Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/66786
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Silva, Ricardo Almeida | por |
dc.contributor.author | Pires, Joao Moura | por |
dc.contributor.author | Datia, Nuno | por |
dc.contributor.author | Santos, Maribel Yasmina | por |
dc.contributor.author | Martins, Bruno | por |
dc.contributor.author | Birra, Fernando | por |
dc.date.accessioned | 2020-09-04T15:16:41Z | - |
dc.date.issued | 2018 | - |
dc.identifier.isbn | 9781538672020 | - |
dc.identifier.uri | https://hdl.handle.net/1822/66786 | - |
dc.description.abstract | Crimes, forest fires, accidents, infectious diseases, human interactions with mobile devices (e.g., tweets) are being logged as spatiotemporal events. For each event, its geographic location, time and related attributes are known with high levels of detail (LoDs). The LoD plays a crucial role when analyzing data, enhancing the user's perception of phenomena. From one LoD to another, some patterns can be easily perceived or different patterns may be detected. Modeling phenomena at different LoDs is needed, as there is no exclusive LoD at which data can be analyzed.Current practices work mainly on a single LoD, driven by the analysts perception, ignoring the fact that the identification of the suitable LoDs is a key issue for pointing relevant patterns.This paper presents a Visual Analytics approach called VAST, that allows users to simultaneously inspect a phenomenon at different LoDs, helping them to see in what LoDs patterns emerge or in what LoDs the perception of the phenomenon is different. In this way, the analysis of vast amounts of spatiotemporal events is assisted, guiding the user in this process.The use of several synthetic and real datasets allowed the evaluation of VAST, which was able to suggest LoDs with different interesting spatiotemporal patterns and the type of expected patterns. | por |
dc.description.sponsorship | This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia MCTES, UID/CEC/04516/2013 (NOVA LINCS) and UID/CEC/00319/2013 (ALGORITMI), and COMPETE: POCI010145-FEDER007043 (ALGORITMI). | por |
dc.language.iso | eng | por |
dc.publisher | IEEE | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147279/PT | por |
dc.rights | restrictedAccess | por |
dc.subject | data visualisation | por |
dc.subject | spatiotemporal patterns | por |
dc.subject | multiple levels of detail | por |
dc.subject | visual analytics | por |
dc.title | Visualising hidden spatiotemporal patterns at multiple levels of detail | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/8564175 | por |
oaire.citationStartPage | 294 | por |
oaire.citationEndPage | 302 | por |
dc.date.updated | 2020-09-04T15:06:59Z | - |
dc.identifier.doi | 10.1109/iV.2018.00057 | por |
dc.date.embargo | 10000-01-01 | - |
dc.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | por |
dc.subject.wos | Science & Technology | - |
sdum.export.identifier | 6160 | - |
sdum.conferencePublication | 2018 22ND INTERNATIONAL CONFERENCE INFORMATION VISUALISATION (IV) | por |
sdum.bookTitle | 2018 22ND INTERNATIONAL CONFERENCE INFORMATION VISUALISATION (IV) | por |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
IV2018_Silva_et_al.pdf Acesso restrito! | 5,31 MB | Adobe PDF | Ver/Abrir |