{"id":"https://openalex.org/W3081464307","doi":"https://doi.org/10.1145/3394486.3406477","title":"Overview and Importance of Data Quality for Machine Learning Tasks","display_name":"Overview and Importance of Data Quality for Machine Learning Tasks","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3081464307","doi":"https://doi.org/10.1145/3394486.3406477","mag":"3081464307"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3406477","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3406477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-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/A5050387442","display_name":"Abhinav Jain","orcid":"https://orcid.org/0000-0001-7993-169X"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Abhinav Jain","raw_affiliation_strings":["IBM Research India, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102917997","display_name":"Hima Patel","orcid":"https://orcid.org/0000-0002-0031-8428"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hima Patel","raw_affiliation_strings":["IBM Research India, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, Bengaluru, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024416733","display_name":"Lokesh Nagalapatti","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Lokesh Nagalapatti","raw_affiliation_strings":["IBM Research India, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, Bengaluru, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054069765","display_name":"Nitin Gupta","orcid":"https://orcid.org/0000-0003-0177-6292"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nitin Gupta","raw_affiliation_strings":["IBM Research India, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046646390","display_name":"Sameep Mehta","orcid":"https://orcid.org/0000-0002-9599-1526"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sameep Mehta","raw_affiliation_strings":["IBM Research India, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, Bengaluru, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082881366","display_name":"Shanmukha Guttula","orcid":"https://orcid.org/0009-0001-1982-024X"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shanmukha Guttula","raw_affiliation_strings":["IBM Research India, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, Bengaluru, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054372047","display_name":"Shashank Mujumdar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shashank Mujumdar","raw_affiliation_strings":["IBM Research India, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101505239","display_name":"Shazia Afzal","orcid":"https://orcid.org/0000-0001-7151-4306"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shazia Afzal","raw_affiliation_strings":["IBM Research India, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046316553","display_name":"Ruhi Sharma Mittal","orcid":"https://orcid.org/0009-0002-2649-6844"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ruhi Sharma Mittal","raw_affiliation_strings":["IBM Research India, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, Bengaluru, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011547127","display_name":"Vitobha Munigala","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vitobha Munigala","raw_affiliation_strings":["IBM Research India, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"IBM Research India, Bengaluru, India","institution_ids":["https://openalex.org/I4210103279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5050387442"],"corresponding_institution_ids":["https://openalex.org/I4210103279"],"apc_list":null,"apc_paid":null,"fwci":12.9124,"has_fulltext":false,"cited_by_count":274,"citation_normalized_percentile":{"value":0.98983591,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3561","last_page":"3562"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9976999759674072,"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":0.9962999820709229,"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/computer-science","display_name":"Computer science","score":0.8452390432357788},{"id":"https://openalex.org/keywords/debugging","display_name":"Debugging","score":0.5871485471725464},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5846357345581055},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5487946271896362},{"id":"https://openalex.org/keywords/ibm","display_name":"IBM","score":0.5357991456985474},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.5220065712928772},{"id":"https://openalex.org/keywords/data-space","display_name":"Data space","score":0.5071887969970703},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4915057122707367},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47603940963745117},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.45549142360687256},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.45352113246917725},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4302537143230438},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32380491495132446},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.09220856428146362}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8452390432357788},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.5871485471725464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5846357345581055},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5487946271896362},{"id":"https://openalex.org/C70388272","wikidata":"https://www.wikidata.org/wiki/Q5968558","display_name":"IBM","level":2,"score":0.5357991456985474},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.5220065712928772},{"id":"https://openalex.org/C2988382989","wikidata":"https://www.wikidata.org/wiki/Q370685","display_name":"Data space","level":2,"score":0.5071887969970703},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4915057122707367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47603940963745117},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.45549142360687256},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.45352113246917725},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4302537143230438},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32380491495132446},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.09220856428146362},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3406477","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3406477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1610496399","https://openalex.org/W2132525863","https://openalex.org/W2163372266","https://openalex.org/W2622411536","https://openalex.org/W2913218482","https://openalex.org/W2914436728","https://openalex.org/W2941766203","https://openalex.org/W2950235146","https://openalex.org/W3098774588"],"related_works":["https://openalex.org/W3126131865","https://openalex.org/W4321442002","https://openalex.org/W2015265939","https://openalex.org/W2284072287","https://openalex.org/W2611067230","https://openalex.org/W2155788121","https://openalex.org/W4235469518","https://openalex.org/W2387706296","https://openalex.org/W2480201319","https://openalex.org/W2294325978"],"abstract_inverted_index":{"It":[0],"is":[1,15,65,183],"well":[2],"understood":[3],"from":[4],"literature":[5],"that":[6],"the":[7,19,22,32,51,56,68,86,89,102,108,118,128,147,158,178],"performance":[8],"of":[9,21,34,55,88,110,117,130,136],"a":[10,111],"machine":[11,140],"learning":[12,141],"(ML)":[13],"model":[14,123],"upper":[16],"bounded":[17],"by":[18],"quality":[20,33,87,103,133,150],"data.":[23],"While":[24],"researchers":[25],"and":[26,41,72,82,95,165,167],"practitioners":[27],"have":[28],"focused":[29],"on":[30,157],"improving":[31,50],"models":[35],"(such":[36],"as":[37],"neural":[38],"architecture":[39],"search":[40],"automated":[42],"feature":[43],"selection),":[44],"there":[45],"are":[46],"limited":[47],"efforts":[48],"towards":[49],"data":[52,90,112,132,149],"quality.":[53],"One":[54],"crucial":[57],"requirements":[58],"before":[59],"consuming":[60],"datasets":[61],"for":[62,114,139],"any":[63],"application":[64],"to":[66,74,100,106,121,171],"understand":[67],"dataset":[69],"at":[70],"hand":[71],"failure":[73],"do":[75],"so":[76],"can":[77],"result":[78],"in":[79,134,154,185],"inaccurate":[80],"analytics":[81],"unreliable":[83],"decisions.":[84],"Assessing":[85],"across":[91],"intelligently":[92],"designed":[93],"metrics":[94],"developing":[96],"corresponding":[97],"transformation":[98],"operations":[99],"address":[101],"gaps":[104],"helps":[105],"reduce":[107],"effort":[109],"scientist":[113],"iterative":[115],"debugging":[116],"ML":[119],"pipeline":[120],"improve":[122],"performance.":[124],"This":[125,143],"tutorial":[126,144],"highlights":[127],"importance":[129],"analysing":[131],"terms":[135],"its":[137],"value":[138],"applications.":[142],"surveys":[145],"all":[146],"important":[148],"related":[151],"approaches":[152],"discussed":[153],"literature,":[155],"focusing":[156],"intuition":[159],"behind":[160],"them,":[161],"highlighting":[162],"their":[163,169],"strengths":[164],"similarities,":[166],"illustrates":[168],"applicability":[170],"real-world":[172],"problems.":[173],"Finally":[174],"we":[175],"will":[176],"discuss":[177],"interesting":[179],"work":[180],"IBM":[181],"Research":[182],"doing":[184],"this":[186],"space.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":71},{"year":2024,"cited_by_count":97},{"year":2023,"cited_by_count":59},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":12}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}