/articles/10.1186/s13321-022-00610-x
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Journal Of Cheminformatics. 14 (1): 29-29
    APA: Garay-Ruiz D; Bo C (2022). Chemical reaction network knowledge graphs: the OntoRXN ontology. Journal Of Cheminformatics, 14(1), 29-29. DOI: 10.1186/s13321-022-00610-x
    Article's DOI: 10.1186/s13321-022-00610-x
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2022
    Publication Type: Journal Publications
  • Keywords:

    Chemistry, Multidisciplinary,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Science, Information Systems,Computer Science, Interdisciplinary Applications,Library and Information Sciences,Physical and Theoretical Chemistry
    World-wide-web
    Semantics
    Reactivity
    Reaction networks
    Ontologies
    xml
    span model
    semantics
    reactivity
    reaction networks
    markup
    entities
    Química
    Physical and theoretical chemistry
    Library and information sciences
    Computer science, interdisciplinary applications
    Computer science, information systems
    Computer science applications
    Computer graphics and computer-aided design
    Ciencias sociales
    Chemistry, multidisciplinary
    Biotecnología
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