{"id":"https://openalex.org/W2793913664","doi":"https://doi.org/10.3233/ida-163311","title":"Beyond accuracy \u2013 A SMART approach to site-based spatio-temporal data quality assessment","display_name":"Beyond accuracy \u2013 A SMART approach to site-based spatio-temporal data quality assessment","publication_year":2018,"publication_date":"2018-02-22","ids":{"openalex":"https://openalex.org/W2793913664","doi":"https://doi.org/10.3233/ida-163311","mag":"2793913664"},"language":"en","primary_location":{"id":"doi:10.3233/ida-163311","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-163311","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"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":"Intelligent Data Analysis","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/A5068557729","display_name":"Douglas Galarus","orcid":null},"institutions":[{"id":"https://openalex.org/I23732399","display_name":"Montana State University","ror":"https://ror.org/02w0trx84","country_code":"US","type":"education","lineage":["https://openalex.org/I23732399","https://openalex.org/I4210126032"]},{"id":"https://openalex.org/I4210099623","display_name":"Western Transportation Institute","ror":"https://ror.org/012pd4b91","country_code":"US","type":"other","lineage":["https://openalex.org/I4210099623"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Douglas Galarus","raw_affiliation_strings":["Western Transportation Institute, Department of Computer Science, Montana State University, Bozeman, MT 59717, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western Transportation Institute, Department of Computer Science, Montana State University, Bozeman, MT 59717, USA","institution_ids":["https://openalex.org/I23732399","https://openalex.org/I4210099623"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009847987","display_name":"Rafal A. Angryk","orcid":"https://orcid.org/0000-0001-9598-8207"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rafal Angryk","raw_affiliation_strings":["Department of Computer Science, Georgia State University, Atlanta, GA 30302-5060, USA","E-mail:","Fax: +1 406 994 1697"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia State University, Atlanta, GA 30302-5060, USA","institution_ids":["https://openalex.org/I181565077"]},{"raw_affiliation_string":"E-mail:","institution_ids":[]},{"raw_affiliation_string":"Fax: +1 406 994 1697","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5068557729"],"corresponding_institution_ids":["https://openalex.org/I23732399","https://openalex.org/I4210099623"],"apc_list":null,"apc_paid":null,"fwci":0.3005,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.57626641,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"22","issue":"1","first_page":"21","last_page":"43"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10757","display_name":"Geographic Information Systems Studies","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9958000183105469,"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":0.6971248388290405},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.48632416129112244},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4664478003978729},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality assessment","score":0.4605623185634613},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4555891156196594},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.1491064429283142},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1302410364151001},{"id":"https://openalex.org/keywords/evaluation-methods","display_name":"Evaluation methods","score":0.06520366668701172}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6971248388290405},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.48632416129112244},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4664478003978729},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.4605623185634613},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4555891156196594},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.1491064429283142},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1302410364151001},{"id":"https://openalex.org/C3018395757","wikidata":"https://www.wikidata.org/wiki/Q1379672","display_name":"Evaluation methods","level":2,"score":0.06520366668701172},{"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/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-163311","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-163311","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"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":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320308025","display_name":"California Department of Transportation","ror":"https://ror.org/04d46jp54"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W174107858","https://openalex.org/W764084494","https://openalex.org/W766643320","https://openalex.org/W1567491469","https://openalex.org/W1586410151","https://openalex.org/W1986948589","https://openalex.org/W1988016803","https://openalex.org/W2005709478","https://openalex.org/W2031249902","https://openalex.org/W2048159935","https://openalex.org/W2049312801","https://openalex.org/W2092981979","https://openalex.org/W2097930305","https://openalex.org/W2099376460","https://openalex.org/W2122379123","https://openalex.org/W2147169375","https://openalex.org/W2171629540","https://openalex.org/W2291872900","https://openalex.org/W2585138032","https://openalex.org/W6674465239"],"related_works":["https://openalex.org/W2334178591","https://openalex.org/W3170966376","https://openalex.org/W2978302552","https://openalex.org/W2378887354","https://openalex.org/W2378319153","https://openalex.org/W3139152607","https://openalex.org/W2391355543","https://openalex.org/W2530386080","https://openalex.org/W2373140243","https://openalex.org/W2355211069","https://openalex.org/W2537854778","https://openalex.org/W3198351119","https://openalex.org/W2954228380","https://openalex.org/W2790853135","https://openalex.org/W2329754848","https://openalex.org/W3095399842","https://openalex.org/W2546341145","https://openalex.org/W2956618284","https://openalex.org/W2607012776","https://openalex.org/W3087428869"],"abstract_inverted_index":{"There":[0],"is":[1,24,57,99,119,211,243],"a":[2,65,109,114,130,187],"need":[3],"for":[4,69,84,87,208,245,254],"robust":[5,131],"solutions":[6],"to":[7,128,153,172,186],"the":[8,28,39,59,70,80,88,102,143,163,228,246],"challenges":[9],"of":[10,21,31,54,63,72,92,106,117,145,162,230],"spatio-temporal":[11,73],"data":[12,74,190,222],"quality":[13,29],"assessment":[14,20,30,71],"that":[15,133,149,197,215,251,260],"include":[16],"and":[17,50,61,90,113,148,157,165,256,259],"go":[18],"beyond":[19],"accuracy.":[22,159,266],"Emphasis":[23],"often":[25],"placed":[26],"on":[27,38,58],"individual":[32],"observations":[33,103],"from":[34,104,121],"sensors":[35,40],"but":[36,248],"not":[37,200],"themselves":[41],"nor":[42],"upon":[43],"site":[44],"metadata":[45,210],"su":[46],"ch":[47],"as":[48,203],"location":[49,180],"timestamps.":[51],"The":[52,160],"focus":[53],"this":[55],"paper":[56],"development":[60],"evaluation":[62],"such":[64],"representative,":[66],"interpolation-based":[67],"solution":[68],"quality.":[75],"We":[76,205,213],"call":[77],"our":[78],"method":[79],"SMART":[81],"method,":[82],"short":[83],"Simple":[85],"Mappings":[86],"Approximation":[89],"Regression":[91],"Time":[93],"series.":[94],"A":[95],"robust,":[96],"linear":[97,123],"mapping":[98],"determined":[100],"between":[101],"pairs":[105],"sites":[107,177,196,207],"over":[108],"representative":[110],"time":[111],"period":[112],"quadratic":[115],"estimate":[116,154],"error":[118],"derived":[120,167],"these":[122,225,235],"mappings.":[124],"These":[125],"mappings":[126,164],"combine":[127],"form":[129],"interpolator":[132],"outperforms":[134],"other":[135,166],"popular":[136],"interpolators":[137],"in":[138,142,227],"estimating":[139],"ground":[140,155],"truth":[141,156],"presence":[144],"bad":[146],"data,":[147],"can":[150,169],"be":[151],"used":[152],"assess":[158],"coefficients":[161],"measures":[168],"also":[170],"help":[171],"identify":[173,193,206],"problematic":[174,195],"sites,":[175],"including":[176],"having":[178],"incorrect":[179],"or":[181],"timestamp":[182],"metadata.":[183],"When":[184],"applied":[185],"real-world,":[188],"meteorological":[189],"set,":[191],"we":[192],"numerous":[194],"otherwise":[198],"have":[199,237],"been":[201],"flagged":[202],"bad.":[204],"which":[209],"incorrect.":[212],"believe":[214],"there":[216],"are":[217],"many":[218],"problems":[219,236],"with":[220],"real":[221],"sets":[223],"like":[224,233],"and,":[226],"absence":[229],"an":[231],"approach":[232,242],"ours,":[234],"largely":[238],"gone":[239],"unidentified.":[240],"Our":[241],"novel":[244],"simple":[247],"effective":[249],"way":[250],"it":[252,261],"accounts":[253],"spatial":[255],"temporal":[257],"variation,":[258],"addresses":[262],"more":[263],"than":[264],"just":[265]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}