{"id":"https://openalex.org/W2012059490","doi":"https://doi.org/10.1109/bigdata.2013.6691719","title":"DriveSense: Contextual handling of large-scale route map data for the automobile","display_name":"DriveSense: Contextual handling of large-scale route map data for the automobile","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W2012059490","doi":"https://doi.org/10.1109/bigdata.2013.6691719","mag":"2012059490"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2013.6691719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2013.6691719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Big Data","raw_type":"proceedings-article"},"type":"conference-paper","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/A5005194002","display_name":"Frederik Wiehr","orcid":"https://orcid.org/0000-0002-6560-3406"},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Frederik Wiehr","raw_affiliation_strings":["Saarland University, Germany","Saarland Univ., Saarbr\u00fccken, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saarland University, Germany","institution_ids":["https://openalex.org/I91712215"]},{"raw_affiliation_string":"Saarland Univ., Saarbr\u00fccken, Germany#TAB#","institution_ids":["https://openalex.org/I91712215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006232882","display_name":"Vidya Setlur","orcid":"https://orcid.org/0000-0003-3722-406X"},"institutions":[{"id":"https://openalex.org/I4210163771","display_name":"Tableau Software (United States)","ror":"https://ror.org/053v5e348","country_code":"US","type":"company","lineage":["https://openalex.org/I4210163771"]},{"id":"https://openalex.org/I72090969","display_name":"Nokia (United States)","ror":"https://ror.org/038km2573","country_code":"US","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I72090969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vidya Setlur","raw_affiliation_strings":["Nokia Research Center and Tableau Software, USA","Nokia Res. Center & Tableau Software, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Research Center and Tableau Software, USA","institution_ids":["https://openalex.org/I4210163771","https://openalex.org/I72090969"]},{"raw_affiliation_string":"Nokia Res. Center & Tableau Software, USA","institution_ids":["https://openalex.org/I4210163771","https://openalex.org/I72090969"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067212091","display_name":"Alark Joshi","orcid":"https://orcid.org/0000-0002-3180-8075"},"institutions":[{"id":"https://openalex.org/I76766440","display_name":"University of San Francisco","ror":"https://ror.org/029m7xn54","country_code":"US","type":"education","lineage":["https://openalex.org/I76766440"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alark Joshi","raw_affiliation_strings":["University of San Francisco, USA","University of San Francisco, San Francisco, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of San Francisco, USA","institution_ids":["https://openalex.org/I76766440"]},{"raw_affiliation_string":"University of San Francisco, San Francisco, CA, USA#TAB#","institution_ids":["https://openalex.org/I76766440"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"87","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9979000091552734,"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":0.9979000091552734,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8224866986274719},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.8147902488708496},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.7661720514297485},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.740611732006073},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.6557701230049133},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6306902170181274},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5420532822608948},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.481356680393219},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.4602263569831848},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.41653749346733093},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36495548486709595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29562318325042725},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.13060623407363892},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11996087431907654}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8224866986274719},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.8147902488708496},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.7661720514297485},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.740611732006073},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.6557701230049133},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6306902170181274},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5420532822608948},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.481356680393219},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.4602263569831848},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.41653749346733093},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36495548486709595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29562318325042725},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.13060623407363892},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11996087431907654},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bigdata.2013.6691719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2013.6691719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Big Data","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.711.4366","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.711.4366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.vidyasetlur.com/papers/drivesense.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.957.5305","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.957.5305","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.usfca.edu/%7Eapjoshi/papers/drivesense.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1539277370","https://openalex.org/W1980872084","https://openalex.org/W1986533012","https://openalex.org/W2006902234","https://openalex.org/W2019090719","https://openalex.org/W2049044499","https://openalex.org/W2079484408","https://openalex.org/W2093798436","https://openalex.org/W2117893272","https://openalex.org/W2165666226","https://openalex.org/W2187787545","https://openalex.org/W2233207476","https://openalex.org/W2294123372"],"related_works":["https://openalex.org/W2158984754","https://openalex.org/W3149127250","https://openalex.org/W2564956852","https://openalex.org/W4246764483","https://openalex.org/W2126824079","https://openalex.org/W2143428259","https://openalex.org/W4378086562","https://openalex.org/W2112083262","https://openalex.org/W4389880955","https://openalex.org/W2056189874"],"abstract_inverted_index":{"Automakers":[0],"are":[1,120],"increasingly":[2],"providing":[3],"connectivity":[4],"enhancements":[5],"for":[6,29,204,218,224],"vehicles":[7],"to":[8,15,19,35,146,229],"download":[9],"navigational":[10],"data,":[11],"as":[12,14,156,158,227],"well":[13,157],"upload":[16],"sensor":[17],"information":[18,33,61],"the":[20,30,49,58,65,69,79,106,112,137,141,147,151,154,159,162,165,181,191,213,219],"cloud.":[21],"Generally,":[22],"while":[23],"more":[24,76],"data":[25],"may":[26,74],"be":[27,36,43,75],"better,":[28],"driver":[31,119],"on-the-go,":[32],"needs":[34],"displayed":[37,145,221],"in":[38,123],"a":[39,109,118,124,130,172,196],"manner":[40],"that":[41,57,71,93,103,134,164,177,212],"can":[42,99],"comprehended":[44],"rather":[45],"quickly.":[46],"One":[47],"of":[48,60,68,108,117,153,161,184],"major":[50],"problems":[51],"with":[52,78,96],"visualizing":[53],"route":[54,185],"maps":[55,186],"is":[56,63,85,167],"amount":[59],"visualized":[62],"always":[64],"same":[66],"regardless":[67],"fact":[70],"an":[72,83],"individual":[73,84],"familiar":[77],"region":[80,163],"or":[81],"whether":[82],"driving":[86,168],"at":[87,207],"varying":[88,208],"speeds.":[89,231],"Research":[90],"has":[91],"shown":[92,194],"complex":[94],"visualizations":[95,183,206],"visual":[97,192,202],"clutter":[98,203,214],"cause":[100],"cognitive":[101],"overload":[102],"adversely":[104],"affects":[105],"performance":[107],"user.":[110],"Additionally,":[111],"attention":[113],"and":[114,140,210],"interaction":[115],"abilities":[116],"significantly":[121,216],"compromised":[122],"vehicular":[125],"environment.":[126],"We":[127,199],"propose":[128],"DriveSense,":[129],"context-sensitive":[131],"visualization":[132,143],"system":[133],"automatically":[135],"varies":[136],"GPS":[138],"updates":[139],"corresponding":[142],"being":[144],"user":[148,166,173],"based":[149],"on":[150,171],"speed":[152],"vehicle":[155],"familiarity":[160],"in.":[169],"Based":[170],"evaluation,":[174],"we":[175],"found":[176,211],"subjects":[178],"preferred":[179],"using":[180],"automatic":[182],"generated":[187],"by":[188,195,222],"DriveSense":[189,223],"than":[190],"representations":[193],"standard":[197],"GPS.":[198],"also":[200],"computed":[201],"our":[205],"speeds":[209,226],"was":[215],"less":[217],"routes":[220],"faster":[225],"compared":[228],"slower":[230]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}