Literature DB >> 30273125

Spatio-Temporal Urban Data Analysis: A Visual Analytics Perspective.

Harish Doraiswamy, Juliana Freire, Marcos Lage, Fabio Miranda, Claudio Silva.   

Abstract

Visual analytics systems can greatly help in the analysis of urban data allowing domain experts from academia and city governments to better understand cities, and thus enable better operations, informed planning and policies. Effectively designing these systems is challenging and requires bringing together methods from different domains. In this paper, we discuss the challenges involved in designing a visual analytics system to interactively explore large spatio-temporal data sets and give an overview of our research that combines visualization and data management to tackle these challenges.

Year:  2018        PMID: 30273125     DOI: 10.1109/MCG.2018.053491728

Source DB:  PubMed          Journal:  IEEE Comput Graph Appl        ISSN: 0272-1716            Impact factor:   2.088


  1 in total

1.  Spatiotemporal data mining: a survey on challenges and open problems.

Authors:  Ali Hamdi; Khaled Shaban; Abdelkarim Erradi; Amr Mohamed; Shakila Khan Rumi; Flora D Salim
Journal:  Artif Intell Rev       Date:  2021-04-15       Impact factor: 9.588

  1 in total

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