Please use this identifier to cite or link to this item:

TitleReasoning about space and time: moving towards a Theory of Granularities
Author(s)Pires, João Moura
Silva, Ricardo Almeida
Santos, Maribel Yasmina
KeywordsSpatial-temporal data
Issue date2014
PublisherSpringer International Publishing
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract(s)Nowadays, the massive amount of spatio-temporal data available exceeds the human capability to absorb them (i.e., to achieve insights). A possible approach to address this issue is through less detailed representations of phenomena so that the data complexity can be decreased making easier for the users to achieve meaningful insights. In this paper, we discuss the state of the art of modeling spatio-temporal phenomena at different levels of detail (LoDs). We found that granularities play an important role to hold spatio-temporal data at different LoDs. A novel granularity framework is proposed, allowing the defini- tion of a granularity over any domain (including spatial and temporal granularities) as well as it allows transposing knowledge from the original domains to granularities (i.e., known relationships and its properties on the domain). Finally, a granularities-based model is proposed, based on the proposed granularity framework, for dealing and relate different LoDs of spatio-temporal data.
TypeConference paper
DescriptionPublicado em "Computational science and its applications – ICCSA 2014 : proceedings...", Series title : Lecture notes in computer science, vol. 8579
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

Files in This Item:
File Description SizeFormat 
  Restricted access
Documento Principal1,56 MBAdobe PDFView/Open    Request a copy!

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID