{"id":"https://openalex.org/W2972323357","doi":"https://doi.org/10.1109/tvcg.2019.2934801","title":"Measures of the Benefit of Direct Encoding of Data Deltas for Data Pair Relation Perception","display_name":"Measures of the Benefit of Direct Encoding of Data Deltas for Data Pair Relation Perception","publication_year":2019,"publication_date":"2019-09-13","ids":{"openalex":"https://openalex.org/W2972323357","doi":"https://doi.org/10.1109/tvcg.2019.2934801","mag":"2972323357","pmid":"https://pubmed.ncbi.nlm.nih.gov/31536003"},"language":"en","primary_location":{"id":"doi:10.1109/tvcg.2019.2934801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2019.2934801","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063629557","display_name":"Christine Nothelfer","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Christine Nothelfer","raw_affiliation_strings":["Northwestern University"],"affiliations":[{"raw_affiliation_string":"Northwestern University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043405353","display_name":"Steven Franconeri","orcid":"https://orcid.org/0000-0001-5244-9764"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Steven Franconeri","raw_affiliation_strings":["Northwestern University"],"affiliations":[{"raw_affiliation_string":"Northwestern University","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5063629557"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.822,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.88714779,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"26","issue":"1","first_page":"311","last_page":"320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9988999962806702,"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":0.9988999962806702,"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/T10427","display_name":"Visual perception and processing mechanisms","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7534801363945007},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.7192220687866211},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6304918527603149},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.5754386782646179},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5363404154777527},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39104729890823364},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3269098997116089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.268287718296051}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7534801363945007},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7192220687866211},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6304918527603149},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.5754386782646179},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5363404154777527},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39104729890823364},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3269098997116089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.268287718296051},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tvcg.2019.2934801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2019.2934801","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:31536003","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31536003","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}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W110349276","https://openalex.org/W1969556630","https://openalex.org/W1971781829","https://openalex.org/W2004040569","https://openalex.org/W2017521531","https://openalex.org/W2017756939","https://openalex.org/W2023534772","https://openalex.org/W2026669101","https://openalex.org/W2030031014","https://openalex.org/W2030246490","https://openalex.org/W2031731579","https://openalex.org/W2049012614","https://openalex.org/W2060883949","https://openalex.org/W2070664725","https://openalex.org/W2106289661","https://openalex.org/W2117470435","https://openalex.org/W2132153787","https://openalex.org/W2132881639","https://openalex.org/W2144024567","https://openalex.org/W2151523458","https://openalex.org/W2153581683","https://openalex.org/W2157258520","https://openalex.org/W2300653232","https://openalex.org/W2529842378","https://openalex.org/W2785608539","https://openalex.org/W4230072782","https://openalex.org/W4242372420","https://openalex.org/W4253237286","https://openalex.org/W4294214781"],"related_works":["https://openalex.org/W2013728941","https://openalex.org/W4225274103","https://openalex.org/W2154046714","https://openalex.org/W2579659702","https://openalex.org/W2189613078","https://openalex.org/W1574055964","https://openalex.org/W2923661510","https://openalex.org/W2542318691","https://openalex.org/W2547096368","https://openalex.org/W2586219255"],"abstract_inverted_index":{"The":[0],"power":[1],"of":[2,11,20,54,66,109,155,170,177,195,207,219,232,244,266,285,296,333,365],"data":[3,13,27,46,57,110,156,221,268,299,315,343],"visualization":[4,89],"is":[5,37,60,84,272,345],"not":[6,357],"to":[7,16,33,38,62,80,87,119,151,167,204,229,241,256,282,328],"convey":[8],"absolute":[9,359],"values":[10,116,125,157,344],"individual":[12,56,314,342],"points,":[14,316],"but":[15,361],"allow":[17],"the":[18,41,52,55,97,105,115,121,124,147,164,168,178,187,193,201,230,242,250,253,258,273,283,322,331,350],"exploration":[19],"relations":[21,36,106,297],"(increases":[22],"or":[23,237],"decreases":[24],"in":[25,76,99,139,189,214],"a":[26,67,88,153,159,171,215,233,245,262,286],"value)":[28],"among":[29,175],"them.":[30],"One":[31],"approach":[32,50],"highlighting":[34],"these":[35],"explicitly":[39,127],"encode":[40],"numeric":[42],"differences":[43,75],"(deltas)":[44],"between":[45,107,123,298,313,368],"values.":[47,370],"Because":[48],"this":[49],"removes":[51],"context":[53],"values,":[58,111,360],"it":[59,70,83],"important":[61],"measure":[63],"how":[64],"much":[65],"performance":[68],"improvement":[69],"actually":[71],"offers,":[72],"especially":[73],"across":[74,129,278],"encodings":[77,135,138],"and":[78,131,181,317,336,348],"tasks,":[79,94],"ensure":[81],"that":[82,355],"worth":[85],"adding":[86],"design.":[90],"Across":[91,290],"3":[92],"different":[93],"we":[95,182],"measured":[96,183],"increase":[98,188],"visual":[100,133,294],"processing":[101,184,295],"efficiency":[102,185],"for":[103,341,352],"judging":[104],"pairs":[108,176,196,222,236,269,301],"from":[112,186,326],"when":[113,120,305],"only":[114,358],"were":[117,126],"shown,":[118],"deltas":[122,309],"encoded,":[128],"position":[130],"length":[132],"feature":[134],"(and":[136],"slope":[137],"Experiments":[140],"1":[141],"&":[142],"2).":[143],"In":[144,198,249],"Experiment":[145,199],"1,":[146],"participant's":[148],"task":[149,202,254,323],"was":[150,203,211,255,302],"locate":[152],"pair":[154],"with":[158],"given":[160],"relation":[161,209,339],"(e.g.,":[162,223,270],"Find":[163],"'small":[165,227,280],"bar":[166,228,240,275,281,334],"left":[169,231,243,284],"tall":[172,234,287],"bar'":[173,235,247,288],"pair)":[174],"opposite":[179],"relation,":[180],"response":[190],"times":[191],"as":[192,308],"number":[194],"increased.":[197],"2,":[200],"judge":[205],"which":[206],"two":[208],"types":[210],"more":[212,226,238],"prevalent":[213],"briefly":[216,263],"presented":[217,264],"display":[218,265],"10":[220],"Are":[224],"there":[225],"'tall":[239],"small":[246],"pairs?).":[248,289],"final":[251],"experiment,":[252],"estimate":[257],"average":[259,274],"delta":[260],"within":[261],"6":[267],"What":[271],"height":[276],"difference":[277],"all":[279,291],"three":[292],"experiments,":[293],"value":[300],"significantly":[303],"better":[304],"directly":[306],"encoded":[307],"rather":[310],"than":[311],"implicitly":[312],"varied":[318],"substantially":[319],"depending":[320],"on":[321],"(improvement":[324],"ranged":[325],"25%":[327],"95%).":[329],"Considering":[330],"ubiquity":[332],"charts":[335],"dot":[337],"plots,":[338],"perception":[340],"highly":[346],"inefficient,":[347],"confirms":[349],"need":[351],"alternative":[353],"designs":[354],"provide":[356],"also":[362],"direct":[363],"encoding":[364],"critical":[366],"relationships":[367],"those":[369]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}