Visualising hidden spatiotemporal patterns at multiple levels of detail

Ricardo Almeida Silva, João Moura Pires, Nuno Datia, Maribel Yasmina Santos, Bruno Martins, Fernando Birra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationInformation Visualisation - Biomedical Visualization, Visualisation on Built and Rural Environments and Geometric Modelling and Imaging, IV 2018
EditorsJoao Moura Pires, Nuno Miguel Soares Datia, Giuseppe Polese, Marco Temperini, Filippo Sciarrone, Michele Risi, Gilles Venturini, Tania Di Mascio, Rocco Zaccagnino, Vincenzo Deufemia, Delfina Malandrino, Paloma Diaz, Antonio Fernandez Anta, Ebad Banissi, Theodor G. Wyeld, Muhammad Sarfraz, Fatma Bouali, Mark W. McK. Bannatyne, Fragkiskos Papadopoulo, Ugo Erra, Veronica Rossano, Anna Ursyn, Alfredo Cuzzocrea, Rita Francese
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages294-302
Number of pages9
ISBN (Electronic)9781538672020
DOIs
Publication statusPublished - 5 Dec 2018
Event22nd International Conference Information Visualisation - Biomedical Visualization, Visualisation on Built and Rural Environments and Geometric Modelling and Imaging, IV 2018 - Salerno, Italy
Duration: 10 Jul 201813 Jul 2018

Conference

Conference22nd International Conference Information Visualisation - Biomedical Visualization, Visualisation on Built and Rural Environments and Geometric Modelling and Imaging, IV 2018
CountryItaly
CitySalerno
Period10/07/1813/07/18

Keywords

  • Data-Visualisation
  • Multiple Levels of Detail
  • Spatiotemporal-Patterns
  • Visual Analytics

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