{"id":"https://openalex.org/W2578845919","doi":"https://doi.org/10.2352/issn.2470-1173.2016.1.vda-509","title":"Visualizing Static Ensembles For Effective Shape and Data Comparison","display_name":"Visualizing Static Ensembles For Effective Shape and Data Comparison","publication_year":2016,"publication_date":"2016-02-14","ids":{"openalex":"https://openalex.org/W2578845919","doi":"https://doi.org/10.2352/issn.2470-1173.2016.1.vda-509","mag":"2578845919"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2016.1.vda-509","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2016.1.vda-509","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5026787396","display_name":"Lihua Hao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lihua Hao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013460936","display_name":"Christopher G. Healey","orcid":"https://orcid.org/0000-0002-2617-8638"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christopher G. Healey","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042522958","display_name":"Steffen A. Bass","orcid":"https://orcid.org/0000-0002-9451-0954"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Steffen A. Bass","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5059073433","display_name":"Hsuan-Ya Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hsuan-Ya Yu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5026787396"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.16441506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"28","issue":"1","first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9994000196456909,"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":0.9994000196456909,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.982699990272522,"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/T13398","display_name":"Data Analysis with R","score":0.9800999760627747,"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/glyph","display_name":"Glyph (data visualization)","score":0.8210973739624023},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.7494471669197083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7183636426925659},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6413866281509399},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5095574855804443},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4996762275695801},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4364608824253082},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.4182431995868683},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3819728195667267},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33149707317352295}],"concepts":[{"id":"https://openalex.org/C142816647","wikidata":"https://www.wikidata.org/wiki/Q5573018","display_name":"Glyph (data visualization)","level":3,"score":0.8210973739624023},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.7494471669197083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7183636426925659},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6413866281509399},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5095574855804443},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4996762275695801},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4364608824253082},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.4182431995868683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3819728195667267},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33149707317352295},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/issn.2470-1173.2016.1.vda-509","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2016.1.vda-509","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1497953515","https://openalex.org/W1923010118","https://openalex.org/W1966634937","https://openalex.org/W1977985708","https://openalex.org/W1999638922","https://openalex.org/W2045712730","https://openalex.org/W2048202762","https://openalex.org/W2055515775","https://openalex.org/W2085074505","https://openalex.org/W2107019423","https://openalex.org/W2109657057","https://openalex.org/W2121932969","https://openalex.org/W2124799063","https://openalex.org/W2141653286","https://openalex.org/W2148870222","https://openalex.org/W2156204145","https://openalex.org/W3025248509","https://openalex.org/W3129034625"],"related_works":["https://openalex.org/W2290503983","https://openalex.org/W2090371563","https://openalex.org/W2513074232","https://openalex.org/W2471951940","https://openalex.org/W2151948537","https://openalex.org/W2068134085","https://openalex.org/W2350092425","https://openalex.org/W2762277149","https://openalex.org/W4288754496","https://openalex.org/W1987416657"],"abstract_inverted_index":{"Ensembles":[0],"are":[1,21],"large,":[2],"multidimensional,":[3],"multivariate":[4],"datasets":[5],"generated":[6,67],"in":[7,94,152,204],"areas":[8],"like":[9],"physical":[10],"and":[11,39,47,116,127,138,150,154,198],"natural":[12],"science":[13],"to":[14,36,118,147,167,190,194,200],"study":[15],"real-world":[16],"phenomena.":[17],"Simulations":[18],"or":[19],"experiments":[20],"run":[22],"repeatedly":[23],"with":[24,60],"slightly":[25],"different":[26],"initial":[27],"parameters,":[28],"producing":[29],"members":[30,93,104],"of":[31,64,69,76,124,134,142,160],"the":[32,74,106,188],"ensemble.":[33],"The":[34],"need":[35],"compare":[37],"data":[38,128,155],"spatial":[40],"properties,":[41],"both":[42],"within":[43,105],"an":[44,83,135],"individual":[45,205],"member":[46,206],"across":[48,157],"multiple":[49,144],"members,":[50],"makes":[51],"analysis":[52],"challenging.":[53],"Initial":[54],"visualization":[55,110,133],"techniques":[56],"focused":[57],"on":[58],"ensembles":[59],"a":[61,120,131,140,158,168],"limited":[62],"number":[63],"members.":[65,162],"Others":[66],"overviews":[68],"larger":[70],"ensembles,":[71],"but":[72],"at":[73,179],"expense":[75],"aggregating":[77],"potentially":[78],"important":[79],"details.":[80],"We":[81,163],"propose":[82],"approach":[84,166],"that":[85,96],"combines":[86],"these":[87],"two":[88],"directions":[89],"by":[90,175],"automatically":[91],"clustering":[92,117],"ways":[95],"help":[97],"scientists":[98],"locate":[99],"interesting":[100],"subsets,":[101],"then":[102],"visualize":[103,201],"subset.":[107],"Our":[108,185],"ensemble":[109,136,161,173],"technique":[111],"includes:":[112],"(1)":[113],"octree":[114],"comparison":[115],"generate":[119],"hierarchical":[121],"level-of-detail":[122],"overview":[123],"inter-member":[125,196],"shape":[126,153],"similarity;":[129],"(2)":[130],"glyph-based":[132],"member;":[137],"(3)":[139],"method":[141],"combining":[143],"glyph":[145],"visualizations":[146],"highlight":[148],"similarities":[149],"differences":[151],"values":[156],"subset":[159],"apply":[164],"our":[165],"Relativistic":[169],"Heavy":[170],"Ion":[171],"Collider":[172],"collected":[174],"nuclear":[176],"physics":[177],"colleagues":[178],"Duke":[180],"University":[181],"studying":[182],"quantum":[183],"chromo-dynamics.":[184],"system":[186],"allows":[187],"physicists":[189],"interactively":[191],"choose":[192],"when":[193,199],"explore":[195],"relationships,":[197],"fine-grained":[202],"details":[203],"datasets.":[207]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}