{"id":"https://openalex.org/W1999976769","doi":"https://doi.org/10.1145/2702123.2702217","title":"The Effects of Representation and Juxtaposition on Graphical Perception of Matrix Visualization","display_name":"The Effects of Representation and Juxtaposition on Graphical Perception of Matrix Visualization","publication_year":2015,"publication_date":"2015-04-17","ids":{"openalex":"https://openalex.org/W1999976769","doi":"https://doi.org/10.1145/2702123.2702217","mag":"1999976769"},"language":"en","primary_location":{"id":"doi:10.1145/2702123.2702217","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2702123.2702217","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2702123.2702217","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/2702123.2702217","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100340834","display_name":"Xiaotong Liu","orcid":"https://orcid.org/0000-0002-3618-0168"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiaotong Liu","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA","The Ohio State University, Columbus, OH, USA.;"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA.;","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065630217","display_name":"Han\u2010Wei Shen","orcid":"https://orcid.org/0000-0002-1211-2320"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Han-Wei Shen","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA","The Ohio State University, Columbus, OH, USA.;"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA.;","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100340834"],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":2.0591,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91246388,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"269","last_page":"278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9997000098228455,"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":0.9997000098228455,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9661999940872192,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7558244466781616},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.7443252801895142},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6741933822631836},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6411263942718506},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5506269335746765},{"id":"https://openalex.org/keywords/adjacency-list","display_name":"Adjacency list","score":0.5412949323654175},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5270956754684448},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5267398357391357},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5018737316131592},{"id":"https://openalex.org/keywords/matrix-representation","display_name":"Matrix representation","score":0.4384498596191406},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.422615647315979},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3340839147567749},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31020259857177734},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.16540184617042542},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.08184358477592468}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7558244466781616},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.7443252801895142},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6741933822631836},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6411263942718506},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5506269335746765},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.5412949323654175},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5270956754684448},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5267398357391357},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5018737316131592},{"id":"https://openalex.org/C103275481","wikidata":"https://www.wikidata.org/wiki/Q6787889","display_name":"Matrix representation","level":3,"score":0.4384498596191406},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.422615647315979},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3340839147567749},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31020259857177734},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.16540184617042542},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.08184358477592468},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2702123.2702217","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2702123.2702217","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2702123.2702217","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/2702123.2702217","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2702123.2702217","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2702123.2702217","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2776741540","display_name":null,"funder_award_id":"IIS- 1017635 and IIS-1065025","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3166479540","display_name":"SCIDAC INSTITUTE FOR ULTRASCALE VISUALIZATION","funder_award_id":"FC02-06ER25779","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G3867289339","display_name":null,"funder_award_id":"IIS-1065025","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5438514253","display_name":"GV: Small: Collaborative Research: An Information-Theoretic Framework for Large-Scale Data Analysis and Visualization","funder_award_id":"1017635","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G936771120","display_name":null,"funder_award_id":"DOESC0005036 and DE-FC02-06ER25779","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1999976769.pdf","grobid_xml":"https://content.openalex.org/works/W1999976769.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1499655453","https://openalex.org/W1557977305","https://openalex.org/W1588957466","https://openalex.org/W1605018553","https://openalex.org/W1971781829","https://openalex.org/W1996136679","https://openalex.org/W2030246490","https://openalex.org/W2035324138","https://openalex.org/W2039163945","https://openalex.org/W2052209137","https://openalex.org/W2057828920","https://openalex.org/W2059018062","https://openalex.org/W2083009591","https://openalex.org/W2101771332","https://openalex.org/W2103140580","https://openalex.org/W2103383236","https://openalex.org/W2108230739","https://openalex.org/W2108713782","https://openalex.org/W2109170454","https://openalex.org/W2111347866","https://openalex.org/W2112397756","https://openalex.org/W2116856566","https://openalex.org/W2128712108","https://openalex.org/W2143717026","https://openalex.org/W2144024567","https://openalex.org/W2144721682","https://openalex.org/W2157316473","https://openalex.org/W2165467901","https://openalex.org/W2610881169","https://openalex.org/W4244500165"],"related_works":["https://openalex.org/W4213150077","https://openalex.org/W2369410163","https://openalex.org/W2059018062","https://openalex.org/W2078477160","https://openalex.org/W1989103179","https://openalex.org/W1991172810","https://openalex.org/W2117632582","https://openalex.org/W4388347373","https://openalex.org/W2604585036","https://openalex.org/W125803343"],"abstract_inverted_index":{"Analyzing":[0],"multiple":[1],"networks":[2,32,151],"at":[3],"once":[4],"is":[5],"a":[6,34,49,131,138],"common":[7],"yet":[8],"difficult":[9],"task":[10],"in":[11,33,147],"many":[12],"domains.":[13],"Using":[14],"adjacency":[15,46],"matrices":[16,47,61,64],"for":[17,44,136],"this":[18],"purpose,":[19],"however,":[20],"can":[21],"be":[22],"effective":[23],"because":[24],"of":[25,51,58,70,141],"its":[26,145],"superior":[27],"ability":[28],"to":[29,85],"accommodate":[30],"dense":[31],"small":[35],"area.":[36],"We":[37,54],"evaluate":[38],"various":[39],"representations":[40,110],"and":[41,62,68,90,97,114,143],"juxtaposition":[42,83,102,117],"designs":[43,84],"visualizing":[45],"through":[48],"series":[50],"controlled":[52],"experiments.":[53],"investigate":[55],"the":[56,66,86,108,115,122],"effect":[57],"using":[59,152],"square":[60],"triangular":[63],"on":[65,75],"speed":[67],"accuracy":[69],"performing":[71],"graphical-perception":[72],"tasks.":[73],"Based":[74],"human":[76],"symmetric":[77],"perception,":[78],"we":[79,129],"propose":[80],"two":[81],"alternative":[82],"conventional":[87],"side-by-side":[88],"juxtaposition,":[89],"study":[91],"how":[92],"users":[93],"perform":[94,119],"visual":[95],"search":[96],"comparison":[98],"tasks":[99],"regarding":[100],"different":[101],"types.":[103],"Our":[104],"results":[105],"show":[106],"that":[107],"matrix":[109,116],"have":[111],"similar":[112],"performance,":[113],"types":[118],"differently.":[120],"With":[121],"design":[123],"guidelines":[124],"derived":[125],"from":[126],"our":[127],"studies,":[128],"present":[130],"compact":[132],"visualization":[133],"termed":[134],"TileMatrix":[135],"juxtaposing":[137],"large":[139],"number":[140],"matrices,":[142],"demonstrate":[144],"effectiveness":[146],"analyzing":[148],"multi-faceted,":[149],"time-varying":[150],"real-world":[153],"data.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
