{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:42:49Z","timestamp":1792788169831,"version":"4.5.0"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:00:00Z","timestamp":1781827200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:00:00Z","timestamp":1781827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["825575"],"award-info":[{"award-number":["825575"]}]},{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["825575"],"award-info":[{"award-number":["825575"]}]},{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["825575"],"award-info":[{"award-number":["825575"]}]},{"name":"European Union\u2019s Horizon 2020 research and innovation programme","award":["825575"],"award-info":[{"award-number":["825575"]}]},{"name":"ELIXIR","id":[{"id":"https:\/\/ror.org\/044rwnt51","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Innovative Health Initiative Joint Undertaking","award":["101132943"],"award-info":[{"award-number":["101132943"]}],"id":[{"id":"https:\/\/ror.org\/04afqts81","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Innovative Health Initiative Joint Undertaking","award":["101172872"],"award-info":[{"award-number":["101172872"]}],"id":[{"id":"https:\/\/ror.org\/04afqts81","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Innovative Health Initiative Joint Undertaking","award":["101132943"],"award-info":[{"award-number":["101132943"]}],"id":[{"id":"https:\/\/ror.org\/04afqts81","id-type":"ROR","asserted-by":"crossref"}]},{"name":"UK Research and Innovation","award":["10105921"],"award-info":[{"award-number":["10105921"]}],"id":[{"id":"https:\/\/ror.org\/001aqnf71","id-type":"ROR","asserted-by":"crossref"}]},{"name":"UK Research and Innovation","award":["10105921"],"award-info":[{"award-number":["10105921"]}],"id":[{"id":"https:\/\/ror.org\/001aqnf71","id-type":"ROR","asserted-by":"crossref"}]},{"name":"European Union\u2019s Horizon Europe research and innovation programme","award":["101156595"],"award-info":[{"award-number":["101156595"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Biomed Semant"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>One pillar of FAIR principles adoption is Reusability by machines to enable for example more efficient data analytics in fields such as Bioinformatics. However, it is not clear to what extent current metadata exposed by datasets and tools in common repositories enable this. In practice, metadata often lacks in machine actionability due to incomplete standardised metadata and lack of ontological descriptions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this work, we identified minimal metadata that is needed to improve the machine actionability of bioinformatics tools and proposed a schema to address current limitations. The schema consists of metadata properties for the identification, selection, validation, and execution of tools. We also aligned this metadata to the metadata of datasets, in order to improve their integration for analytics by machines.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The identified minimal metadata improves the machine actionability of tools and data, and can be incorporated into platforms for tool and data sharing, and in FAIR infrastructures.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13326-026-00354-9","type":"journal-article","created":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T10:39:09Z","timestamp":1781865549000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FAIR in practice: minimum metadata schema for bioinformatics analytics by machines"],"prefix":"10.1186","volume":"17","author":[{"given":"Daphne","family":"Wijnbergen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"N\u00faria","family":"Queralt-Rosinach","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Val\u00e9rie","family":"Barbi\u00e9","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emma","family":"Verkinderen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nirupama","family":"Benis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annika","family":"Jacobsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter A. C.","family":"\u2019t Hoen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudio","family":"Carta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Roos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eleni","family":"Mina","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,19]]},"reference":[{"key":"354_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2016.18","volume":"3","author":"MD Wilkinson","year":"2016","unstructured":"Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. Comment: The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016;3:1\u20139. https:\/\/doi.org\/10.1038\/sdata.2016.18.","journal-title":"Sci Data"},{"key":"354_CR2","unstructured":"van der Horst E, Kaliyaperumal R, Tatum Z, Thompson M, Schultes E, Mina E et al. Finding novel associations across domains using linked data: a case study on genetic variants disrupting transcription start sites."},{"key":"354_CR3","doi-asserted-by":"publisher","unstructured":"Liao X, Niehues A, de Visser C, Huang J, Doornbos C, Ederveen THA et al. FAIR data cube, a FAIR data infrastructure for integrated multi-omics data analysis. 2023;:2023.04.23.23289000. https:\/\/doi.org\/10.1101\/2023.04.23.23289000","DOI":"10.1101\/2023.04.23.23289000"},{"key":"354_CR4","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1186\/s13023-022-02558-5","volume":"17","author":"B dos Santos Vieira","year":"2022","unstructured":"dos Santos Vieira B, Bernab\u00e9 CH, Zhang S, Abaza H, Benis N, C\u00e1mara A, et al. Towards FAIRification of sensitive and fragmented rare disease patient data: challenges and solutions in European reference network registries. Orphanet J Rare Dis. 2022;17:436. https:\/\/doi.org\/10.1186\/s13023-022-02558-5.","journal-title":"Orphanet J Rare Dis"},{"key":"354_CR5","doi-asserted-by":"publisher","first-page":"e407","DOI":"10.1016\/S2468-2667(24)00073-2","volume":"9","author":"B Herre","year":"2024","unstructured":"Herre B, Rod\u00e9s-Guirao L, Mathieu E, Ritchie H, Giattino C, Hasell J, et al. Best practices for government agencies to publish data: lessons from COVID-19. Lancet Public Health. 2024;9:e407\u201310. https:\/\/doi.org\/10.1016\/S2468-2667(24)00073-2.","journal-title":"Lancet Public Health"},{"key":"354_CR6","doi-asserted-by":"publisher","first-page":"e214","DOI":"10.1017\/cts.2023.619","volume":"7","author":"K Fecho","year":"2023","unstructured":"Fecho K, Bizon C, Issabekova T, Moxon S, Thessen AE, Abdollahi S, et al. An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges. J Clin Transl Sci. 2023;7:e214. https:\/\/doi.org\/10.1017\/cts.2023.619.","journal-title":"J Clin Transl Sci"},{"key":"354_CR7","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-023-02028-y","author":"V Tour\u00e9","year":"2023","unstructured":"Tour\u00e9 V, Krauss P, Gnodtke K, Buchhorn J, Unni D, Horki P, et al. Sci Data. 2023;10:127. https:\/\/doi.org\/10.1038\/s41597-023-02028-y. FAIRification of health-related data using semantic web technologies in the Swiss Personalized Health Network."},{"key":"354_CR8","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/s13326-022-00264-6","volume":"13","author":"R Kaliyaperumal","year":"2022","unstructured":"Kaliyaperumal R, Wilkinson MD, Moreno PA, Benis N, Cornet R, dos Santos Vieira B, et al. Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data. J Biomed Semant. 2022;13:9. https:\/\/doi.org\/10.1186\/s13326-022-00264-6.","journal-title":"J Biomed Semant"},{"key":"354_CR9","unstructured":"Metadata for EJP rare disease patient registries, biobanks and catalogs. 2024. https:\/\/github.com\/ejp-rd-vp\/resource-metadata-schema"},{"key":"354_CR10","unstructured":"da Silva Santos LB, Burger K, Kaliyaperumal R. FAIR data train specifications. 2023. https:\/\/specs.fairdatatrain.org\/. Accessed 19 Feb 2025."},{"key":"354_CR11","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/s12551-018-0490-8","volume":"11","author":"Z Wang","year":"2019","unstructured":"Wang Z, Lachmann A, Ma\u2019ayan A. Mining data and metadata from the gene expression omnibus. Biophys Rev. 2019;11:103\u201310. https:\/\/doi.org\/10.1007\/s12551-018-0490-8.","journal-title":"Biophys Rev"},{"key":"354_CR12","doi-asserted-by":"publisher","first-page":"baab006","DOI":"10.1093\/database\/baab006","volume":"2021","author":"N Lim","year":"2021","unstructured":"Lim N, Tesar S, Belmadani M, Poirier-Morency G, Mancarci BO, Sicherman J, et al. Curation of over 10 000 transcriptomic studies to enable data reuse. Database. 2021;2021:baab006. https:\/\/doi.org\/10.1093\/database\/baab006.","journal-title":"Database"},{"key":"354_CR13","doi-asserted-by":"publisher","first-page":"e0213090","DOI":"10.1371\/journal.pone.0213090","volume":"14","author":"S Carbon","year":"2019","unstructured":"Carbon S, Champieux R, McMurry JA, Winfree L, Wyatt LR, Haendel MA. An analysis and metric of reusable data licensing practices for biomedical resources. PLoS ONE. 2019;14:e0213090. https:\/\/doi.org\/10.1371\/journal.pone.0213090.","journal-title":"PLoS ONE"},{"key":"354_CR14","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1038\/s41597-022-01710-x","volume":"9","author":"M Barker","year":"2022","unstructured":"Barker M, Chue Hong NP, Katz DS, Lamprecht A-L, Martinez-Ortiz C, Psomopoulos F, et al. Introducing the FAIR Principles for research software. Sci Data. 2022;9:622. https:\/\/doi.org\/10.1038\/s41597-022-01710-x.","journal-title":"Sci Data"},{"key":"354_CR15","doi-asserted-by":"publisher","unstructured":"Chue Hong NP, Katz DS, Barker M, Lamprecht A-L, Martinez C, Psomopoulos FE et al. FAIR principles for research software (FAIR4RS Principles). 2022. https:\/\/doi.org\/10.15497\/RDA00068","DOI":"10.15497\/RDA00068"},{"key":"354_CR16","doi-asserted-by":"publisher","first-page":"e1011369","DOI":"10.1371\/journal.pcbi.1011369","volume":"19","author":"C de Visser","year":"2023","unstructured":"de Visser C, Johansson LF, Kulkarni P, Mei H, Neerincx P, van der Velde KJ, et al. Ten quick tips for building FAIR workflows. PLOS Comput Biol. 2023;19:e1011369. https:\/\/doi.org\/10.1371\/journal.pcbi.1011369.","journal-title":"PLOS Comput Biol"},{"key":"354_CR17","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1145\/3486897","volume":"65","author":"MR Crusoe","year":"2022","unstructured":"Crusoe MR, Abeln S, Iosup A, Amstutz P, Chilton J, Tijani\u0107 N, et al. Methods Included: Standardizing Computational Reuse and Portability with the Common Workflow Language. Commun ACM. 2022;65:54\u201363. https:\/\/doi.org\/10.1145\/3486897.","journal-title":"Commun ACM"},{"key":"354_CR18","doi-asserted-by":"publisher","unstructured":"Gustafsson OJR, Wilkinson SR, Bacall F, Pireddu L, Soiland-Reyes S, Leo S et al. WorkflowHub: a registry for computational workflows. 2024. https:\/\/doi.org\/10.48550\/arXiv.2410.06941","DOI":"10.48550\/arXiv.2410.06941"},{"key":"354_CR19","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1186\/s13023-024-03526-x","volume":"20","author":"D Wijnbergen","year":"2025","unstructured":"Wijnbergen D, Johari M, Ozisik O, \u2018t Hoen PAC, Ehrhart F, Baudot A, et al. Multi-omics analysis in inclusion body myositis identifies mir-16 responsible for HLA overexpression. Orphanet J Rare Dis. 2025;20:27. https:\/\/doi.org\/10.1186\/s13023-024-03526-x.","journal-title":"Orphanet J Rare Dis"},{"key":"354_CR20","doi-asserted-by":"publisher","unstructured":"Wijnbergen D, Johari M, Udd B, Roos M, Mina E. Inclusion body myositis active subnetwork identification workflow. 2024. https:\/\/doi.org\/10.48546\/WORKFLOWHUB.WORKFLOW.681.7","DOI":"10.48546\/WORKFLOWHUB.WORKFLOW.681.7"},{"key":"354_CR21","unstructured":"codemeta\/crosswalk.csv at master \u00b7 codemeta\/codemeta. https:\/\/github.com\/codemeta\/codemeta\/blob\/master\/crosswalk.csv. Accessed 21 Jan 2025."},{"key":"354_CR22","unstructured":"The CodeMeta Project. https:\/\/codemeta.github.io\/. Accessed 21 Jan 2025."},{"key":"354_CR23","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1186\/s13059-019-1772-6","volume":"20","author":"J Ison","year":"2019","unstructured":"Ison J, Ienasescu H, Chmura P, Rydza E, M\u00e9nager H, Kala\u0161 M, et al. The bio.tools registry of software tools and data resources for the life sciences. Genome Biol. 2019;20:164. https:\/\/doi.org\/10.1186\/s13059-019-1772-6.","journal-title":"Genome Biol"},{"key":"354_CR24","unstructured":"R Core Team. R: a language and environment for statistical computing."},{"key":"354_CR25","doi-asserted-by":"publisher","first-page":"R80","DOI":"10.1186\/gb-2004-5-10-r80","volume":"5","author":"RC Gentleman","year":"2004","unstructured":"Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5:R80. https:\/\/doi.org\/10.1186\/gb-2004-5-10-r80.","journal-title":"Genome Biol"},{"key":"354_CR26","unstructured":"Rare Diseases Community | ELIXIR. https:\/\/elixir-europe.org\/communities\/rare-diseases. Accessed 20 Feb 2025."},{"key":"354_CR27","unstructured":"EJP, RD \u2013 European Joint Programme on Rare Diseases. https:\/\/www.ejprarediseases.org\/. Accessed 20 Feb 2025."},{"key":"354_CR28","doi-asserted-by":"publisher","first-page":"e47","DOI":"10.1093\/nar\/gkv007","volume":"43","author":"ME Ritchie","year":"2015","unstructured":"Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43:e47. https:\/\/doi.org\/10.1093\/nar\/gkv007.","journal-title":"Nucleic Acids Res"},{"key":"354_CR29","doi-asserted-by":"publisher","first-page":"W93","DOI":"10.1093\/nar\/gkz437","volume":"47","author":"A Renaux","year":"2019","unstructured":"Renaux A, Papadimitriou S, Versbraegen N, Nachtegael C, Boutry S, Now\u00e9 A, et al. ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations. Nucleic Acids Res. 2019;47:W93\u20138. https:\/\/doi.org\/10.1093\/nar\/gkz437.","journal-title":"Nucleic Acids Res"},{"key":"354_CR30","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1186\/s12859-022-04828-2","volume":"23","author":"O Ozisik","year":"2022","unstructured":"Ozisik O, T\u00e9r\u00e9zol M, Baudot A. orsum: a Python package for filtering and comparing enrichment analyses using a simple principle. BMC Bioinformatics. 2022;23:293. https:\/\/doi.org\/10.1186\/s12859-022-04828-2.","journal-title":"BMC Bioinformatics"},{"key":"354_CR31","doi-asserted-by":"publisher","first-page":"2595","DOI":"10.1093\/bioinformatics\/btac146","volume":"38","author":"E Pasche","year":"2022","unstructured":"Pasche E, Mottaz A, Caucheteur D, Gobeill J, Michel P-A, Ruch P. Variomes: a high recall search engine to support the curation of genomic variants. Bioinformatics. 2022;38:2595\u2013601. https:\/\/doi.org\/10.1093\/bioinformatics\/btac146.","journal-title":"Bioinformatics"},{"key":"354_CR32","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1002\/humu.24353","volume":"43","author":"S Laurie","year":"2022","unstructured":"Laurie S, Piscia D, Matalonga L, Corv\u00f3 A, Fern\u00e1ndez-Callejo M, Garcia-Linares C, et al. The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases. Hum Mutat. 2022;43:717\u201333. https:\/\/doi.org\/10.1002\/humu.24353.","journal-title":"Hum Mutat"},{"key":"354_CR33","doi-asserted-by":"publisher","first-page":"e1009263","DOI":"10.1371\/journal.pcbi.1009263","volume":"17","author":"EM Novoa-del-Toro","year":"2021","unstructured":"Novoa-del-Toro EM, Mezura-Montes E, Vignes M, T\u00e9r\u00e9zol M, Magdinier F, Tichit L, et al. A multi-objective genetic algorithm to find active modules in multiplex biological networks. PLOS Comput Biol. 2021;17:e1009263. https:\/\/doi.org\/10.1371\/journal.pcbi.1009263.","journal-title":"PLOS Comput Biol"},{"key":"354_CR34","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1186\/1471-2105-11-5","volume":"11","author":"MP van Iersel","year":"2010","unstructured":"van Iersel MP, Pico AR, Kelder T, Gao J, Ho I, Hanspers K, et al. The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services. BMC Bioinformatics. 2010;11:5. https:\/\/doi.org\/10.1186\/1471-2105-11-5.","journal-title":"BMC Bioinformatics"},{"key":"354_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13059-016-0974-4","volume":"17","author":"W McLaren","year":"2016","unstructured":"McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GRS, Thormann A, et al. The Ensembl Variant Effect Predictor. Genome Biol. 2016;17:1\u201314. https:\/\/doi.org\/10.1186\/s13059-016-0974-4.","journal-title":"Genome Biol"},{"key":"354_CR36","doi-asserted-by":"publisher","first-page":"e1004085","DOI":"10.1371\/journal.pcbi.1004085","volume":"11","author":"M Kutmon","year":"2015","unstructured":"Kutmon M, van Iersel MP, Bohler A, Kelder T, Nunes N, Pico AR, et al. PathVisio 3: An Extendable Pathway Analysis Toolbox. PLOS Comput Biol. 2015;11:e1004085. https:\/\/doi.org\/10.1371\/journal.pcbi.1004085.","journal-title":"PLOS Comput Biol"},{"key":"354_CR37","doi-asserted-by":"publisher","first-page":"2855","DOI":"10.1093\/bioinformatics\/btp515","volume":"25","author":"K-A L\u00ea Cao","year":"2009","unstructured":"L\u00ea Cao K-A, Gonz\u00e1lez I, D\u00e9jean S. integrOmics: an R package to unravel relationships between two omics datasets. Bioinformatics. 2009;25:2855\u20136. https:\/\/doi.org\/10.1093\/bioinformatics\/btp515.","journal-title":"Bioinformatics"},{"key":"354_CR38","unstructured":"L\u00ea Cao K-A, Rohart F, Gonzalez I, Dejean S. mixOmics: Omics data integration project. R package version 6.1.1. 2016."},{"key":"354_CR39","doi-asserted-by":"publisher","first-page":"101701","DOI":"10.1016\/j.softx.2024.101701","volume":"26","author":"M T\u00e9r\u00e9zol","year":"2024","unstructured":"T\u00e9r\u00e9zol M, Baudot A, Ozisik O, ODAMNet. A python package to identify molecular relationships between chemicals and rare diseases using overlap, active module and random walk approaches. SoftwareX. 2024;26:101701. https:\/\/doi.org\/10.1016\/j.softx.2024.101701.","journal-title":"SoftwareX"},{"key":"354_CR40","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1093\/bioinformatics\/btr709","volume":"28","author":"R Kolde","year":"2012","unstructured":"Kolde R, Laur S, Adler P, Vilo J. Robust rank aggregation for gene list integration and meta-analysis. Bioinformatics. 2012;28:573\u201380. https:\/\/doi.org\/10.1093\/bioinformatics\/btr709.","journal-title":"Bioinformatics"},{"key":"354_CR41","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1186\/s13059-014-0550-8","volume":"15","author":"MI Love","year":"2014","unstructured":"Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. https:\/\/doi.org\/10.1186\/s13059-014-0550-8.","journal-title":"Genome Biol"},{"key":"354_CR42","doi-asserted-by":"publisher","DOI":"10.1162\/dint_a_00160","author":"LOB da Silva Santos","year":"2023","unstructured":"da Silva Santos LOB, Burger K, Kaliyaperumal R, Wilkinson MD. Data Intell. 2023;5:163\u201383. https:\/\/doi.org\/10.1162\/dint_a_00160. FAIR Data Point: A FAIR-Oriented Approach for Metadata Publication."},{"key":"354_CR43","doi-asserted-by":"publisher","first-page":"D1255","DOI":"10.1093\/nar\/gkab1063","volume":"50","author":"LM Schriml","year":"2022","unstructured":"Schriml LM, Munro JB, Schor M, Olley D, McCracken C, Felix V, et al. The Human Disease Ontology 2022 update. Nucleic Acids Res. 2022;50:D1255\u201361. https:\/\/doi.org\/10.1093\/nar\/gkab1063.","journal-title":"Nucleic Acids Res"},{"key":"354_CR44","doi-asserted-by":"publisher","unstructured":"Black M, Lamothe L, Eldakroury H, Kierkegaard M, Priya A, Machinda A et al. EDAM: the bioscientific data analysis ontology (update 2021). F1000Research. 2022;11. https:\/\/doi.org\/10.7490\/f1000research.1118900.1","DOI":"10.7490\/f1000research.1118900.1"},{"key":"354_CR45","unstructured":"Albertoni R, Browning D, Cox S, Gonzalez Beltran A, Perego A, Winstanley P et al. Data Catalog Vocabulary (DCAT) - Version 2. 2020. https:\/\/www.w3.org\/TR\/vocab-dcat-2\/. Accessed 10 Feb 2023."},{"key":"354_CR46","unstructured":"Vasant D, Chanas L, Malone J, Hanauer M, Olry A, Jupp S et al. ORDO: An ontology connecting rare disease, epidemiology and genetic data. 2014."}],"container-title":["Journal of Biomedical Semantics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13326-026-00354-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13326-026-00354-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13326-026-00354-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:27:32Z","timestamp":1790036852000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s13326-026-00354-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,19]]},"references-count":46,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["354"],"URL":"https:\/\/doi.org\/10.1186\/s13326-026-00354-9","relation":{"references":[{"id-type":"doi","id":"10.1038\/s41597-023-02028-y","asserted-by":"subject"},{"id-type":"doi","id":"10.1162\/dint_a_00160","asserted-by":"subject"}],"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-6396831\/v1","asserted-by":"object"}]},"ISSN":["2041-1480"],"issn-type":[{"value":"2041-1480","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,19]]},"assertion":[{"value":"7 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 April 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"11"}}