{"id":"https://openalex.org/W7161539289","doi":"https://doi.org/10.48550/arxiv.2605.16068","title":"Relational Database Data Lineage Ontology","display_name":"Relational Database Data Lineage Ontology","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161539289","doi":"https://doi.org/10.48550/arxiv.2605.16068"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.16068","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16068","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.16068","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015925998","display_name":"Jakub Dutkiewicz","orcid":"https://orcid.org/0000-0002-7954-7484"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dutkiewicz, Jakub","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069958377","display_name":"Pawe\u0142 Misiorek","orcid":"https://orcid.org/0000-0001-5223-240X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Misiorek, Pawe\u0142","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5054888563","display_name":"Robert Wrembel","orcid":"https://orcid.org/0000-0001-6037-5718"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wrembel, Robert","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.7483999729156494,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.7483999729156494,"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/T11719","display_name":"Data Quality and Management","score":0.11620000004768372,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.024900000542402267,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ontology","display_name":"Ontology","score":0.6826000213623047},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.6025000214576721},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.476500004529953},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43560001254081726},{"id":"https://openalex.org/keywords/lineage","display_name":"Lineage (genetic)","score":0.4323999881744385},{"id":"https://openalex.org/keywords/relational-model","display_name":"Relational model","score":0.3847000002861023},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3538999855518341},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.3382999897003174}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7721999883651733},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.6826000213623047},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.6025000214576721},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.476500004529953},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43560001254081726},{"id":"https://openalex.org/C2776817793","wikidata":"https://www.wikidata.org/wiki/Q6553369","display_name":"Lineage (genetic)","level":3,"score":0.4323999881744385},{"id":"https://openalex.org/C40207289","wikidata":"https://www.wikidata.org/wiki/Q755662","display_name":"Relational model","level":3,"score":0.3847000002861023},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.383899986743927},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C5968703","wikidata":"https://www.wikidata.org/wiki/Q267136","display_name":"Database model","level":3,"score":0.3294000029563904},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C22550185","wikidata":"https://www.wikidata.org/wiki/Q7095047","display_name":"Ontology-based data integration","level":3,"score":0.3262999951839447},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32190001010894775},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29580000042915344},{"id":"https://openalex.org/C148840519","wikidata":"https://www.wikidata.org/wiki/Q1049878","display_name":"Database design","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27070000767707825},{"id":"https://openalex.org/C100463513","wikidata":"https://www.wikidata.org/wiki/Q5227322","display_name":"Data model (GIS)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.16068","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16068","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.16068","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16068","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modeling":[0],"data":[1,32],"lineage":[2,47,62,90,155],"in":[3,11,154],"relational":[4,30,81],"databases":[5],"remains":[6],"a":[7,26,37,102,106,118],"challenging":[8],"problem,":[9],"particularly":[10],"scenarios":[12],"involving":[13],"incomplete":[14],"or":[15],"missing":[16],"dependencies":[17],"between":[18],"database":[19,31],"objects.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24,100,113],"propose":[25],"novel":[27],"ontology":[28,66,134],"for":[29],"lineage,":[33],"designed":[34],"to":[35,152],"provide":[36],"richer":[38],"and":[39,77,135,163],"more":[40,86],"expressive":[41],"semantic":[42,149],"representation":[43],"supporting":[44],"discovering":[45],"the":[46,64,68,94,97,115,131,136,144,147],"links":[48],"by":[49,161],"means":[50],"of":[51,80,89,96,117,146],"knowledge":[52],"graphs":[53],"(KGs).":[54],"Building":[55],"upon":[56],"our":[57],"previous":[58],"work":[59],"on":[60,124],"KG-based":[61,107],"discovery,":[63],"proposed":[65,98,138],"extends":[67],"earlier":[69],"model":[70,122,150],"with":[71],"additional":[72],"concepts":[73],"capturing":[74],"structural,":[75],"semantic,":[76],"transformation-level":[78],"characteristics":[79],"data.":[82],"These":[83],"extensions":[84],"enable":[85],"precise":[87],"encoding":[88],"evidence.":[91],"To":[92],"evaluate":[93],"impact":[95],"ontology,":[99],"conduct":[101],"comparative":[103],"study":[104],"using":[105,130],"inductive":[108],"link":[109,156],"prediction":[110,157],"framework.":[111],"Specifically,":[112],"assess":[114],"performance":[116],"graph":[119],"neural":[120],"network":[121],"based":[123],"path":[125],"embeddings":[126],"under":[127],"two":[128],"settings:":[129],"original":[132],"baseline":[133],"newly":[137],"one.":[139],"Experimental":[140],"results":[141],"demonstrate":[142],"that":[143],"application":[145],"enriched":[148],"leads":[151],"improvements":[153],"performance,":[158],"as":[159],"measured":[160],"AUC":[162],"Hits@10":[164],"metrics.":[165]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-19T00:00:00"}