{"id":"https://openalex.org/W4410081721","doi":"https://doi.org/10.3390/data10050068","title":"Performance and Scalability of Data Cleaning and Preprocessing Tools: A Benchmark on Large Real-World Datasets","display_name":"Performance and Scalability of Data Cleaning and Preprocessing Tools: A Benchmark on Large Real-World Datasets","publication_year":2025,"publication_date":"2025-05-05","ids":{"openalex":"https://openalex.org/W4410081721","doi":"https://doi.org/10.3390/data10050068"},"language":"en","primary_location":{"id":"doi:10.3390/data10050068","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data10050068","pdf_url":"https://www.mdpi.com/2306-5729/10/5/68/pdf?version=1746437834","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2306-5729/10/5/68/pdf?version=1746437834","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103618208","display_name":"Pedro Martins","orcid":"https://orcid.org/0000-0002-2118-1440"},"institutions":[{"id":"https://openalex.org/I56125125","display_name":"Polytechnic Institute of Viseu","ror":"https://ror.org/0235kxk33","country_code":"PT","type":"education","lineage":["https://openalex.org/I56125125"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"Pedro Martins","raw_affiliation_strings":["Research Center in Digital Services, Polytechnic of Viseu, 3504-510 Viseu, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-2118-1440","affiliations":[{"raw_affiliation_string":"Research Center in Digital Services, Polytechnic of Viseu, 3504-510 Viseu, Portugal","institution_ids":["https://openalex.org/I56125125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067746692","display_name":"Filipe Cardoso","orcid":"https://orcid.org/0000-0002-3916-5182"},"institutions":[{"id":"https://openalex.org/I4210114793","display_name":"Instituto Polit\u00e9cnico de Santar\u00e9m","ror":"https://ror.org/02bbx2g30","country_code":"PT","type":"education","lineage":["https://openalex.org/I4210114793"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Filipe Cardoso","raw_affiliation_strings":["Polytechnic Institute of Santar\u00e9m, Escola Superior de Gest\u00e3o e Tecnologia de Santar\u00e9m, 2001-904 Santar\u00e9m, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-3916-5182","affiliations":[{"raw_affiliation_string":"Polytechnic Institute of Santar\u00e9m, Escola Superior de Gest\u00e3o e Tecnologia de Santar\u00e9m, 2001-904 Santar\u00e9m, Portugal","institution_ids":["https://openalex.org/I4210114793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069470015","display_name":"Paulo V\u00e1z","orcid":"https://orcid.org/0000-0002-1745-8937"},"institutions":[{"id":"https://openalex.org/I56125125","display_name":"Polytechnic Institute of Viseu","ror":"https://ror.org/0235kxk33","country_code":"PT","type":"education","lineage":["https://openalex.org/I56125125"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Paulo V\u00e1z","raw_affiliation_strings":["Research Center in Digital Services, Polytechnic of Viseu, 3504-510 Viseu, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-1745-8937","affiliations":[{"raw_affiliation_string":"Research Center in Digital Services, Polytechnic of Viseu, 3504-510 Viseu, Portugal","institution_ids":["https://openalex.org/I56125125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431521","display_name":"Jos\u00e9 Silva","orcid":"https://orcid.org/0000-0001-7285-8282"},"institutions":[{"id":"https://openalex.org/I56125125","display_name":"Polytechnic Institute of Viseu","ror":"https://ror.org/0235kxk33","country_code":"PT","type":"education","lineage":["https://openalex.org/I56125125"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 Silva","raw_affiliation_strings":["Research Center in Digital Services, Polytechnic of Viseu, 3504-510 Viseu, Portugal"],"raw_orcid":"https://orcid.org/0000-0001-7285-8282","affiliations":[{"raw_affiliation_string":"Research Center in Digital Services, Polytechnic of Viseu, 3504-510 Viseu, Portugal","institution_ids":["https://openalex.org/I56125125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064251517","display_name":"Maryam Abbasi","orcid":"https://orcid.org/0000-0002-9011-0734"},"institutions":[{"id":"https://openalex.org/I293362453","display_name":"Polytechnic Institute of Coimbra","ror":"https://ror.org/01n8x4993","country_code":"PT","type":"education","lineage":["https://openalex.org/I293362453"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Maryam Abbasi","raw_affiliation_strings":["Applied Research Institute, Polytechnic of Coimbra, 3045-093 Coimbra, Portugal"],"raw_orcid":"https://orcid.org/0000-0002-9011-0734","affiliations":[{"raw_affiliation_string":"Applied Research Institute, Polytechnic of Coimbra, 3045-093 Coimbra, Portugal","institution_ids":["https://openalex.org/I293362453"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103618208"],"corresponding_institution_ids":["https://openalex.org/I56125125"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":15.8728,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.98977505,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"10","issue":"5","first_page":"68","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9998999834060669,"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/T11891","display_name":"Big Data and Business Intelligence","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9678999781608582,"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/scalability","display_name":"Scalability","score":0.8302223682403564},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7823851108551025},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7542237043380737},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7131606936454773},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.5865949988365173},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.577599823474884},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4187779426574707},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37192559242248535},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36380821466445923},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.36285853385925293},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2604396343231201},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.0834733247756958},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07750412821769714}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8302223682403564},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7823851108551025},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7542237043380737},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7131606936454773},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.5865949988365173},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.577599823474884},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4187779426574707},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37192559242248535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36380821466445923},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36285853385925293},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2604396343231201},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0834733247756958},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07750412821769714}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/data10050068","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data10050068","pdf_url":"https://www.mdpi.com/2306-5729/10/5/68/pdf?version=1746437834","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:gam:jdataj:v:10:y:2025:i:5:p:68-:d:1649421","is_oa":false,"landing_page_url":"https://www.mdpi.com/2306-5729/10/5/68/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:818f8fd0db494df29403ebb88da4600c","is_oa":true,"landing_page_url":"https://doaj.org/article/818f8fd0db494df29403ebb88da4600c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data, Vol 10, Iss 5, p 68 (2025)","raw_type":"article"},{"id":"pmh:oai:repositorio.ipv.pt:10400.19/9342","is_oa":true,"landing_page_url":"http://hdl.handle.net/10400.19/9342","pdf_url":null,"source":{"id":"https://openalex.org/S4306402433","display_name":"Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.3390/data10050068","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data10050068","pdf_url":"https://www.mdpi.com/2306-5729/10/5/68/pdf?version=1746437834","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410081721.pdf","grobid_xml":"https://content.openalex.org/works/W4410081721.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1610496399","https://openalex.org/W2064766209","https://openalex.org/W2143677795","https://openalex.org/W2342249984","https://openalex.org/W2437617937","https://openalex.org/W2544486974","https://openalex.org/W2767280887","https://openalex.org/W2949244208","https://openalex.org/W3146259567","https://openalex.org/W4220923188","https://openalex.org/W4402390732","https://openalex.org/W4408444355","https://openalex.org/W6636177537","https://openalex.org/W6696516842"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"Data":[0],"cleaning":[1,37,113,223],"remains":[2],"one":[3],"of":[4,21,32,100,175,195],"the":[5,17,193],"most":[6],"time-consuming":[7],"and":[8,19,44,58,84,98,114,151,161,168,187,192,204,216],"critical":[9],"steps":[10],"in":[11,122,126,185,190],"modern":[12],"data":[13,36,88,112,209,222],"science,":[14],"directly":[15],"influencing":[16],"reliability":[18],"accuracy":[20],"downstream":[22],"analytics.":[23],"In":[24],"this":[25,206],"paper,":[26],"we":[27,91],"present":[28],"a":[29,45],"comprehensive":[30],"evaluation":[31],"five":[33],"widely":[34],"used":[35],"tools\u2014OpenRefine,":[38],"Dedupe,":[39],"Great":[40,152],"Expectations,":[41],"TidyData":[42,160],"(PyJanitor),":[43],"baseline":[46,162],"Pandas":[47,163],"pipeline\u2014applied":[48],"to":[49,72,219],"large-scale,":[50],"messy":[51],"datasets":[52],"spanning":[53],"three":[54],"domains":[55],"(healthcare,":[56],"finance,":[57,123],"industrial":[59,127],"telemetry).":[60],"We":[61,106],"benchmark":[62],"each":[63,201],"tool":[64,132,176],"on":[65,110,179],"dataset":[66],"sizes":[67],"ranging":[68],"from":[69],"1":[70],"million":[71,74],"100":[73],"records,":[75],"measuring":[76],"execution":[77],"time,":[78],"memory":[79],"usage,":[80],"error":[81],"detection":[82,150],"accuracy,":[83],"scalability":[85,167],"under":[86,170],"increasing":[87],"volumes.":[89],"Additionally,":[90],"assess":[92],"qualitative":[93],"aspects":[94],"such":[95],"as":[96],"usability":[97],"ease":[99],"integration,":[101],"reflecting":[102],"real-world":[103],"adoption":[104],"concerns.":[105],"incorporate":[107],"recent":[108],"findings":[109,135],"parallelized":[111],"highlight":[115],"how":[116],"domain-specific":[117,180],"anomalies":[118],"(e.g.,":[119,182],"negative":[120],"amounts":[121],"sensor":[124],"corruption":[125],"telemetry)":[128],"can":[129],"significantly":[130],"impact":[131],"choice.":[133],"Our":[134],"reveal":[136],"that":[137],"no":[138],"single":[139],"solution":[140],"excels":[141],"across":[142],"all":[143],"metrics;":[144],"while":[145],"Dedupe":[146],"provides":[147],"robust":[148],"duplicate":[149],"Expectations":[153],"offers":[154,208],"in-depth":[155],"rule-based":[156],"validation,":[157],"tools":[158,218],"like":[159],"pipelines":[164],"demonstrate":[165],"strong":[166],"flexibility":[169],"chunk-based":[171],"ingestion.":[172],"The":[173],"choice":[174],"ultimately":[177],"depends":[178],"requirements":[181],"approximate":[183],"matching":[184],"finance":[186],"strict":[188],"auditing":[189],"healthcare)":[191],"magnitude":[194],"available":[196],"computational":[197],"resources.":[198],"By":[199],"highlighting":[200],"framework\u2019s":[202],"strengths":[203],"limitations,":[205],"study":[207],"practitioners":[210],"clear,":[211],"evidence-driven":[212],"guidance":[213],"for":[214],"selecting":[215],"combining":[217],"tackle":[220],"large-scale":[221],"challenges.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-04T09:04:59.091469","created_date":"2025-10-10T00:00:00"}
