{"id":"https://openalex.org/W3203991651","doi":"https://doi.org/10.2312/vmv.20211378","title":"CoSi: Visual Comparison of Similarities in High-Dimensional Data Ensembles","display_name":"CoSi: Visual Comparison of Similarities in High-Dimensional Data Ensembles","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3203991651","doi":"https://doi.org/10.2312/vmv.20211378","mag":"3203991651"},"language":"en","primary_location":{"id":"doi:10.2312/vmv.20211378","is_oa":true,"landing_page_url":"https://doi.org/10.2312/vmv.20211378","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/vmv.20211378","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065470689","display_name":"Anja Heim","orcid":"https://orcid.org/0000-0002-3670-5403"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Heim, Anja","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109928029","display_name":"M. Eduard Gr\u00f6ller","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gr\u00f6ller, Eduard","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056214245","display_name":"Christoph Heinzl","orcid":"https://orcid.org/0000-0002-3173-8871"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heinzl, Christoph","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065470689"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1921,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49622549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.8598999977111816,"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":0.8598999977111816,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.7813000082969666,"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/computer-science","display_name":"Computer science","score":0.6542407274246216},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.44085240364074707},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4316723942756653},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3731837868690491},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3551129102706909}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6542407274246216},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.44085240364074707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4316723942756653},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3731837868690491},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3551129102706909}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2312/vmv.20211378","is_oa":true,"landing_page_url":"https://doi.org/10.2312/vmv.20211378","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.2312/vmv.20211378","is_oa":true,"landing_page_url":"https://doi.org/10.2312/vmv.20211378","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2906297595","https://openalex.org/W2959752065","https://openalex.org/W2960826148","https://openalex.org/W2744045245","https://openalex.org/W2888854077","https://openalex.org/W3170799558","https://openalex.org/W2868148645","https://openalex.org/W2888804504","https://openalex.org/W2964476476","https://openalex.org/W3043316363","https://openalex.org/W2906394293","https://openalex.org/W2296400371","https://openalex.org/W2966038578","https://openalex.org/W2898830931","https://openalex.org/W3022162528","https://openalex.org/W3126392892","https://openalex.org/W2947830256","https://openalex.org/W2958874938","https://openalex.org/W2158984754","https://openalex.org/W3037102231"],"abstract_inverted_index":{"Comparative":[0],"analysis":[1,130],"of":[2,6,12,19,37,51,93,127,131,153],"multivariate":[3],"datasets,":[4],"e.g.":[5],"advanced":[7],"materials":[8,30,56],"regarding":[9],"the":[10,84,87,91,125,143,147],"characteristics":[11],"internal":[13],"structures":[14],"(fibers,":[15],"pores,":[16],"etc.),":[17],"is":[18],"crucial":[20],"importance":[21],"in":[22,29,55,86,124],"various":[23],"scientific":[24],"disciplines.":[25],"Currently":[26],"domain":[27,44],"experts":[28,45,137],"science":[31,57],"mostly":[32],"rely":[33],"on":[34,83,96,142],"sequential":[35,151],"comparison":[36],"data":[38,54,144],"using":[39,105],"juxtaposition.":[40],"Our":[41,134],"work":[42,119],"assists":[43],"to":[46,78],"perform":[47],"detailed":[48,75],"comparative":[49,65,128],"analyses":[50],"large":[52],"ensemble":[53],"applications.":[58],"For":[59],"this":[60],"purpose,":[61],"we":[62],"developed":[63],"a":[64,70,80,106,121,139],"visualization":[66,76],"framework,":[67],"that":[68],"includes":[69],"tabular":[71],"overview":[72],"and":[73,101,145],"three":[74],"techniques":[77,104],"provide":[79],"holistic":[81],"view":[82],"similarities":[85],"ensemble.":[88],"We":[89],"demonstrate":[90],"applicability":[92],"our":[94,118],"framework":[95,135],"two":[97],"specific":[98],"usage":[99],"scenarios":[100],"verify":[102],"its":[103],"qualitative":[107],"user":[108],"study":[109],"with":[110,138],"12":[111],"material":[112,129],"experts.":[113],"The":[114],"insights":[115],"gained":[116],"from":[117],"represent":[120],"significant":[122],"advancement":[123],"field":[126],"high-dimensional":[132],"data.":[133,155],"provides":[136],"novel":[140],"perspective":[141],"eliminates":[146],"need":[148],"for":[149],"time-consuming":[150],"exploration":[152],"numerical":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}