{"id":"https://openalex.org/W4391785473","doi":"https://doi.org/10.1007/s00778-024-00835-2","title":"Assisted design of data science pipelines","display_name":"Assisted design of data science pipelines","publication_year":2024,"publication_date":"2024-02-13","ids":{"openalex":"https://openalex.org/W4391785473","doi":"https://doi.org/10.1007/s00778-024-00835-2"},"language":"en","primary_location":{"id":"doi:10.1007/s00778-024-00835-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00778-024-00835-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00778-024-00835-2.pdf","source":{"id":"https://openalex.org/S78926909","display_name":"The VLDB Journal","issn_l":"0949-877X","issn":["0949-877X","1066-8888"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The VLDB Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00778-024-00835-2.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033843672","display_name":"Sergey Redyuk","orcid":"https://orcid.org/0000-0001-7131-745X"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]},{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Sergey Redyuk","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI), Berlin, Germany","Technical University Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0001-7131-745X","affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI), Berlin, Germany","institution_ids":["https://openalex.org/I33256026"]},{"raw_affiliation_string":"Technical University Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068470780","display_name":"Zoi Kaoudi","orcid":"https://orcid.org/0000-0003-4520-5360"},"institutions":[{"id":"https://openalex.org/I83467386","display_name":"IT University of Copenhagen","ror":"https://ror.org/02309jg23","country_code":"DK","type":"education","lineage":["https://openalex.org/I83467386"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Zoi Kaoudi","raw_affiliation_strings":["IT University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IT University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I83467386"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090934117","display_name":"Sebastian Schelter","orcid":"https://orcid.org/0000-0003-4722-5840"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Sebastian Schelter","raw_affiliation_strings":["University of Amsterdam, Amsterdam, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002413906","display_name":"Volker Markl","orcid":"https://orcid.org/0009-0009-0964-026X"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]},{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Volker Markl","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI), Berlin, Germany","Technical University Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI), Berlin, Germany","institution_ids":["https://openalex.org/I33256026"]},{"raw_affiliation_string":"Technical University Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002413906","https://openalex.org/A5033843672","https://openalex.org/A5068470780","https://openalex.org/A5090934117"],"corresponding_institution_ids":["https://openalex.org/I33256026","https://openalex.org/I4577782","https://openalex.org/I83467386","https://openalex.org/I887064364"],"apc_list":{"value":2890,"currency":"USD","value_usd":2890},"apc_paid":{"value":2890,"currency":"USD","value_usd":2890},"fwci":1.6808,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.85062531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"33","issue":"4","first_page":"1129","last_page":"1153"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9929999709129333,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9815999865531921,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.6164793372154236},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4255998730659485},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.36942195892333984},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3099997639656067},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.09912633895874023}],"concepts":[{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.6164793372154236},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4255998730659485},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36942195892333984},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3099997639656067},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.09912633895874023}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s00778-024-00835-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00778-024-00835-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00778-024-00835-2.pdf","source":{"id":"https://openalex.org/S78926909","display_name":"The VLDB Journal","issn_l":"0949-877X","issn":["0949-877X","1066-8888"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The VLDB Journal","raw_type":"journal-article"},{"id":"pmh:oai:dare.uva.nl:openaire_cris_publications/85e657e9-dbf7-4654-a4af-76a3915449d1","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/assisted-design-of-data-science-pipelines(85e657e9-dbf7-4654-a4af-76a3915449d1).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Redyuk, S, Kaoudi, Z, Schelter, S & Markl, V 2024, 'Assisted design of data science pipelines', The VLDB Journal, vol. 33, no. 4, pp. 1129-1153. https://doi.org/10.1007/s00778-024-00835-2","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:pure.atira.dk:openaire/2ff36e10-98fa-467b-824b-681dbbd65f72","is_oa":true,"landing_page_url":"https://pure.itu.dk/portal/da/publications/2ff36e10-98fa-467b-824b-681dbbd65f72","pdf_url":null,"source":{"id":"https://openalex.org/S4377196680","display_name":"IT University Of Copenhagen (IT University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83467386","host_organization_name":"IT University of Copenhagen","host_organization_lineage":["https://openalex.org/I83467386"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Redyuk, S, Kaoudi, Z & Markl, V 2024, 'Assisted design of data science pipelines', The VLDB Journal, vol. 33, no. 4, pp. 1129-1153. https://doi.org/10.1007/s00778-024-00835-2","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:dare.uva.nl:publications/85e657e9-dbf7-4654-a4af-76a3915449d1","is_oa":true,"landing_page_url":"https://hdl.handle.net/11245.1/85e657e9-dbf7-4654-a4af-76a3915449d1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"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":"Redyuk, S, Kaoudi, Z, Schelter, S & Markl, V 2024, 'Assisted design of data science pipelines', The VLDB Journal, vol. 33, no. 4, pp. 1129-1153. https://doi.org/10.1007/s00778-024-00835-2","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s00778-024-00835-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00778-024-00835-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00778-024-00835-2.pdf","source":{"id":"https://openalex.org/S78926909","display_name":"The VLDB Journal","issn_l":"0949-877X","issn":["0949-877X","1066-8888"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The VLDB Journal","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.49000000953674316,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2231918279","display_name":null,"funder_award_id":"01IS18037A","funder_id":"https://openalex.org/F4320336673","funder_display_name":"Berlin Center for Machine Learning"},{"id":"https://openalex.org/G4696046801","display_name":null,"funder_award_id":"01IS18025A","funder_id":"https://openalex.org/F4320336673","funder_display_name":"Berlin Center for Machine Learning"}],"funders":[{"id":"https://openalex.org/F4320324094","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40"},{"id":"https://openalex.org/F4320334604","display_name":"Banting and Best Diabetes Centre, University of Toronto","ror":"https://ror.org/03dbr7087"},{"id":"https://openalex.org/F4320336673","display_name":"Berlin Center for Machine Learning","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4391785473.pdf"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W1836559177","https://openalex.org/W1910918478","https://openalex.org/W1965142824","https://openalex.org/W1994529543","https://openalex.org/W2009415795","https://openalex.org/W2032338144","https://openalex.org/W2062920098","https://openalex.org/W2089666999","https://openalex.org/W2117852087","https://openalex.org/W2122776323","https://openalex.org/W2126385963","https://openalex.org/W2126997347","https://openalex.org/W2132862423","https://openalex.org/W2147405597","https://openalex.org/W2149427297","https://openalex.org/W2165558283","https://openalex.org/W2189149359","https://openalex.org/W2192203593","https://openalex.org/W2432911982","https://openalex.org/W2479166836","https://openalex.org/W2579555219","https://openalex.org/W2589681725","https://openalex.org/W2620641980","https://openalex.org/W2877984652","https://openalex.org/W2945172243","https://openalex.org/W2945790622","https://openalex.org/W2947187332","https://openalex.org/W2948742859","https://openalex.org/W2949237386","https://openalex.org/W2955219525","https://openalex.org/W2966284335","https://openalex.org/W2970228335","https://openalex.org/W2979989546","https://openalex.org/W3045754299","https://openalex.org/W3099348480","https://openalex.org/W3105684693","https://openalex.org/W3105704032","https://openalex.org/W3122109253","https://openalex.org/W4211208325","https://openalex.org/W4293191915","https://openalex.org/W4302313152","https://openalex.org/W4312867851"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Abstract":[0],"When":[1],"designing":[2],"data":[3,19,100,139,152],"science":[4,140],"(DS)":[5],"pipelines,":[6,181],"end-users":[7,37],"can":[8,170],"get":[9,76],"overwhelmed":[10],"by":[11,38],"the":[12,40,77,119,135,168,196,217,222],"large":[13],"and":[14,21,28,48,60,93,102,105,113,153,187,202,226,244,247],"growing":[15],"set":[16,97],"of":[17,56,73,84,98,138,163],"available":[18,99],"preprocessing":[20,101],"modeling":[22],"techniques.":[23],"Intelligent":[24],"discovery":[25],"assistants":[26],"(IDAs)":[27],"automated":[29],"machine":[30],"learning":[31],"(AutoML)":[32],"solutions":[33,235],"aim":[34],"to":[35,46,66,70,75,109,172,208,240,249],"facilitate":[36],"(semi-)automating":[39],"process.":[41],"However,":[42],"they":[43],"are":[44],"expensive":[45],"compute":[47],"yield":[49],"limited":[50,82],"applicability":[51],"for":[52,123,134],"a":[53,94,131,148,154,160],"wide":[54],"range":[55],"real-world":[57],"use":[58],"cases":[59],"application":[61],"domains.":[62],"This":[63],"is":[64],"due":[65],"(a)":[67],"their":[68,81,107],"need":[69],"execute":[71,173],"thousands":[72],"pipelines":[74,141,188,198],"optimal":[78],"one,":[79],"(b)":[80],"support":[83],"DS":[85,155,245],"tasks,":[86,246],"e.g.,":[87,115],"supervised":[88],"classification":[89],"or":[90,174],"regression":[91],"only,":[92],"small,":[95],"static":[96],"ML":[103],"algorithms;":[104],"(c)":[106],"restriction":[108],"quantifiable":[110],"evaluation":[111,242],"processes":[112,243],"metrics,":[114],"tenfold":[116],"cross-validation":[117],"using":[118,142,199],"ROC":[120],"AUC":[121],"score":[122],"classification.":[124],"To":[125,179],"overcome":[126],"these":[127],"limitations,":[128],"we":[129],"propose":[130],"human-in-the-loop":[132],"approach":[133],"assisted":[136],"design":[137],"previously":[143],"executed":[144],"pipelines.":[145],"Based":[146],"on":[147],"user":[149,169,204],"query,":[150],"i.e.,":[151],"task,":[156],"our":[157,214],"framework":[158,219],"outputs":[159],"ranked":[161],"list":[162],"pipeline":[164],"candidates":[165],"from":[166],"which":[167],"choose":[171],"modify":[175],"in":[176],"real":[177],"time.":[178,212],"recommend":[180],"it":[182],"first":[183],"identifies":[184],"relevant":[185],"datasets":[186],"utilizing":[189],"efficient":[190],"similarity":[191],"search.":[192],"It":[193],"then":[194],"ranks":[195],"candidate":[197],"multi-objective":[200],"sorting":[201],"takes":[203],"interactions":[205],"into":[206],"account":[207],"improve":[209],"suggestions":[210],"over":[211],"In":[213],"experimental":[215],"evaluation,":[216],"proposed":[218],"significantly":[220],"outperforms":[221],"state-of-the-art":[223,232],"IDA":[224],"tool":[225],"achieves":[227],"similar":[228],"predictive":[229],"performance":[230],"with":[231],"long-running":[233],"AutoML":[234],"while":[236],"being":[237],"real-time,":[238],"generic":[239],"any":[241],"extensible":[248],"new":[250],"operators.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
