{"doi":"10.1515/pac-2021-2007","title":"Ontologies4Chem: the landscape of ontologies in chemistry","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>For a long time, databases such as CAS, Reaxys, PubChem or ChemSpider mostly rely on unique numerical identifiers or chemical structure identifiers like InChI, SMILES or others to link data across heterogeneous data sources. The retrospective processing of information and fragmented data from text publications to maintain these databases is a cumbersome process. Ontologies are a holistic approach to semantically describe data, information and knowledge of a domain. They provide terms, relations and logic to semantically annotate and link data building knowledge graphs. The application of standard taxonomies and vocabularies from the very beginning of data generation and along research workflows in electronic lab notebooks (ELNs), software tools, and their final publication in data repositories create FAIR data straightforwardly. Thus a proper semantic description of an investigation and the why, how, where, when, and by whom data was produced in conjunction with the description and representation of research data is a natural outcome in contrast to the retrospective processing of research publications as we know it. In this work we provide an overview of ontologies in chemistry suitable to represent concepts of research and research data. These ontologies are evaluated against several criteria derived from the FAIR data principles and their possible application in the digitisation of research data management workflows.</jats:p>","journal":"Pure and Applied Chemistry","year":2022,"id":591116,"datarank":1.7030718286920556,"base_score":3.9318256327243257,"endowment":3.9318256327243257,"self_citation_contribution":0.5897738449086489,"citation_network_contribution":1.1132979837834067,"self_endowment_contribution":0.5897738449086489,"citer_contribution":1.1132979837834067,"corpus_percentile":null,"corpus_rank":null,"citation_count":50,"citer_count":39,"citers_with_citation_signal":30,"citers_with_endowment":30,"datacite_reuse_total":2,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1512363,"name":"Johannes Hunold","orcid":"0000-0002-4378-6061","position":1,"is_corresponding":false},{"id":1512364,"name":"André Castro","orcid":"0000-0002-7839-3698","position":2,"is_corresponding":false},{"id":5924,"name":"Steffen Neumann","orcid":"0000-0002-7899-7192","position":3,"is_corresponding":false},{"id":1512366,"name":"Oliver Koepler","orcid":"0000-0003-3385-4232","position":4,"is_corresponding":false},{"id":27324,"name":"Philip Strömert","orcid":"0000-0002-1595-3213","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Ontologies4Chem: the landscape of ontologies in chemistry","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>For a long time, databases such as CAS, Reaxys, PubChem or ChemSpider mostly rely on unique numerical identifiers or chemical structure identifiers like InChI, SMILES or others to link data across heterogeneous data sources. The retrospective processing of information and fragmented data from text publications to maintain these databases is a cumbersome process. Ontologies are a holistic approach to semantically describe data, information and knowledge of a domain. They provide terms, relations and logic to semantically annotate and link data building knowledge graphs. The application of standard taxonomies and vocabularies from the very beginning of data generation and along research workflows in electronic lab notebooks (ELNs), software tools, and their final publication in data repositories create FAIR data straightforwardly. Thus a proper semantic description of an investigation and the why, how, where, when, and by whom data was produced in conjunction with the description and representation of research data is a natural outcome in contrast to the retrospective processing of research publications as we know it. In this work we provide an overview of ontologies in chemistry suitable to represent concepts of research and research data. These ontologies are evaluated against several criteria derived from the FAIR data principles and their possible application in the digitisation of research data management workflows.</jats:p>","is_dataset_classified":null,"base_score":3.9318256327243257,"endowment":3.9318256327243257,"datacite_reuse_total":2,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"20725694","pmcid":null,"openalex_id":"https://openalex.org/W4220791129","authors":[],"funders":[{"funder_name":"Deutsche Forschungsgemeinschaft","grant_id":"441958208","title":null},{"funder_name":"Deutsche Forschungsgemeinschaft","grant_id":"unidentified","title":"unidentified"}],"total_grants":2,"fwci":3.8613,"citation_percentile":0.94919974,"influential_citations":0,"citation_trend":[{"year":2022,"count":4},{"year":2023,"count":19},{"year":2024,"count":12},{"year":2025,"count":11},{"year":2026,"count":4}],"oa_status":"hybrid","license":"cc-by-nc-nd","oa_locations":[{"url":"https://www.degruyter.com/document/doi/10.1515/pac-2021-2007/pdf","host_type":"journal"},{"url":"https://www.degruyter.com/document/doi/10.1515/pac-2021-2007/pdf","host_type":"publisher"},{"url":"https://www.degruyter.com/document/doi/10.1515/pac-2021-2007/xml","host_type":"publisher"},{"url":"https://doi.org/10.1515/pac-2021-2007","host_type":"journal"},{"url":"https://dx.doi.org/10.34657/9161","host_type":""}],"fields_of_study":["Biomedical Text Mining and Ontologies","Research Data Management Practices","Semantic Web and Ontologies","0301 basic medicine","03 medical and health sciences"],"mesh_terms":[],"keywords":["Workflow","Computer science","Identifier","Information retrieval","PubChem","Data science","Domain (mathematical analysis)","Representation (politics)","External Data Representation","Cheminformatics","World Wide Web","Chemistry","Database","Artificial intelligence","FAIR data","terminology","linked data","ontology","540","research data"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Quality Education"}],"linked_datasets":[{"doi":"10.5281/zenodo.7049723","title":"Ontologies4Chem: Current chemical ontologies 4 research data management","publisher":"Zenodo","resource_type":"Text"},{"doi":"10.5281/zenodo.7049724","title":"Ontologies4Chem: Current chemical ontologies 4 research data management","publisher":"Zenodo","resource_type":"Text"}],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-25T14:27:17.843564Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}