{"id":"https://openalex.org/W4406145277","doi":"https://doi.org/10.3389/fdata.2024.1476506","title":"Constructing a metadata knowledge graph as an atlas for demystifying AI pipeline optimization","display_name":"Constructing a metadata knowledge graph as an atlas for demystifying AI pipeline optimization","publication_year":2025,"publication_date":"2025-01-07","ids":{"openalex":"https://openalex.org/W4406145277","doi":"https://doi.org/10.3389/fdata.2024.1476506","pmid":"https://pubmed.ncbi.nlm.nih.gov/39839155"},"language":"en","primary_location":{"id":"doi:10.3389/fdata.2024.1476506","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1476506","pdf_url":"https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2024.1476506/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2024.1476506/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061795720","display_name":"Revathy Venkataramanan","orcid":"https://orcid.org/0000-0002-5642-3438"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]},{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Revathy Venkataramanan","raw_affiliation_strings":["AI Institute, University of South Carolina, Columbia, SC, United States","Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"AI Institute, University of South Carolina, Columbia, SC, United States","institution_ids":["https://openalex.org/I155781252"]},{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044171088","display_name":"Aalap Tripathy","orcid":"https://orcid.org/0000-0002-9046-6298"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aalap Tripathy","raw_affiliation_strings":["Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061190677","display_name":"Tarun Kumar","orcid":"https://orcid.org/0000-0001-6265-629X"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tarun Kumar","raw_affiliation_strings":["Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029590134","display_name":"Sergey Serebryakov","orcid":"https://orcid.org/0000-0001-6963-9337"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergey Serebryakov","raw_affiliation_strings":["Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108828884","display_name":"Annmary Justine","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Annmary Justine","raw_affiliation_strings":["Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033227006","display_name":"Arpit Shah","orcid":"https://orcid.org/0009-0002-2208-1238"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arpit Shah","raw_affiliation_strings":["Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105513963","display_name":"Suparna Bhattacharya","orcid":"https://orcid.org/0000-0001-9541-4027"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suparna Bhattacharya","raw_affiliation_strings":["Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071889037","display_name":"Martin Folt\u00edn","orcid":"https://orcid.org/0000-0002-3386-0272"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martin Foltin","raw_affiliation_strings":["Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040764379","display_name":"Paolo Faraboschi","orcid":"https://orcid.org/0000-0003-4778-5696"},"institutions":[{"id":"https://openalex.org/I4210122178","display_name":"Hewlett Packard Enterprise (United States)","ror":"https://ror.org/020x0c621","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122178"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paolo Faraboschi","raw_affiliation_strings":["Hewlett Packard Enterprise Labs, Houston, TX, United States"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Enterprise Labs, Houston, TX, United States","institution_ids":["https://openalex.org/I4210122178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050105172","display_name":"Kaushik Roy","orcid":"https://orcid.org/0000-0001-6610-7845"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushik Roy","raw_affiliation_strings":["AI Institute, University of South Carolina, Columbia, SC, United States"],"affiliations":[{"raw_affiliation_string":"AI Institute, University of South Carolina, Columbia, SC, United States","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028772801","display_name":"Amit Sheth","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit Sheth","raw_affiliation_strings":["AI Institute, University of South Carolina, Columbia, SC, United States"],"affiliations":[{"raw_affiliation_string":"AI Institute, University of South Carolina, Columbia, SC, United States","institution_ids":["https://openalex.org/I155781252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5061795720"],"corresponding_institution_ids":["https://openalex.org/I155781252","https://openalex.org/I4210122178"],"apc_list":{"value":1150,"currency":"USD","value_usd":1150},"apc_paid":{"value":1150,"currency":"USD","value_usd":1150},"fwci":9.3726,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97099876,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"1476506","last_page":"1476506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9872999787330627,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.8701578378677368},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8427318334579468},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6500217914581299},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.6185315847396851},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5221669673919678},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4683156907558441},{"id":"https://openalex.org/keywords/metadata-repository","display_name":"Metadata repository","score":0.45461615920066833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37438544631004333},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.23276561498641968},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.07518747448921204},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07275184988975525},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07186037302017212}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.8701578378677368},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8427318334579468},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6500217914581299},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.6185315847396851},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5221669673919678},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4683156907558441},{"id":"https://openalex.org/C153048206","wikidata":"https://www.wikidata.org/wiki/Q3454922","display_name":"Metadata repository","level":3,"score":0.45461615920066833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37438544631004333},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.23276561498641968},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.07518747448921204},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07275184988975525},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07186037302017212},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fdata.2024.1476506","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1476506","pdf_url":"https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2024.1476506/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},{"id":"pmid:39839155","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39839155","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in big data","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11748301","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11748301","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11748301/pdf/fdata-07-1476506.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Front Big Data","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:3ef3d419efaa4b87a847f8c48a633303","is_oa":true,"landing_page_url":"https://doaj.org/article/3ef3d419efaa4b87a847f8c48a633303","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Big Data, Vol 7 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fdata.2024.1476506","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1476506","pdf_url":"https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2024.1476506/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5400000214576721,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406145277.pdf","grobid_xml":"https://content.openalex.org/works/W4406145277.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2102539288","https://openalex.org/W2132862423","https://openalex.org/W2295598076","https://openalex.org/W2507449987","https://openalex.org/W2737041163","https://openalex.org/W2753460696","https://openalex.org/W2932529478","https://openalex.org/W2942231644","https://openalex.org/W2948273090","https://openalex.org/W2963242637","https://openalex.org/W2963834410","https://openalex.org/W2964121744","https://openalex.org/W2966284335","https://openalex.org/W2970427081","https://openalex.org/W3005680577","https://openalex.org/W3040266635","https://openalex.org/W3092710364","https://openalex.org/W3093789214","https://openalex.org/W3135550350","https://openalex.org/W3170647102","https://openalex.org/W3174397553","https://openalex.org/W3199052634","https://openalex.org/W3201904098","https://openalex.org/W3202036678","https://openalex.org/W3203324567","https://openalex.org/W3211229017","https://openalex.org/W3213898752","https://openalex.org/W4289753531","https://openalex.org/W4310491435","https://openalex.org/W4361866031","https://openalex.org/W4362678815","https://openalex.org/W4376122803","https://openalex.org/W4378711711","https://openalex.org/W4386517356","https://openalex.org/W4388955808","https://openalex.org/W4391514872","https://openalex.org/W4392616852","https://openalex.org/W4393034354","https://openalex.org/W4393336166","https://openalex.org/W4399117321"],"related_works":["https://openalex.org/W1552553528","https://openalex.org/W4380433113","https://openalex.org/W2183628870","https://openalex.org/W4386072068","https://openalex.org/W252339960","https://openalex.org/W3023161639","https://openalex.org/W2008531296","https://openalex.org/W2782431616","https://openalex.org/W2394393789","https://openalex.org/W2374379029"],"abstract_inverted_index":{"The":[0],"emergence":[1],"of":[2,12,25,33,53,59,62,147,170,209,223,238,284],"advanced":[3],"artificial":[4],"intelligence":[5],"(AI)":[6],"models":[7],"has":[8],"driven":[9],"the":[10,107,154,228,239,248],"development":[11],"frameworks":[13],"and":[14,22,42,65,80,100,105,110,168,176,183,268,274,282],"approaches":[15],"that":[16,199,215],"focus":[17],"on":[18,179],"automating":[19],"model":[20,43,198],"training":[21],"hyperparameter":[23],"tuning":[24],"end-to-end":[26,54],"AI":[27,55,63,75,90,140,171,250,263,272,286],"pipelines.":[28,150,172],"However,":[29,103],"other":[30,201],"crucial":[31],"stages":[32],"these":[34,114],"pipelines":[35,56,64,76,186,220],"such":[36,96,165],"as":[37,97,166,243,276],"dataset":[38],"selection,":[39],"feature":[40],"engineering,":[41],"optimization":[44],"for":[45,162,246,258,270,279],"deployment":[46],"have":[47],"received":[48],"less":[49],"attention.":[50],"Improving":[51],"efficiency":[52],"requires":[57],"metadata":[58,70,92,156],"past":[60],"executions":[61],"all":[66],"their":[67,259],"stages.":[68],"Regenerating":[69],"history":[71],"by":[72,127,203],"re-executing":[73],"existing":[74],"is":[77,117,134,159],"computationally":[78],"challenging":[79],"impractical.":[81],"To":[82],"address":[83],"this":[84,121],"issue,":[85],"we":[86,123,193],"propose":[87,194],"to":[88,136,181,187,227],"source":[89],"pipeline":[91,155,264],"from":[93,113],"open-source":[94],"platforms":[95],"Papers-with-Code,":[98],"OpenML,":[99],"Hugging":[101],"Face.":[102],"integrating":[104],"unifying":[106],"varying":[108],"terminologies":[109],"data":[111,280],"formats":[112],"diverse":[115],"sources":[116],"a":[118,125,195,205,255,277],"challenge.":[119],"In":[120],"study,":[122],"present":[124],"solution":[126],"introducing":[128],"Common":[129],"Metadata":[130,142],"Ontology":[131],"(CMO)":[132],"which":[133,232],"used":[135],"construct":[137],"an":[138,244],"extensive":[139],"Pipeline":[141],"Knowledge":[143],"Graph":[144],"(AIMKG)":[145],"consisting":[146],"1.6":[148],"million":[149],"Through":[151],"semantic":[152],"enhancements,":[153],"in":[157,221,236],"AIMKG":[158,180,241],"also":[160],"enriched":[161],"downstream":[163],"tasks":[164],"search":[167,182],"recommendation":[169],"We":[173],"perform":[174],"quantitative":[175,191],"qualitative":[177,212],"evaluations":[178],"recommend":[184],"relevant":[185,219,234],"user":[188],"query.":[189],"For":[190],"evaluation,":[192],"custom":[196],"aggregation":[197],"outperforms":[200],"baselines":[202],"achieving":[204],"retrieval":[206],"accuracy":[207],"(R@1)":[208],"76.3%.":[210],"Our":[211],"analysis":[213,283],"shows":[214],"AIMKG-based":[216],"recommender":[217,231],"retrieved":[218,233],"78%":[222],"test":[224],"cases":[225],"compared":[226],"state-of-the-art":[229],"MLSchema-based":[230],"responses":[235],"51%":[237],"cases.":[240],"serves":[242,275],"atlas":[245],"navigating":[247],"evolving":[249,285],"landscape,":[251],"providing":[252],"practitioners":[253],"with":[254],"comprehensive":[256],"factsheet":[257],"applications.":[260],"It":[261],"guides":[262],"optimization,":[265],"offers":[266],"insights":[267],"recommendations":[269],"improving":[271],"pipelines,":[273],"foundation":[278],"mining":[281],"workflows.":[287]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}