{"id":"https://openalex.org/W4297336528","doi":"https://doi.org/10.1109/tvcg.2022.3209426","title":"Studying Early Decision Making with Progressive Bar Charts","display_name":"Studying Early Decision Making with Progressive Bar Charts","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4297336528","doi":"https://doi.org/10.1109/tvcg.2022.3209426","pmid":"https://pubmed.ncbi.nlm.nih.gov/36166544"},"language":"en","primary_location":{"id":"doi:10.1109/tvcg.2022.3209426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2022.3209426","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://inria.hal.science/hal-03738461/document","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101922351","display_name":"Ameya Patil","orcid":"https://orcid.org/0000-0002-9743-4264"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ameya Patil","raw_affiliation_strings":["University of Washington, Seattle, USA","Paul G. Allen School of Computer Science and Engineering [Seattle] (Paul G. Allen Center, Box 352350, 185 E Stevens Way NE, Seattle, WA 98195-2350 - United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, USA","institution_ids":["https://openalex.org/I201448701","https://openalex.org/I58610484"]},{"raw_affiliation_string":"Paul G. Allen School of Computer Science and Engineering [Seattle] (Paul G. Allen Center, Box 352350, 185 E Stevens Way NE, Seattle, WA 98195-2350 - United States)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040197934","display_name":"Ga\u00eblle Richer","orcid":"https://orcid.org/0000-0002-7556-1668"},"institutions":[{"id":"https://openalex.org/I4210126360","display_name":"Centre Inria de Saclay","ror":"https://ror.org/0315e5x55","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210126360"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Gaelle Richer","raw_affiliation_strings":["Inria &amp; Universite&#x00B4; Paris-Saclay, France"],"raw_orcid":"https://orcid.org/0000-0002-7556-1668","affiliations":[{"raw_affiliation_string":"Inria &amp; Universite&#x00B4; Paris-Saclay, France","institution_ids":["https://openalex.org/I4210126360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109437922","display_name":"Christopher Jermaine","orcid":null},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Jermaine","raw_affiliation_strings":["Rice University, USA","Rice University [Houston] (P.O. Box 1892, Houston, Texas 77251-1892 - United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rice University, USA","institution_ids":["https://openalex.org/I74775410"]},{"raw_affiliation_string":"Rice University [Houston] (P.O. Box 1892, Houston, Texas 77251-1892 - United States)","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006087928","display_name":"Dominik Moritz","orcid":"https://orcid.org/0000-0002-3110-1053"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dominik Moritz","raw_affiliation_strings":["Carnegie Mellon University, USA","CMU - Carnegie Mellon University [Pittsburgh] (5000 Forbes Ave, Pittsburgh, PA 15213 - United States)"],"raw_orcid":"https://orcid.org/0000-0002-3110-1053","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"CMU - Carnegie Mellon University [Pittsburgh] (5000 Forbes Ave, Pittsburgh, PA 15213 - United States)","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060725233","display_name":"Jean\u2010Daniel Fekete","orcid":"https://orcid.org/0000-0003-3770-8726"},"institutions":[{"id":"https://openalex.org/I4210126360","display_name":"Centre Inria de Saclay","ror":"https://ror.org/0315e5x55","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210126360"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Daniel Fekete","raw_affiliation_strings":["Inria &amp; Universite&#x00B4; Paris-Saclay, France"],"raw_orcid":"https://orcid.org/0000-0003-3770-8726","affiliations":[{"raw_affiliation_string":"Inria &amp; Universite&#x00B4; Paris-Saclay, France","institution_ids":["https://openalex.org/I4210126360"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0767,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.77991676,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"29","issue":"1","first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10799","display_name":"Data Visualization and Analytics","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13398","display_name":"Data Analysis with R","score":0.980400025844574,"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/bar-chart","display_name":"Bar chart","score":0.9112784266471863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.814984142780304},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.7372617721557617},{"id":"https://openalex.org/keywords/pie-chart","display_name":"Pie chart","score":0.6523301005363464},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.6434170007705688},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.5324813723564148},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.5291137099266052},{"id":"https://openalex.org/keywords/bar","display_name":"Bar (unit)","score":0.513810932636261},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4700031876564026},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4185103178024292},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4147641062736511},{"id":"https://openalex.org/keywords/creative-visualization","display_name":"Creative visualization","score":0.41403627395629883},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27266693115234375},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09403061866760254}],"concepts":[{"id":"https://openalex.org/C61122496","wikidata":"https://www.wikidata.org/wiki/Q1124595","display_name":"Bar chart","level":2,"score":0.9112784266471863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.814984142780304},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.7372617721557617},{"id":"https://openalex.org/C205208641","wikidata":"https://www.wikidata.org/wiki/Q273404","display_name":"Pie chart","level":2,"score":0.6523301005363464},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.6434170007705688},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5324813723564148},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.5291137099266052},{"id":"https://openalex.org/C188721877","wikidata":"https://www.wikidata.org/wiki/Q103510","display_name":"Bar (unit)","level":2,"score":0.513810932636261},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4700031876564026},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4185103178024292},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4147641062736511},{"id":"https://openalex.org/C14669888","wikidata":"https://www.wikidata.org/wiki/Q4014850","display_name":"Creative visualization","level":3,"score":0.41403627395629883},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27266693115234375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09403061866760254},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tvcg.2022.3209426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2022.3209426","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics","raw_type":"journal-article"},{"id":"pmid:36166544","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36166544","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on visualization and computer graphics","raw_type":null},{"id":"pmh:oai:HAL:hal-03738461v2","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-03738461","pdf_url":"https://inria.hal.science/hal-03738461/document","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics, 2023, 29 (1), pp.407-417. &#x27E8;10.1109/TVCG.2022.3209426&#x27E9;","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-03738461v2","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-03738461","pdf_url":"https://inria.hal.science/hal-03738461/document","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics, 2023, 29 (1), pp.407-417. &#x27E8;10.1109/TVCG.2022.3209426&#x27E9;","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4297336528.pdf"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W884650706","https://openalex.org/W1480884888","https://openalex.org/W1601042374","https://openalex.org/W1881224552","https://openalex.org/W1976365965","https://openalex.org/W1982261337","https://openalex.org/W1989505216","https://openalex.org/W1998908151","https://openalex.org/W2002544066","https://openalex.org/W2005534705","https://openalex.org/W2010759743","https://openalex.org/W2041411104","https://openalex.org/W2061562960","https://openalex.org/W2062989416","https://openalex.org/W2069228960","https://openalex.org/W2070664725","https://openalex.org/W2084367271","https://openalex.org/W2103484089","https://openalex.org/W2104839312","https://openalex.org/W2106458620","https://openalex.org/W2108230739","https://openalex.org/W2115018524","https://openalex.org/W2123381087","https://openalex.org/W2126728600","https://openalex.org/W2138722877","https://openalex.org/W2158604298","https://openalex.org/W2169155183","https://openalex.org/W2294212155","https://openalex.org/W2296677182","https://openalex.org/W2398514781","https://openalex.org/W2398599047","https://openalex.org/W2421547754","https://openalex.org/W2512646345","https://openalex.org/W2602567987","https://openalex.org/W2611375157","https://openalex.org/W2617963188","https://openalex.org/W2622662334","https://openalex.org/W2790071679","https://openalex.org/W2795875919","https://openalex.org/W2795915595","https://openalex.org/W2811283511","https://openalex.org/W2888554701","https://openalex.org/W2891628559","https://openalex.org/W2924001750","https://openalex.org/W2941366772","https://openalex.org/W2941489991","https://openalex.org/W2948467154","https://openalex.org/W2950627632","https://openalex.org/W2965571318","https://openalex.org/W2969788738","https://openalex.org/W3030671780","https://openalex.org/W3030927997","https://openalex.org/W3120225869","https://openalex.org/W3204797703","https://openalex.org/W4226149098","https://openalex.org/W4230704549","https://openalex.org/W4232345992","https://openalex.org/W4233886011","https://openalex.org/W4237375617","https://openalex.org/W4249267923","https://openalex.org/W6631275681"],"related_works":["https://openalex.org/W2970848727","https://openalex.org/W4254627246","https://openalex.org/W4243489664","https://openalex.org/W1499232172","https://openalex.org/W2905210242","https://openalex.org/W4236230270","https://openalex.org/W3009603321","https://openalex.org/W2101830037","https://openalex.org/W4379390844","https://openalex.org/W2795915595"],"abstract_inverted_index":{"We":[0,138,161,203],"conduct":[1],"a":[2,12,232],"user":[3,9,163,176],"study":[4,140],"to":[5,55,79,98,100,132,216],"quantify":[6],"and":[7,32,50,71,93,107,149,175,187,225],"compare":[8],"performance":[10,164],"for":[11,234],"value":[13],"comparison":[14],"task":[15],"using":[16,150,193],"four":[17,141],"bar":[18,37,128,143,208,217],"chart":[19,144,209],"designs,":[20],"where":[21],"the":[22,25,45,57,101,122,133,167,197,201,226],"bars":[23],"show":[24,180],"mean":[26,85],"values":[27,125],"of":[28,44,63,124,135,169,196,200],"data":[29,92,159],"loaded":[30],"progressively":[31],"updated":[33],"every":[34],"second":[35],"(progressive":[36],"charts).":[38],"Progressive":[39],"visualization":[40,46,67],"divides":[41],"different":[42],"stages":[43],"pipeline-data":[47],"loading,":[48],"processing,":[49],"visualization-into":[51],"iterative":[52],"animated":[53,66],"steps":[54],"limit":[56],"latency":[58],"when":[59],"loading":[60],"large":[61],"amounts":[62],"data.":[64],"An":[65],"appearing":[68],"quickly,":[69],"unfolding,":[70],"getting":[72],"more":[73],"accurate":[74,188],"with":[75,190,211,219,236],"time,":[76,174],"enables":[77],"users":[78,106,183],"make":[80,185],"early":[81,186],"decisions.":[82,111],"However,":[83],"intermediate":[84],"estimates":[86],"are":[87],"computed":[88],"only":[89,194,212,220],"on":[90,156,166],"partial":[91],"may":[94],"not":[95],"have":[96],"time":[97],"converge":[99],"true":[102],"means,":[103],"potentially":[104],"misleading":[105],"resulting":[108],"in":[109,126,130,223],"incorrect":[110],"To":[112],"address":[113],"this":[114],"issue,":[115],"we":[116,229],"propose":[117],"two":[118],"new":[119],"designs":[120,235],"visualizing":[121],"history":[123],"progressive":[127,142],"charts,":[129],"addition":[131],"use":[134],"confidence":[136,147,154,221],"intervals.":[137],"comparatively":[139],"designs:":[145],"with/without":[146,153],"intervals,":[148,155],"near-history":[151,213],"representation":[152],"three":[157],"realistic":[158],"distributions.":[160],"evaluate":[162],"based":[165],"percentage":[168],"correct":[170],"answers":[171],"(accuracy),":[172],"response":[173],"confidence.":[177],"Our":[178],"results":[179],"that,":[181],"overall,":[182],"can":[184],"decisions":[189],"92%":[191],"accuracy":[192],"18%":[195],"data,":[198],"regardless":[199],"design.":[202],"find":[204],"that":[205],"our":[206],"proposed":[207],"design":[210],"is":[214],"comparable":[215],"charts":[218],"intervals":[222],"performance,":[224],"qualitative":[227],"feedback":[228],"received":[230],"indicates":[231],"preference":[233],"history.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
