{"id":"https://openalex.org/W2583780137","doi":"https://doi.org/10.1109/bigdata.2016.7840684","title":"Big data on a few pixels","display_name":"Big data on a few pixels","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2583780137","doi":"https://doi.org/10.1109/bigdata.2016.7840684","mag":"2583780137"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840684","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5063997221","display_name":"Uwe Jugel","orcid":"https://orcid.org/0000-0003-0722-4544"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"funder","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Uwe Jugel","raw_affiliation_strings":["Technische Universit\u00e4t Berlin, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006578340","display_name":"Zbigniew Jerzak","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132444","display_name":"Systems, Applications & Products in Data Processing (Germany)","ror":"https://ror.org/03dsc8d33","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210132444"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Zbigniew Jerzak","raw_affiliation_strings":["SAP SE Berlin/Walldorf, Germany"],"affiliations":[{"raw_affiliation_string":"SAP SE Berlin/Walldorf, Germany","institution_ids":["https://openalex.org/I4210132444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002413906","display_name":"Volker Markl","orcid":"https://orcid.org/0009-0009-0964-026X"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"funder","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Volker Markl","raw_affiliation_strings":["Technische Universit\u00e4t Berlin, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":66},"biblio":{"volume":null,"issue":null,"first_page":"895","last_page":"900"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9999,"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":0.9999,"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/T11106","display_name":"Data Management and Algorithms","score":0.9727,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9344,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5878745}],"concepts":[{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.8200301},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.81017596},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6060707},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5878745},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.5871883},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.53298396},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.5146502},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.46456066},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.42081413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3622198},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33448523},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.28589717},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.087287575},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840684","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":12,"referenced_works":["https://openalex.org/W1182426426","https://openalex.org/W1823329909","https://openalex.org/W1987968210","https://openalex.org/W2114566476","https://openalex.org/W2120422643","https://openalex.org/W2121418890","https://openalex.org/W2143545446","https://openalex.org/W2152922709","https://openalex.org/W2242977838","https://openalex.org/W2263651082","https://openalex.org/W2285670967","https://openalex.org/W4244857585"],"related_works":["https://openalex.org/W4387885925","https://openalex.org/W3162529344","https://openalex.org/W3095784589","https://openalex.org/W2594301978","https://openalex.org/W2527777278","https://openalex.org/W2379704676","https://openalex.org/W2378744544","https://openalex.org/W2373300491","https://openalex.org/W2147224006","https://openalex.org/W1212596013"],"abstract_inverted_index":{"Data":[0,32],"aggregation":[1],"techniques":[2],"help":[3],"to":[4,57,95],"reduce":[5],"large":[6],"data":[7,10,41,60,115],"volumes":[8],"in":[9,64,116],"visualization":[11,63,94],"systems":[12],"and":[13,74,85],"are":[14],"particularly":[15],"effective":[16],"when":[17],"incorporating":[18],"the":[19,23,30,37,45,62,80,92,97,103],"spatial":[20],"properties":[21,68],"of":[22,69],"final":[24],"visualization.":[25],"One":[26],"such":[27],"technique":[28],"is":[29],"Visualization-Driven":[31],"Aggregation":[33],"(VDDA)":[34],"that":[35],"models":[36],"pixel-level":[38],"overplotting":[39],"as":[40],"reduction":[42],"query":[43],"inside":[44],"database.":[46,119],"In":[47],"this":[48],"paper,":[49],"we":[50,72],"extend":[51],"VDDA":[52],"with":[53],"a":[54,117],"novel":[55],"approach":[56],"prepare":[58],"high-dimensional":[59],"for":[61,79,89,110],"chart":[65,83],"matrices.":[66],"Incorporating":[67],"human":[70],"perception,":[71],"introduce":[73],"formalize":[75],"visual":[76],"capacity":[77,105],"functions":[78,88,106],"most":[81],"common":[82],"types":[84],"use":[86],"these":[87],"automatically":[90],"configuring":[91],"best-perceivable":[93],"contain":[96],"acquired":[98],"data.":[99],"We":[100],"demonstrate":[101],"how":[102],"introduced":[104],"can":[107],"be":[108],"used":[109],"VDDA-precedent":[111],"pruning":[112],"using":[113],"real-world":[114],"relational":[118]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2583780137","counts_by_year":[],"updated_date":"2025-01-26T06:17:13.332670","created_date":"2017-02-10"}