{"id":"https://openalex.org/W4414898447","doi":"https://doi.org/10.1109/escience65000.2025.00090","title":"Improving FAIR Compliance for High-Dimensional Data via Automated Metadata Extraction","display_name":"Improving FAIR Compliance for High-Dimensional Data via Automated Metadata Extraction","publication_year":2025,"publication_date":"2025-09-15","ids":{"openalex":"https://openalex.org/W4414898447","doi":"https://doi.org/10.1109/escience65000.2025.00090"},"language":"en","primary_location":{"id":"doi:10.1109/escience65000.2025.00090","doi":"https://doi.org/10.1109/escience65000.2025.00090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/escience65000.2025.00090","pdf_url":null,"source":{"id":"https://openalex.org/S4306418677","display_name":"IEEE International Conference on eScience","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on eScience (eScience)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114375346","display_name":"Ana Tri\u0161ovi\u0107","orcid":"https://orcid.org/0000-0003-1991-0533","observed_orcids":["https://orcid.org/0000-0003-1991-0533"]},"institutions":[{"id":"https://openalex.org/I4405258931","display_name":"MIT Computer Science and Artificial Intelligence Laboratory","ror":"https://ror.org/01e85r662","country_code":"US","type":"facility","lineage":["https://openalex.org/I4405258931","https://openalex.org/I63966007"]},{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ana Tri\u0161ovi\u0107","raw_affiliation_strings":["MIT Computer Science and Artificial Intelligence Laboratory,Cambridge,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT Computer Science and Artificial Intelligence Laboratory,Cambridge,USA","institution_ids":["https://openalex.org/I4405258931","https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055182924","display_name":"Jan Range","orcid":"https://orcid.org/0000-0001-6478-1051","observed_orcids":["https://orcid.org/0000-0001-6478-1051"]},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]},{"id":"https://openalex.org/I4405268297","display_name":"Stuttgart Center for Simulation Science","ror":"https://ror.org/00ft66751","country_code":"DE","type":"education","lineage":["https://openalex.org/I4405268297"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jan Range","raw_affiliation_strings":["University of Stuttgart,Cluster of Excellence SimTech,Stuttgart,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Stuttgart,Cluster of Excellence SimTech,Stuttgart,Germany","institution_ids":["https://openalex.org/I100066346","https://openalex.org/I4405268297"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082375012","display_name":"Philip Durbin","orcid":"https://orcid.org/0000-0002-9528-9470","observed_orcids":["https://orcid.org/0000-0002-9528-9470"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Durbin","raw_affiliation_strings":["Harvard University,Institute for Quantitative Social Science,Cambridge,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University,Institute for Quantitative Social Science,Cambridge,USA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073484807","display_name":"Amber Leahey","orcid":"https://orcid.org/0000-0001-6476-223X","observed_orcids":["https://orcid.org/0000-0001-6476-223X"]},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Amber Leahey","raw_affiliation_strings":["University of Toronto Libraries University of Toronto,Toronto,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto Libraries University of Toronto,Toronto,Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100318012","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7547-2908","observed_orcids":["https://orcid.org/0000-0001-7547-2908"]},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Xidian University,School of Mathematics and Statistics,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Mathematics and Statistics,Xi’an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048337523","display_name":"Danielle Braun","orcid":"https://orcid.org/0000-0002-5177-8598","observed_orcids":["https://orcid.org/0000-0002-5177-8598"]},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I4210117453","display_name":"Dana-Farber Cancer Institute","ror":"https://ror.org/02jzgtq86","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210117453"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danielle Braun","raw_affiliation_strings":["Harvard T. H. Chan School of Public Health Dana-Farber Cancer Institute,Department of Biostatistics,Boston,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard T. H. Chan School of Public Health Dana-Farber Cancer Institute,Department of Biostatistics,Boston,USA","institution_ids":["https://openalex.org/I136199984","https://openalex.org/I4210117453"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25992948,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"445","last_page":"451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11937","display_name":"Research Data Management Practices","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11937","display_name":"Research Data Management Practices","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.005100000184029341,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14201","display_name":"Data Analysis and Archiving","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fair-principles","display_name":"FAIR principles","score":0.9169999957084656},{"id":"https://openalex.org/keywords/high-dimensional-data","display_name":"high-dimensional data","score":0.878000020980835},{"id":"https://openalex.org/keywords/metadata-extraction","display_name":"metadata extraction","score":0.7730000019073486},{"id":"https://openalex.org/keywords/netcdf","display_name":"NetCDF","score":0.9589999914169312},{"id":"https://openalex.org/keywords/hdf5","display_name":"HDF5","score":1.0},{"id":"https://openalex.org/keywords/research-data-repositories","display_name":"research data repositories","score":0.734000027179718},{"id":"https://openalex.org/keywords/dataverse","display_name":"Dataverse","score":0.8050000071525574},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9449999928474426},{"id":"https://openalex.org/keywords/metadata-quality-assessment","display_name":"metadata quality assessment","score":0.7369999885559082},{"id":"https://openalex.org/keywords/data-findability","display_name":"data discoverability","score":0.6890000104904175}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.9398999810218811},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8123999834060669},{"id":"https://openalex.org/C153048206","wikidata":"https://www.wikidata.org/wiki/Q3454922","display_name":"Metadata repository","level":3,"score":0.659600019454956},{"id":"https://openalex.org/C136976847","wikidata":"https://www.wikidata.org/wiki/Q6822297","display_name":"Meta Data Services","level":4,"score":0.6269000172615051},{"id":"https://openalex.org/C110326360","wikidata":"https://www.wikidata.org/wiki/Q17149476","display_name":"Metadata modeling","level":4,"score":0.5820000171661377},{"id":"https://openalex.org/C30872290","wikidata":"https://www.wikidata.org/wiki/Q1172389","display_name":"Data element","level":3,"score":0.5277000069618225},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.5130000114440918},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49619999527931213},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.44449999928474426},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.41359999775886536},{"id":"https://openalex.org/C193150823","wikidata":"https://www.wikidata.org/wiki/Q1477538","display_name":"Geospatial metadata","level":5,"score":0.38929998874664307},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3882000148296356},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3871000111103058},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.34950000047683716},{"id":"https://openalex.org/C171730128","wikidata":"https://www.wikidata.org/wiki/Q5227290","display_name":"Data file","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.33000001311302185},{"id":"https://openalex.org/C2779489174","wikidata":"https://www.wikidata.org/wiki/Q6822246","display_name":"Metadata management","level":3,"score":0.3147999942302704},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C137314826","wikidata":"https://www.wikidata.org/wiki/Q2330408","display_name":"Data mapping","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C11090531","wikidata":"https://www.wikidata.org/wiki/Q1361922","display_name":"NetCDF","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C3102742","wikidata":"https://www.wikidata.org/wiki/Q6031177","display_name":"Information repository","level":3,"score":0.2619999945163727},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2533999979496002},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/escience65000.2025.00090","doi":"https://doi.org/10.1109/escience65000.2025.00090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/escience65000.2025.00090","pdf_url":null,"source":{"id":"https://openalex.org/S4306418677","display_name":"IEEE International Conference on eScience","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on eScience (eScience)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306151","display_name":"Alfred P. Sloan Foundation","ror":"https://ror.org/052csg198"},{"id":"https://openalex.org/F4320307764","display_name":"Microsoft","ror":"https://ror.org/00d0nc645"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1987822482","https://openalex.org/W2032756564","https://openalex.org/W2106721232","https://openalex.org/W2141297584","https://openalex.org/W2302501749","https://openalex.org/W2949033096","https://openalex.org/W2964386587","https://openalex.org/W2977341319","https://openalex.org/W2988998130","https://openalex.org/W3121991495","https://openalex.org/W3128940808","https://openalex.org/W4235633549","https://openalex.org/W4383710649","https://openalex.org/W4389520463","https://openalex.org/W4390947663","https://openalex.org/W4408233117","https://openalex.org/W4409500924"],"related_works":[],"abstract_inverted_index":{"High-dimensional":[0],"datasets":[1],"are":[2,126],"becoming":[3],"an":[4,104],"increasingly":[5],"vital":[6],"asset":[7],"in":[8,34],"the":[9,36,47,56,72,91,97,131],"machine":[10],"learning":[11],"and":[12,39,54,80,123],"AI":[13],"domains":[14],"due":[15],"to":[16,19,61,70,90,116],"their":[17],"ability":[18],"capture":[20],"large":[21,67],"volumes":[22],"of":[23,41,50,74,93],"structured,":[24],"self-descriptive":[25],"information.":[26],"Research":[27],"data":[28,133],"repositories":[29],"play":[30],"a":[31,66,113],"key":[32],"role":[33],"supporting":[35],"documentation,":[37],"discoverability,":[38],"reuse":[40],"such":[42],"data.":[43,119],"This":[44],"paper":[45],"highlights":[46],"growing":[48],"presence":[49],"high-dimensional":[51,118],"formats\u2014particularly":[52],"NetCDF":[53],"HDF5\u2014underscoring":[55],"need":[57],"for":[58],"better":[59],"infrastructure":[60],"support":[62],"them.":[63],"We":[64],"use":[65],"language":[68],"model":[69],"assess":[71],"quality":[73],"metadata":[75,84,95,106],"associated":[76],"with":[77,130],"these":[78],"files":[79,98],"find":[81],"that":[82],"user-provided":[83],"often":[85],"falls":[86],"short":[87],"when":[88],"compared":[89],"richness":[92],"embedded":[94],"within":[96],"themselves.":[99],"In":[100],"response,":[101],"we":[102],"implement":[103],"automated":[105],"extraction":[107],"process":[108],"during":[109],"file":[110],"ingestion,":[111],"offering":[112],"practical":[114],"pathway":[115],"FAIR-ify":[117],"Our":[120],"empirical":[121],"analysis":[122],"technical":[124],"solution":[125],"demonstrated":[127],"through":[128],"integration":[129],"Dataverse":[132],"repository":[134],"platform.":[135]},"counts_by_year":[],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2025-10-10T00:00:00"}