{"id":"https://openalex.org/W4313483253","doi":"https://doi.org/10.48550/arxiv.2301.00002","title":"Evaluating Alternative Glyph Design for Showing Large-Magnitude-Range Quantum Spins","display_name":"Evaluating Alternative Glyph Design for Showing Large-Magnitude-Range Quantum Spins","publication_year":2022,"publication_date":"2022-12-25","ids":{"openalex":"https://openalex.org/W4313483253","doi":"https://doi.org/10.48550/arxiv.2301.00002"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2301.00002","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.00002","pdf_url":"https://arxiv.org/pdf/2301.00002","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2301.00002","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101334100","display_name":"Henan Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhao, Henan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076705483","display_name":"Garnett W. Bryant","orcid":"https://orcid.org/0000-0002-2232-0545"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bryant, Garnett W.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023695903","display_name":"Wesley Griffin","orcid":"https://orcid.org/0000-0002-3615-1463"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Griffin, Wesley","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028869229","display_name":"Judith E. Terrill","orcid":"https://orcid.org/0000-0002-4822-9264"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Terrill, Judith E.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100326425","display_name":"Jian Chen","orcid":"https://orcid.org/0000-0002-0123-5165"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jian","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101334100"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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":0.9560999870300293,"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":0.9560999870300293,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9318000078201294,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9046000242233276,"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":0.8686373233795166},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.7995458841323853},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7174014449119568},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.5755186080932617},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5720512270927429},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4606070816516876},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4391610026359558},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.41398629546165466},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.32538363337516785},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.325317919254303},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.264651358127594}],"concepts":[{"id":"https://openalex.org/C142816647","wikidata":"https://www.wikidata.org/wiki/Q5573018","display_name":"Glyph (data visualization)","level":3,"score":0.8686373233795166},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.7995458841323853},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7174014449119568},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.5755186080932617},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5720512270927429},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4606070816516876},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4391610026359558},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.41398629546165466},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.32538363337516785},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.325317919254303},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.264651358127594},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2301.00002","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.00002","pdf_url":"https://arxiv.org/pdf/2301.00002","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"doi:10.48550/arxiv.2301.00002","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2301.00002","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2301.00002","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.00002","pdf_url":"https://arxiv.org/pdf/2301.00002","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2350760135","https://openalex.org/W2090371563","https://openalex.org/W1972316918","https://openalex.org/W2151948537","https://openalex.org/W4312601913","https://openalex.org/W4212776738","https://openalex.org/W2786162233","https://openalex.org/W2964313340","https://openalex.org/W2350092425","https://openalex.org/W91638230"],"abstract_inverted_index":{"We":[0,42,174],"present":[1],"experimental":[2],"results":[3,100],"to":[4,59,95,122,162],"explore":[5],"a":[6,35,39,112,124],"form":[7],"of":[8,29,90,92,127,138],"bivariate":[9,51,152],"glyphs":[10,16,94,153],"for":[11,108,134,167,188],"representing":[12],"large-magnitude-range":[13],"vectors.":[14],"The":[15,54,71,129],"meet":[17],"two":[18,21,31,47,69],"conditions:":[19],"(1)":[20],"visual":[22,32],"dimensions":[23,33],"are":[24,115],"separable;":[25],"and":[26,185],"(2)":[27],"one":[28],"the":[30,50,76,87,103,147,151],"uses":[34],"categorical":[36,40,148],"representation":[37],"(e.g.,":[38],"colormap).":[41],"evaluate":[43],"how":[44],"much":[45],"these":[46],"conditions":[48],"determine":[49],"glyphs'":[52],"effectiveness.":[53],"first":[55,104],"experiment":[56,73],"asks":[57],"participants":[58,83],"perform":[60],"three":[61],"local":[62,109],"tasks":[63,81,110],"requiring":[64],"reading":[65],"no":[66],"more":[67],"than":[68],"glyphs.":[70],"second":[72,130],"scales":[74],"up":[75],"search":[77],"space":[78],"in":[79,150],"global":[80,136],"when":[82,111],"must":[84],"look":[85],"at":[86],"entire":[88],"scene":[89],"hundreds":[91],"vector":[93],"get":[96],"an":[97],"answer.":[98],"Our":[99],"support":[101],"that":[102,146],"condition":[105,131],"is":[106,119,132],"necessary":[107,133],"few":[113],"items":[114],"compared.":[116],"But":[117],"it":[118],"not":[120],"enough":[121],"understand":[123],"large":[125,171],"amount":[126],"data.":[128],"perceiving":[135],"structures":[137],"examining":[139],"very":[140],"complex":[141],"datasets.":[142],"Participants'":[143],"comments":[144],"reveal":[145],"features":[149],"trigger":[154],"emergent":[155],"optimal":[156],"viewers'":[157],"behaviors.":[158],"This":[159],"work":[160],"contributes":[161],"perceptually":[163],"accurate":[164],"glyph":[165],"representations":[166],"revealing":[168],"patterns":[169],"from":[170],"scientific":[172],"results.":[173],"release":[175],"source":[176],"code,":[177],"quantum":[178],"physics":[179],"data,":[180],"training":[181],"documents,":[182],"participants'":[183],"answers,":[184],"statistical":[186],"analyses":[187],"reproducible":[189],"science":[190],"https://osf.io/4xcf5/?view_only=94123139df9c4ac984a1e0df811cd580.":[191]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}