{"id":"https://openalex.org/W1984076134","doi":"https://doi.org/10.1145/1179622.1179810","title":"Dimensional compositing for visualizing high-dimensional dataset","display_name":"Dimensional compositing for visualizing high-dimensional dataset","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W1984076134","doi":"https://doi.org/10.1145/1179622.1179810","mag":"1984076134"},"language":"en","primary_location":{"id":"doi:10.1145/1179622.1179810","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1179622.1179810","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGGRAPH 2006 Research posters on   - SIGGRAPH '06","raw_type":"proceedings-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/A5055183973","display_name":"Pin Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pin Ren","raw_affiliation_strings":["Northwestern University****"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University****","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110052029","display_name":"Bruce Gooch","orcid":null},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bruce Gooch","raw_affiliation_strings":["Northwestern University****"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University****","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016365293","display_name":"Benjamin Watson","orcid":"https://orcid.org/0000-0002-3758-7357"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Watson","raw_affiliation_strings":["North Carolina State University,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina State University,","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.08263556,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"163","last_page":"163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9846000075340271,"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"}},"topics":[{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9846000075340271,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9839000105857849,"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/compositing","display_name":"Compositing","score":0.8930796980857849},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.675101637840271},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5168055295944214},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.38281673192977905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2796052396297455},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0887480080127716}],"concepts":[{"id":"https://openalex.org/C129315195","wikidata":"https://www.wikidata.org/wiki/Q1121886","display_name":"Compositing","level":3,"score":0.8930796980857849},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.675101637840271},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5168055295944214},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.38281673192977905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2796052396297455},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0887480080127716}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1179622.1179810","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1179622.1179810","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGGRAPH 2006 Research posters on   - SIGGRAPH '06","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2084961399"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2098628853","https://openalex.org/W4242350840","https://openalex.org/W2363688420","https://openalex.org/W2488155886","https://openalex.org/W2052474806","https://openalex.org/W2177745862","https://openalex.org/W2997387466","https://openalex.org/W562517220","https://openalex.org/W4253284636"],"abstract_inverted_index":{"The":[0],"scalability":[1,28],"problem":[2],"in":[3],"high-dimensional":[4,53],"dataset":[5],"visualization":[6,19],"has":[7],"been":[8],"a":[9,17,31],"difficult":[10],"problem.":[11],"In":[12,46],"this":[13,27],"poster":[14],"we":[15,55],"propose":[16],"novel":[18],"technique":[20],"which":[21],"utilizes":[22],"image":[23],"compositing":[24,40],"to":[25,35,48],"solve":[26],"problem,":[29],"and":[30,41,60],"cube-like":[32],"visual":[33],"metaphor":[34],"integrate":[36],"the":[37,51],"new":[38],"dimensional":[39],"traditional":[42],"parallel":[43],"co-ordinate":[44],"visualization.":[45],"order":[47],"effectively":[49],"visualize":[50],"complex":[52],"datasets,":[54],"also":[56],"developed":[57],"supporting":[58],"interaction":[59],"navigation":[61],"functionalities.":[62]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
