{"id":"https://openalex.org/W3013886221","doi":"https://doi.org/10.1186/s40537-020-0285-1","title":"Sensor data quality: a systematic review","display_name":"Sensor data quality: a systematic review","publication_year":2020,"publication_date":"2020-02-11","ids":{"openalex":"https://openalex.org/W3013886221","doi":"https://doi.org/10.1186/s40537-020-0285-1","mag":"3013886221"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-020-0285-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-020-0285-1","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-0285-1","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"review","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-0285-1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067211476","display_name":"Hui Yie Teh","orcid":"https://orcid.org/0000-0002-1899-6550"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Hui Yie Teh","raw_affiliation_strings":["Department of Electrical, Computer, and Software Engineering, The University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, and Software Engineering, The University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000654559","display_name":"Andreas W. Kempa-Liehr","orcid":"https://orcid.org/0000-0001-5558-0573"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Andreas W. Kempa-Liehr","raw_affiliation_strings":["Freiburg Materials Research Center, University of Freiburg, Freiburg, Germany"],"raw_orcid":"https://orcid.org/0000-0001-5558-0573","affiliations":[{"raw_affiliation_string":"Freiburg Materials Research Center, University of Freiburg, Freiburg, Germany","institution_ids":["https://openalex.org/I161046081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091532881","display_name":"Kevin I\u2010Kai Wang","orcid":"https://orcid.org/0000-0001-8450-2558"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Kevin I-Kai Wang","raw_affiliation_strings":["Department of Electrical, Computer, and Software Engineering, The University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, and Software Engineering, The University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000654559"],"corresponding_institution_ids":["https://openalex.org/I161046081"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1123,"currency":"EUR","value_usd":1211},"fwci":10.7115,"has_fulltext":true,"cited_by_count":324,"citation_normalized_percentile":{"value":0.99239905,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"7","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9858999848365784,"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/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9779999852180481,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7838438749313354},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7253557443618774},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5986877679824829},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5593097805976868},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5467339158058167},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5169233679771423},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.500800609588623},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4262782335281372},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42581576108932495},{"id":"https://openalex.org/keywords/systematic-review","display_name":"Systematic review","score":0.4254779517650604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36421358585357666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3076915144920349}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7838438749313354},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7253557443618774},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5986877679824829},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5593097805976868},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5467339158058167},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5169233679771423},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.500800609588623},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4262782335281372},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42581576108932495},{"id":"https://openalex.org/C189708586","wikidata":"https://www.wikidata.org/wiki/Q1504425","display_name":"Systematic review","level":3,"score":0.4254779517650604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36421358585357666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3076915144920349},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political 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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-020-0285-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-020-0285-1","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-0285-1","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1c344d3feb4144a39cdf9e53bfa8deba","is_oa":true,"landing_page_url":"https://doaj.org/article/1c344d3feb4144a39cdf9e53bfa8deba","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 7, Iss 1, Pp 1-49 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-020-0285-1","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-020-0285-1","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-0285-1","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321421","display_name":"Albert-Ludwigs-Universit\u00e4t Freiburg","ror":"https://ror.org/0245cg223"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3013886221.pdf","grobid_xml":"https://content.openalex.org/works/W3013886221.grobid-xml"},"referenced_works_count":104,"referenced_works":["https://openalex.org/W349035991","https://openalex.org/W826886530","https://openalex.org/W950335322","https://openalex.org/W1126373486","https://openalex.org/W1533179050","https://openalex.org/W1567491469","https://openalex.org/W1805434785","https://openalex.org/W1965606617","https://openalex.org/W1966857452","https://openalex.org/W1973218232","https://openalex.org/W1973956882","https://openalex.org/W1977326106","https://openalex.org/W1983710014","https://openalex.org/W1984378466","https://openalex.org/W1985029811","https://openalex.org/W1989650021","https://openalex.org/W1992775328","https://openalex.org/W1993546962","https://openalex.org/W1996458756","https://openalex.org/W2004469416","https://openalex.org/W2010254953","https://openalex.org/W2011749470","https://openalex.org/W2013377700","https://openalex.org/W2018254212","https://openalex.org/W2042939937","https://openalex.org/W2043251326","https://openalex.org/W2045593919","https://openalex.org/W2054645302","https://openalex.org/W2064604759","https://openalex.org/W2074613498","https://openalex.org/W2079743397","https://openalex.org/W2081987572","https://openalex.org/W2083174992","https://openalex.org/W2083868427","https://openalex.org/W2084229232","https://openalex.org/W2086468013","https://openalex.org/W2088683982","https://openalex.org/W2093045381","https://openalex.org/W2100116885","https://openalex.org/W2100199551","https://openalex.org/W2101234009","https://openalex.org/W2103269600","https://openalex.org/W2103401572","https://openalex.org/W2111619626","https://openalex.org/W2118680859","https://openalex.org/W2121735876","https://openalex.org/W2122904721","https://openalex.org/W2129451159","https://openalex.org/W2134603844","https://openalex.org/W2137434741","https://openalex.org/W2140572114","https://openalex.org/W2144263768","https://openalex.org/W2155329925","https://openalex.org/W2156098321","https://openalex.org/W2156209126","https://openalex.org/W2163382007","https://openalex.org/W2186290821","https://openalex.org/W2187643071","https://openalex.org/W2199940212","https://openalex.org/W2217402295","https://openalex.org/W2298211015","https://openalex.org/W2341514930","https://openalex.org/W2346720329","https://openalex.org/W2398358554","https://openalex.org/W2464073121","https://openalex.org/W2481159763","https://openalex.org/W2496357058","https://openalex.org/W2516873367","https://openalex.org/W2529611981","https://openalex.org/W2530970943","https://openalex.org/W2531320996","https://openalex.org/W2538683629","https://openalex.org/W2562761545","https://openalex.org/W2596636257","https://openalex.org/W2600769841","https://openalex.org/W2619456424","https://openalex.org/W2619576622","https://openalex.org/W2620661538","https://openalex.org/W2726150830","https://openalex.org/W2738654846","https://openalex.org/W2771169143","https://openalex.org/W2772937478","https://openalex.org/W2781243672","https://openalex.org/W2791925478","https://openalex.org/W2795240825","https://openalex.org/W2796837256","https://openalex.org/W2800099531","https://openalex.org/W2802314367","https://openalex.org/W2807704342","https://openalex.org/W2809006397","https://openalex.org/W2834963557","https://openalex.org/W2991792334","https://openalex.org/W3004157836","https://openalex.org/W3021376362","https://openalex.org/W3023000814","https://openalex.org/W3045153201","https://openalex.org/W4211088835","https://openalex.org/W4212944460","https://openalex.org/W4248082917","https://openalex.org/W4294215472","https://openalex.org/W4393480503","https://openalex.org/W6816560326","https://openalex.org/W6910409717","https://openalex.org/W6960492257"],"related_works":["https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2085630472","https://openalex.org/W1977098485","https://openalex.org/W4285201053","https://openalex.org/W4213040784"],"abstract_inverted_index":{"Abstract":[0],"Sensor":[1],"data":[2,21,73,130,139,217,241,262],"quality":[3,22],"plays":[4],"a":[5],"vital":[6],"role":[7],"in":[8,40,177],"Internet":[9],"of":[10,43,51,70,94,128,171,257],"Things":[11],"(IoT)":[12],"applications":[13],"as":[14],"they":[15],"are":[16,38,55,66,89,136,154,187,202],"rendered":[17],"useless":[18],"if":[19],"the":[20,52,61,67,90,109,125,178,189,199,224,234,249,254,266],"is":[23,231],"bad.":[24],"This":[25],"systematic":[26,53,228],"review":[27,54],"aims":[28,58],"to":[29,59,76,83,220,237,248],"provide":[30],"an":[31],"introduction":[32],"and":[33,49,86,106,120,140,145,161,185,222,253],"guide":[34],"for":[35,151,168,181,278],"researchers":[36],"who":[37],"interested":[39],"quality-related":[41],"issues":[42],"physical":[44,71,239],"sensor":[45,72,129,240],"data.":[46],"The":[47,147],"process":[48,252],"results":[50],"presented":[56],"which":[57,166],"answer":[60],"following":[62],"research":[63],"questions:":[64],"what":[65,87],"different":[68,126],"types":[69,127],"errors,":[74,81],"how":[75,82],"quantify":[77],"or":[78],"detect":[79,221],"those":[80,134],"correct":[84,223],"them":[85],"domains":[88],"solutions":[91,150,213],"in.":[92],"Out":[93],"6970":[95],"literatures":[96],"obtained":[97],"from":[98],"three":[99],"databases":[100],"(ACM":[101],"Digital":[102],"Library,":[103],"IEEE":[104],"Xplore":[105],"ScienceDirect)":[107],"using":[108,205,274],"search":[110],"string":[111],"refined":[112],"via":[113],"topic":[114],"modelling,":[115],"57":[116,267],"publications":[117,269,273],"were":[118],"selected":[119,268],"examined.":[121],"Results":[122],"show":[123],"that":[124,214,233,272],"errors":[131,242],"addressed":[132],"by":[133],"papers":[135,175],"mostly":[137,203],"missing":[138],"faults":[141],"e.g.":[142],"outliers,":[143],"bias":[144],"drift.":[146],"most":[148,190],"common":[149],"error":[152,173],"detection":[153,174],"based":[155],"on":[156,198,265],"principal":[157],"component":[158],"analysis":[159,263],"(PCA)":[160],"artificial":[162],"neural":[163],"network":[164],"(ANN)":[165],"accounts":[167],"about":[169],"40%":[170],"all":[172],"found":[176,232],"study.":[179],"Similarly,":[180],"fault":[182],"correction,":[183],"PCA":[184],"ANN":[186],"among":[188],"common,":[191],"along":[192],"with":[193],"Bayesian":[194,261],"Networks.":[195],"Missing":[196],"values":[197],"other":[200],"hand,":[201],"imputed":[204],"Association":[206],"Rule":[207],"Mining.":[208],"Other":[209],"techniques":[210],"include":[211],"hybrid":[212],"combine":[215],"several":[216],"science":[218],"methods":[219,235],"errors.":[225],"Through":[226],"this":[227],"review,":[229],"it":[230],"proposed":[236],"solve":[238],"cannot":[243],"be":[244],"directly":[245],"compared":[246],"due":[247],"non-uniform":[250],"evaluation":[251,280],"high":[255],"use":[256],"non-publicly":[258],"available":[259,276],"datasets.":[260],"done":[264],"also":[270],"suggests":[271],"publicly":[275],"datasets":[277],"method":[279],"have":[281],"higher":[282],"citation":[283],"rates.":[284]},"counts_by_year":[{"year":2026,"cited_by_count":32},{"year":2025,"cited_by_count":106},{"year":2024,"cited_by_count":76},{"year":2023,"cited_by_count":50},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":28},{"year":2020,"cited_by_count":7}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
