{"id":"https://openalex.org/W2929358910","doi":"https://doi.org/10.1109/vast.2018.8802502","title":"Time Series Projection to Highlight Trends and Outliers","display_name":"Time Series Projection to Highlight Trends and Outliers","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2929358910","doi":"https://doi.org/10.1109/vast.2018.8802502","mag":"2929358910"},"language":"en","primary_location":{"id":"doi:10.1109/vast.2018.8802502","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2018.8802502","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Conference on Visual Analytics Science and Technology (VAST)","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/A5065218054","display_name":"Eren Cakmak","orcid":"https://orcid.org/0000-0002-1812-2271"},"institutions":[{"id":"https://openalex.org/I189712700","display_name":"University of Konstanz","ror":"https://ror.org/0546hnb39","country_code":"DE","type":"education","lineage":["https://openalex.org/I189712700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Eren Cakmak","raw_affiliation_strings":["Data Analysis and Visualization Group, University of Konstanz"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Analysis and Visualization Group, University of Konstanz","institution_ids":["https://openalex.org/I189712700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019671636","display_name":"Daniel Seebacher","orcid":"https://orcid.org/0000-0003-0097-5855"},"institutions":[{"id":"https://openalex.org/I189712700","display_name":"University of Konstanz","ror":"https://ror.org/0546hnb39","country_code":"DE","type":"education","lineage":["https://openalex.org/I189712700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Seebacher","raw_affiliation_strings":["Data Analysis and Visualization Group, University of Konstanz"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Analysis and Visualization Group, University of Konstanz","institution_ids":["https://openalex.org/I189712700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071098711","display_name":"Juri Buchm\u00fcller","orcid":"https://orcid.org/0000-0002-4713-911X"},"institutions":[{"id":"https://openalex.org/I189712700","display_name":"University of Konstanz","ror":"https://ror.org/0546hnb39","country_code":"DE","type":"education","lineage":["https://openalex.org/I189712700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Juri Buchmuller","raw_affiliation_strings":["Data Analysis and Visualization Group, University of Konstanz"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Analysis and Visualization Group, University of Konstanz","institution_ids":["https://openalex.org/I189712700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073919282","display_name":"Daniel A. Keim","orcid":"https://orcid.org/0000-0001-7966-9740"},"institutions":[{"id":"https://openalex.org/I189712700","display_name":"University of Konstanz","ror":"https://ror.org/0546hnb39","country_code":"DE","type":"education","lineage":["https://openalex.org/I189712700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel A. Keim","raw_affiliation_strings":["Data Analysis and Visualization Group, University of Konstanz"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Analysis and Visualization Group, University of Konstanz","institution_ids":["https://openalex.org/I189712700"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I189712700"],"apc_list":null,"apc_paid":null,"fwci":1.1689,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82378223,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"104","last_page":"105"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9912999868392944,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9535999894142151,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7558791637420654},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7541370391845703},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6585605144500732},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6334810853004456},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5262664556503296},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5159505009651184},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4787853956222534},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.4480102062225342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40171393752098083},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33087730407714844},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26659759879112244},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2620406746864319},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0700024962425232}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7558791637420654},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7541370391845703},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6585605144500732},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6334810853004456},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5262664556503296},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5159505009651184},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4787853956222534},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.4480102062225342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40171393752098083},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33087730407714844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26659759879112244},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2620406746864319},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0700024962425232},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/vast.2018.8802502","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2018.8802502","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Conference on Visual Analytics Science and Technology (VAST)","raw_type":"proceedings-article"},{"id":"pmh:oai:kops.uni-konstanz.de:123456789/45035","is_oa":false,"landing_page_url":"http://nbn-resolving.de/urn:nbn:de:bsz:352-2-lhh4jf6w9x756","pdf_url":null,"source":{"id":"https://openalex.org/S4306401487","display_name":"KOPS (University of Konstanz)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I189712700","host_organization_name":"University of Konstanz","host_organization_lineage":["https://openalex.org/I189712700"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2018 MC2). 2018","raw_type":"doc-type:conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2097481508","https://openalex.org/W2150231912"],"related_works":["https://openalex.org/W2068608913","https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2000145235","https://openalex.org/W2362367986","https://openalex.org/W348707231","https://openalex.org/W2571228289","https://openalex.org/W4280506488","https://openalex.org/W2064719069","https://openalex.org/W3041760129"],"abstract_inverted_index":{"The":[0,65,106],"goal":[1],"of":[2,20,57,87,103],"the":[3,15,24,31,43,58,83,101,127],"VAST":[4],"Challenge":[5,8],"2018":[6],"Mini":[7],"2":[9],"(MC":[10],"2)":[11],"was":[12],"to":[13,40,51,72,81,99,117],"unveil":[14],"possible":[16,121],"causes":[17,123],"and":[18,55,95,113,119,124],"effects":[19,125],"environmental":[21],"pollution":[22,122],"in":[23,126],"Boonsong":[25],"Lekagul":[26],"Wildlife":[27],"Preserve.":[28],"We":[29],"propose":[30],"ViCCEx":[32,66],"(Visual":[33],"Chemical":[34],"Contamination":[35],"Explorer)":[36],"system":[37,67],"that":[38],"enables":[39,116],"interactively":[41],"explore":[42,118],"sparse":[44],"multivariate":[45],"river":[46],"network":[47],"sensor":[48,60,93],"reading":[49,61],"dataset":[50],"identify":[52,120],"characteristics,":[53],"trends,":[54],"outliers":[56],"different":[59,88],"locations":[62],"over":[63],"time.":[64],"uses":[68],"a":[69,77],"t-SNE":[70],"projection":[71],"display":[73],"an":[74],"overview":[75],"visualization,":[76],"sampling":[78,85],"strategy":[79],"view":[80],"highlight":[82,100],"overall":[84],"strategies":[86],"chemical":[89,104],"measurements":[90],"at":[91],"each":[92],"location,":[94],"various":[96],"extracted":[97],"statistics":[98],"evolution":[102],"measurements.":[105],"three":[107],"views":[108],"are":[109],"connected":[110],"via":[111],"linking":[112],"brushing,":[114],"which":[115],"preserve.":[128]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}