Repository logo
 
Publication

Visual analytics for spatiotemporal events

2019-08-16Journal article Open access
Simple item page
dc.contributor.authorSilva, Ricardo Almeida
dc.contributor.authorMoura Pires, João
dc.contributor.authorDatia, Nuno
dc.contributor.authorSantos, Maribel Yasmina
dc.contributor.authorMartins, Bruno
dc.contributor.authorBirra, Fernando
dc.date.accessioned2019-10-08T08:25:51Z
dc.date.available2019-10-08T08:25:51Z
dc.date.issued2019-08-16
dc.description.abstractCrimes, forest fires, accidents, infectious diseases, or 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, as it can highlight useful patterns or insights and enhance the user’ perception of phenomena. For this reason, modeling phenomena at different LoDs is needed to increase the analytical value of the data, as there is no exclusive LOD at which the data can be analyzed. Current practices work mainly on a single LoD of the phenomena, driven by the analysts’ perception, ignoring that identifying the suitable LoDs is a key issue for pointing relevant patterns. This article 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 do interesting 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 supported the evaluation and validation of VAST, suggesting LoDs with different interesting spatiotemporal patterns and pointing the type of expected patterns.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSILVA, Ricardo Almeida; [et al] – Visual analytics for spatiotemporal events. Multimedia Tools and Applications. ISSN 1380-7501. Vol. 78, N.º 23 (2019), pp. 32805-32847pt_PT
dc.identifier.doihttps://doi.org/10.1007/s11042-019-08012-2pt_PT
dc.identifier.issn1380-7501
dc.identifier.issn1573-7721
dc.identifier.urihttp://hdl.handle.net/10400.21/10545
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relationUID/CEC/00319/2019 - FCT (ALGORITMI)pt_PT
dc.relationUID/CEC/50021/2019 - FCT (INESC-ID)pt_PT
dc.relation.publisherversionhttps://link.springer.com/content/pdf/10.1007%2Fs11042-019-08012-2.pdfpt_PT
dc.subjectData visualizationpt_PT
dc.subjectSpatiotemporal patternspt_PT
dc.subjectMultiple levels of detailpt_PT
dc.subjectVisual analyticspt_PT
dc.titleVisual analytics for spatiotemporal eventspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FCEC%2F04516%2F2013/PT
oaire.citation.endPage32847pt_PT
oaire.citation.issue23
oaire.citation.startPage32805pt_PT
oaire.citation.titleMultimedia Tools and Applicationspt_PT
oaire.citation.volume78
oaire.fundingStream5876
person.familyNameSilva
person.familyNameMoura Pires
person.familyNameDatia
person.familyNameSantos
person.familyNameBirra
person.givenNameRicardo Almeida
person.givenNameJoão
person.givenNameNuno
person.givenNameMaribel Yasmina
person.givenNameFernando
person.identifier2587159
person.identifier.ciencia-idB71B-453A-0176
person.identifier.ciencia-id071F-5CBD-5D83
person.identifier.ciencia-id3212-54CD-F759
person.identifier.ciencia-id5913-8494-636D
person.identifier.orcid0000-0001-5187-8604
person.identifier.orcid0000-0001-9933-936X
person.identifier.orcid0000-0003-1600-0227
person.identifier.orcid0000-0002-3249-6229
person.identifier.orcid0000-0002-4232-5079
person.identifier.ridD-5450-2013
person.identifier.ridR-7957-2016
person.identifier.ridM-5214-2013
person.identifier.ridC-8253-2016
person.identifier.scopus-author-id55925917200
person.identifier.scopus-author-id56026178000
person.identifier.scopus-author-id8407376200
person.identifier.scopus-author-id24512124500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationfec6d85b-e271-4691-a44e-555c2863ce3d
relation.isAuthorOfPublication883c6c34-0540-4848-b3d4-e03d0d0cad93
relation.isAuthorOfPublication368f1534-fbb8-4e99-994c-1c7104a42bc6
relation.isAuthorOfPublication2ccd0839-d6e3-40f7-b447-da8e6923eba2
relation.isAuthorOfPublication42c3c420-7d49-4fc3-9b25-8498dd4b4d00
relation.isAuthorOfPublication.latestForDiscoveryfec6d85b-e271-4691-a44e-555c2863ce3d
relation.isProjectOfPublicationcbce3bca-c959-4bd5-a02c-0f1de598f8e0
relation.isProjectOfPublication.latestForDiscoverycbce3bca-c959-4bd5-a02c-0f1de598f8e0

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Visual_NDatia.pdf
Size:
6.95 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ISEL - Eng. Elect. Tel. Comp. - Artigos