{"id":"https://openalex.org/W2895960353","doi":"https://doi.org/10.3233/sw-180319","title":"Generating public transport data based on population distributions for RDF benchmarking","display_name":"Generating public transport data based on population distributions for RDF benchmarking","publication_year":2018,"publication_date":"2018-08-28","ids":{"openalex":"https://openalex.org/W2895960353","doi":"https://doi.org/10.3233/sw-180319","mag":"2895960353"},"language":"en","primary_location":{"id":"doi:10.3233/sw-180319","is_oa":false,"landing_page_url":"https://doi.org/10.3233/sw-180319","pdf_url":null,"source":{"id":"https://openalex.org/S4210177235","display_name":"Semantic Web","issn_l":"1570-0844","issn":["1570-0844","2210-4968"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Semantic Web","raw_type":"journal-article"},"type":"article","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/A5089444758","display_name":"Ruben Taelman","orcid":"https://orcid.org/0000-0001-5118-256X"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Ruben Taelman","raw_affiliation_strings":["imec \u2013 Ghent University \u2013 IDLab, Technologiepark-Zwijnaarde 15, B-9052 Ghent, Belgium. E-mail:\u00a0ruben.taelman@ugent.be"],"affiliations":[{"raw_affiliation_string":"imec \u2013 Ghent University \u2013 IDLab, Technologiepark-Zwijnaarde 15, B-9052 Ghent, Belgium. E-mail:\u00a0ruben.taelman@ugent.be","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068448434","display_name":"Pieter Colpaert","orcid":"https://orcid.org/0000-0001-6917-2167"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Pieter Colpaert","raw_affiliation_strings":["imec \u2013 Ghent University \u2013 IDLab, Technologiepark-Zwijnaarde 15, B-9052 Ghent, Belgium. E-mail:\u00a0ruben.taelman@ugent.be"],"affiliations":[{"raw_affiliation_string":"imec \u2013 Ghent University \u2013 IDLab, Technologiepark-Zwijnaarde 15, B-9052 Ghent, Belgium. E-mail:\u00a0ruben.taelman@ugent.be","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059346676","display_name":"Erik Mannens","orcid":"https://orcid.org/0000-0001-7946-4884"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Erik Mannens","raw_affiliation_strings":["imec \u2013 Ghent University \u2013 IDLab, Technologiepark-Zwijnaarde 15, B-9052 Ghent, Belgium. E-mail:\u00a0ruben.taelman@ugent.be"],"affiliations":[{"raw_affiliation_string":"imec \u2013 Ghent University \u2013 IDLab, Technologiepark-Zwijnaarde 15, B-9052 Ghent, Belgium. E-mail:\u00a0ruben.taelman@ugent.be","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055871472","display_name":"Ruben Verborgh","orcid":"https://orcid.org/0000-0002-8596-222X"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Ruben Verborgh","raw_affiliation_strings":["imec \u2013 Ghent University \u2013 IDLab, Technologiepark-Zwijnaarde 15, B-9052 Ghent, Belgium. E-mail:\u00a0ruben.taelman@ugent.be"],"affiliations":[{"raw_affiliation_string":"imec \u2013 Ghent University \u2013 IDLab, Technologiepark-Zwijnaarde 15, B-9052 Ghent, Belgium. E-mail:\u00a0ruben.taelman@ugent.be","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089444758"],"corresponding_institution_ids":["https://openalex.org/I32597200"],"apc_list":null,"apc_paid":null,"fwci":0.3316,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.5746521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"10","issue":"2","first_page":"305","last_page":"328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9991000294685364,"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":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.849768340587616},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.8268535137176514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7364692687988281},{"id":"https://openalex.org/keywords/rdf","display_name":"RDF","score":0.6292034387588501},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5831602215766907},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5706970691680908},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4789638817310333},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.4574512839317322},{"id":"https://openalex.org/keywords/public-transport","display_name":"Public transport","score":0.4351480007171631},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.40968015789985657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19797632098197937},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.11832109093666077},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11099392175674438},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10498890280723572},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.08371436595916748}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.849768340587616},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.8268535137176514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7364692687988281},{"id":"https://openalex.org/C147497476","wikidata":"https://www.wikidata.org/wiki/Q54872","display_name":"RDF","level":3,"score":0.6292034387588501},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5831602215766907},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5706970691680908},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4789638817310333},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.4574512839317322},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.4351480007171631},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40968015789985657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19797632098197937},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.11832109093666077},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11099392175674438},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10498890280723572},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.08371436595916748},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3233/sw-180319","is_oa":false,"landing_page_url":"https://doi.org/10.3233/sw-180319","pdf_url":null,"source":{"id":"https://openalex.org/S4210177235","display_name":"Semantic Web","issn_l":"1570-0844","issn":["1570-0844","2210-4968"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Semantic Web","raw_type":"journal-article"},{"id":"pmh:oai:archive.ugent.be:8612888","is_oa":false,"landing_page_url":"https://biblio.ugent.be/publication/8612888","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 2210-4968","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W10089010","https://openalex.org/W15302468","https://openalex.org/W114983493","https://openalex.org/W115854788","https://openalex.org/W1487130678","https://openalex.org/W1715730942","https://openalex.org/W1964915778","https://openalex.org/W1983094331","https://openalex.org/W1989009626","https://openalex.org/W2015191210","https://openalex.org/W2061253631","https://openalex.org/W2113582899","https://openalex.org/W2114314131","https://openalex.org/W2116135393","https://openalex.org/W2124289460","https://openalex.org/W2129908242","https://openalex.org/W2131230769","https://openalex.org/W2134193499","https://openalex.org/W2143608744","https://openalex.org/W2151247073","https://openalex.org/W2168148394","https://openalex.org/W2169440812","https://openalex.org/W2293861670","https://openalex.org/W2296760620","https://openalex.org/W2342227594","https://openalex.org/W2403125604","https://openalex.org/W2577407133","https://openalex.org/W2767161927","https://openalex.org/W2772156817","https://openalex.org/W2963108767","https://openalex.org/W6600611317"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2341842940","https://openalex.org/W1490753184","https://openalex.org/W1684934485","https://openalex.org/W114983493","https://openalex.org/W625828003","https://openalex.org/W2403445471","https://openalex.org/W4288335615"],"abstract_inverted_index":{"When":[0],"benchmarking":[1,207],"rdf":[2,101,208],"data":[3,102,209],"management":[4,103,210],"systems":[5,104,211],"such":[6,105],"as":[7,36,106],"public":[8,125,147,197],"transport":[9,126,198],"route":[10,107],"planners,":[11],"system":[12],"evaluation":[13],"needs":[14],"to":[15,48,67,91,96,135],"happen":[16],"under":[17],"various":[18],"realistic":[19,40,129],"circumstances,":[20],"which":[21],"requires":[22],"a":[23,118,178,203],"wide":[24],"range":[25],"of":[26,88,137,161,167,181],"datasets":[27,32,65,127],"with":[28,109,128,212],"different":[29],"properties.":[30],"Real-world":[31],"are":[33,45,60,76,80],"almost":[34],"ideal,":[35],"they":[37,44],"offer":[38],"these":[39,55],"circ":[41],"umstances,":[42],"but":[43],"often":[46],"hard":[47],"obtain":[49],"and":[50,99,113,131,151,159,163,189,214],"inflexible":[51],"for":[52,123,195,206],"testing.":[53],"For":[54],"reasons,":[56],"synthetic":[57,73,124],"dataset":[58,74],"generators":[59],"typically":[61],"preferred":[62],"over":[63],"real-world":[64,92,139,146],"due":[66],"their":[68,138],"intrinsic":[69],"flexibility.":[70],"Unfortunately,":[71],"many":[72],"that":[75,174],"generated":[77,169],"within":[78],"benchmarks":[79],"insufficiently":[81],"realistic,":[82],"raising":[83],"questions":[84],"about":[85],"the":[86,157,165,175,185,196],"generalizability":[87],"benchmark":[89,97],"results":[90],"scenarios.":[93],"In":[94],"order":[95],"geospatial":[98,130,213],"temporal":[100,132,215],"planners":[108],"sufficient":[110,179],"external":[111],"validity":[112],"depth,":[114],"we":[115,192],"designed":[116],"podigg,":[117],"highly":[119],"configurable":[120],"generation":[121],"algorithm":[122,142],"characteristics":[133],"comparable":[134],"those":[136],"variants.":[140],"The":[141],"is":[143],"inspired":[144],"by":[145],"transit":[148],"network":[149],"design":[150,158],"scheduling":[152],"methodologies.":[153],"This":[154],"article":[155],"discusses":[156],"implementation":[160],"podigg":[162,201],"validates":[164],"properties":[166],"its":[168],"datasets.":[170],"Our":[171],"findings":[172],"show":[173],"generator":[176],"achieves":[177],"level":[180],"realism,":[182],"based":[183],"on":[184],"existing":[186],"coherence":[187],"metric":[188],"new":[190],"metrics":[191],"introduce":[193],"specifically":[194],"domain.":[199],"Thereby,":[200],"provides":[202],"flexible":[204],"foundation":[205],"data.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
