{"id":"https://openalex.org/W2218451112","doi":"https://doi.org/10.1177/2053951715602495","title":"Big Data and the danger of being precisely inaccurate","display_name":"Big Data and the danger of being precisely inaccurate","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2218451112","doi":"https://doi.org/10.1177/2053951715602495","mag":"2218451112"},"language":"en","primary_location":{"id":"doi:10.1177/2053951715602495","is_oa":true,"landing_page_url":"https://doi.org/10.1177/2053951715602495","pdf_url":"https://journals.sagepub.com/doi/pdf/10.1177/2053951715602495","source":{"id":"https://openalex.org/S2736409588","display_name":"Big Data & Society","issn_l":"2053-9517","issn":["2053-9517"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data & Society","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals.sagepub.com/doi/pdf/10.1177/2053951715602495","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002809454","display_name":"Daniel A. McFarland","orcid":"https://orcid.org/0000-0002-6805-0798"},"institutions":[{"id":"https://openalex.org/I4210089246","display_name":"Hearst (United States)","ror":"https://ror.org/006s3gt16","country_code":"US","type":"company","lineage":["https://openalex.org/I4210089246"]},{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel A McFarland","raw_affiliation_strings":["Hearst Corporation, New York, NY, USA","Stanford University, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hearst Corporation, New York, NY, USA","institution_ids":["https://openalex.org/I4210089246"]},{"raw_affiliation_string":"Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072764324","display_name":"H. Richard McFarland","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089246","display_name":"Hearst (United States)","ror":"https://ror.org/006s3gt16","country_code":"US","type":"company","lineage":["https://openalex.org/I4210089246"]},{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H Richard McFarland","raw_affiliation_strings":["Hearst Corporation, New York, NY, USA","Stanford University, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hearst Corporation, New York, NY, USA","institution_ids":["https://openalex.org/I4210089246"]},{"raw_affiliation_string":"Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":800,"currency":"USD","value_usd":800},"apc_paid":{"value":800,"currency":"USD","value_usd":800},"fwci":2.1708,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.87979557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"2","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9988999962806702,"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":0.9988999962806702,"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/T10574","display_name":"Crime Patterns and Interventions","score":0.9383000135421753,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T13398","display_name":"Data Analysis with R","score":0.9323999881744385,"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/big-data","display_name":"Big data","score":0.8079507350921631},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6865320205688477},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.6724610924720764},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.6142278909683228},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.48759618401527405},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.485318124294281},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.47900885343551636},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.44538936018943787},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.41321444511413574},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2515435516834259},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13669991493225098}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.8079507350921631},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6865320205688477},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.6724610924720764},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.6142278909683228},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.48759618401527405},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.485318124294281},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.47900885343551636},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.44538936018943787},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.41321444511413574},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2515435516834259},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13669991493225098},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1177/2053951715602495","is_oa":true,"landing_page_url":"https://doi.org/10.1177/2053951715602495","pdf_url":"https://journals.sagepub.com/doi/pdf/10.1177/2053951715602495","source":{"id":"https://openalex.org/S2736409588","display_name":"Big Data & Society","issn_l":"2053-9517","issn":["2053-9517"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data & Society","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:60092d05707044b8b9d276d242f7057d","is_oa":true,"landing_page_url":"https://doaj.org/article/60092d05707044b8b9d276d242f7057d","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":"Big Data & Society, Vol 2 (2015)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1177/2053951715602495","is_oa":true,"landing_page_url":"https://doi.org/10.1177/2053951715602495","pdf_url":"https://journals.sagepub.com/doi/pdf/10.1177/2053951715602495","source":{"id":"https://openalex.org/S2736409588","display_name":"Big Data & Society","issn_l":"2053-9517","issn":["2053-9517"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data & Society","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2218451112.pdf"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W245051506","https://openalex.org/W1499618787","https://openalex.org/W1977186326","https://openalex.org/W2012921801","https://openalex.org/W2036207307","https://openalex.org/W2061975354","https://openalex.org/W2068181924","https://openalex.org/W2111002549","https://openalex.org/W2112257737","https://openalex.org/W2117239687","https://openalex.org/W2168345670","https://openalex.org/W2461826015","https://openalex.org/W3102647957","https://openalex.org/W3126019886","https://openalex.org/W4241134930","https://openalex.org/W4243838916"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4381328000","https://openalex.org/W4247566972","https://openalex.org/W2109147503","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2322581019","https://openalex.org/W2103779230"],"abstract_inverted_index":{"Social":[0],"scientists":[1],"and":[2],"data":[3,16,29,43,93,109,118,125,136],"analysts":[4,57],"are":[5,18,95,114],"increasingly":[6],"making":[7],"use":[8],"of":[9,34,51,61,103,134,146],"Big":[10,80],"Data":[11,81],"in":[12,91],"their":[13],"analyses.":[14],"These":[15,138],"sets":[17,44],"often":[19],"\u201cfound":[20],"data\u201d":[21],"arising":[22],"from":[23],"purely":[24],"observational":[25,135],"sources":[26],"rather":[27],"than":[28],"derived":[30],"under":[31],"strict":[32],"rules":[33],"a":[35,58,123],"statistically":[36],"designed":[37],"experiment.":[38],"However,":[39],"since":[40],"these":[41],"large":[42,117],"easily":[45,96],"meet":[46],"the":[47,92,100,104,108,144,147],"sample":[48],"size":[49],"requirements":[50],"most":[52,76],"statistical":[53,71],"procedures,":[54],"they":[55,64],"give":[56],"false":[59],"sense":[60],"security":[62],"as":[63],"proceed":[65],"to":[66,84,99,128,142],"focus":[67],"on":[68,79,116],"employing":[69,122],"traditional":[70],"methods.":[72],"We":[73],"explain":[74],"how":[75],"analyses":[77,113],"performed":[78,115],"today":[82],"lead":[83],"\u201cprecisely":[85],"inaccurate\u201d":[86],"results":[87,105],"that":[88],"hide":[89],"biases":[90],"but":[94],"overlooked":[97],"due":[98],"enhanced":[101],"significance":[102],"created":[106],"by":[107],"size.":[110],"Before":[111],"any":[112],"sets,":[119],"we":[120],"recommend":[121],"simple":[124],"segmentation":[126],"technique":[127],"control":[129],"for":[130],"some":[131],"major":[132],"components":[133],"biases.":[137],"segments":[139],"will":[140],"help":[141],"improve":[143],"accuracy":[145],"results.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":5},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}