The VagueGeometry Abstract Data Type

Authors

  • Anderson Chaves Carniel University of São Paulo
  • Ricardo Rodrigues Ciferri Federal University of São Carlos
  • Cristina Dutra de Aguiar Ciferri University of São Paulo

Keywords:

abstract data types, spatial databases, vague spatial objects, vague topological predicates

Abstract

Spatial vagueness has been increasingly required by geoscientists to handle vague spatial objects, that is, spatial objects found in real-world phenomena that do not have exact locations, strict boundaries, or sharp interiors. However, there is a gap in the literature in how to handle spatial vagueness in spatial database management systems and Geographical Information Systems (GIS) since they mainly provide support to crisp spatial objects, that is, objects that have well-defined locations, boundaries, and interiors. In this article, we propose VagueGeometry, a novel abstract data type that allows users to manipulate vague spatial objects in spatial applications and GIS. The main advantages of our VagueGeometry are that (i) it offers textual and binary representations for vague spatial objects, (ii) it includes an expressive set of vague spatial operations, (iii) it supports SQL operators, and (iv) its implementation is open source. We also propose an improvement of VagueGeometry to deal efficiently with the processing of vague topological predicates. Experimental results show that VagueGeometry improved the performance of spatial queries with vague topological predicates from 21% up to 98% if compared with functionalities available in current spatial databases.

Author Biographies

  • Anderson Chaves Carniel, University of São Paulo

    Anderson Chaves Carniel received the System Analysis and Development degree from Federal Institute of Education, Science and Technology of São Paulo, Brazil, in 2011. In 2014, he received the MSc degree in Computer Science from Federal University of São Carlos, Brazil. He is currently a PhD student at Department of Computer Science at University of São Paulo in São Carlos, Brazil. His main areas of interest are spatial databases, vague spatial data, and spatial indexing.

  • Ricardo Rodrigues Ciferri, Federal University of São Carlos

    Ricardo Rodrigues Ciferri received the BS degree in Computer Science from Federal University of São Carlos, Brazil, in 1992. In 1995, he received the MSc degree in Computer Science from State University of Campinas, Brazil. He obtained his PhD degree in 2002 in Computer Science from Federal University of Pernambuco, Brazil. He is currently an Associate Professor at Department of Computer Science at Federal University of São Carlos, Brazil. His main areas of interest are data integration, data warehousing, geographical information systems, spatial databases, cloud databases and parallel and distributed databases.

  • Cristina Dutra de Aguiar Ciferri, University of São Paulo
    Cristina Dutra de Aguiar Ciferri received the BS degree in computer science from Federal University of São Carlos, Brazil, in 1992. In 1995, she received the MSc degree in Computer Science from State University of Campinas, Brazil. She obtained her PhD degree in 2002 in Computer Science from Federal University of Pernambuco, Brazil. She is currently an Associate Professor at Department of Computer Science at University of São Paulo in São Carlos, Brazil. Her main areas of interest are data provenance, data integration, cloud computing, data warehousing, geographical information systems, spatial databases, heterogeneous and distributed databases, and bioinformatics.

Downloads

Additional Files

Published

2016-10-03

Issue

Vol. 7 No. 1 (2016): JOURNAL OF INFORMATION AND DATA MANAGEMENT

Section

GeoInfo 2015