Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/42355

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dc.contributor.authorSilva, Ricardo Almeidapor
dc.contributor.authorPires, João Mourapor
dc.contributor.authorSantos, Maribel Yasminapor
dc.contributor.authorDatia, Nunopor
dc.date.accessioned2016-08-05T08:47:31Z-
dc.date.issued2016-06-
dc.identifier.citationSilva, Ricardo, João Moura Pires, Maribel Yasmina Santos and Nuno Datia, “Aggregating Spatio-temporal Phenomena at Multiple Levels of Detail”, T. Sarjakoski et al. (eds.), Geospatial Data in a Changing World, Proceedings of the 19th AGILE International Conference in Geographic Information Science, Lectures Notes in Geoinformation and Cartography, Springer-Verlag, 2016, June 14-17, Helsinki, Finland, ISBN: 978-3-319-33782-1.por
dc.identifier.isbn978-3-319-33782-1-
dc.identifier.issn1863-2351por
dc.identifier.urihttps://hdl.handle.net/1822/42355-
dc.description.abstractThere are many spatiotemporal events with high levels of detail (LoDs) being collected in many phenomena. The LoD of analysis plays a crucial role in the user’s perception of phenomena. From one LoD to another, some patterns can be easily perceived or different patterns may be detected. Standard practices work on a single LoD driven by the user in spite of the fact that there is no exclusive LoD to study a phenom- enon. Our proposal aims to support users in carrying the inspection and comparison tasks of a phenomenon across multiple LoDs, without having to look at raw data, and to handle the spatiotemporal complexity. This paper presents a framework to build abstracts at different LoDs where five types of abstracts are proposed. The framework makes no assumption about the phenomenon, the analytical task and the phenomenon’s LoDs. The SUITE’s prototype implements the proposed framework allowing users to inspect abstracts across multiple LoDs simultaneously, helping to understand in what LoDs the phenomenon perception distinguishes itself or in what LoDs “interesting patterns” emerge.por
dc.description.sponsorshipThis work has been supported by FCT - Fundação para a Ciência e Tecnologia MCTES, UID/CEC/04516/2013 (NOVA LINCS) and UID/CEC/00319/2013 (ALGORITMI), and COMPETE: POCI-01-0145-FEDER-007043 (ALGORITMI).por
dc.language.isoengpor
dc.publisherSpringer Verlagpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147279/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147280/PTpor
dc.rightsrestrictedAccesspor
dc.subjectMultiple levels of detailpor
dc.subjectSpatiotemporal datapor
dc.subjectVisual Analyticspor
dc.titleEnhancing exploratory analysis by summarizing spatiotemporal events across multiple levels of detailpor
dc.typeconferencePaperpor
dc.peerreviewedyespor
sdum.publicationstatusinfo:eu-repo/semantics/publishedVersionpor
oaire.citationStartPage219por
oaire.citationEndPage238por
oaire.citationIssue175179por
oaire.citationConferencePlaceFinlandpor
oaire.citationTitleProceedings of the 19th AGILE International Conference in Geographic Information Sciencepor
dc.identifier.doi10.1007/978-3-319-33783-8_13por
dc.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.subject.wosScience & Technologypor
sdum.journalLecture Notes in Geoinformation and Cartographypor
sdum.conferencePublicationProceedings of the 19th AGILE International Conference in Geographic Information Sciencepor
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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