Building Spatio-Temporal Database Model Based on Ontological Approach using Relational Database Environment

  • Nadeem Mehmood Department of Computer Science, University of Karachi, Karachi
  • Syed Muhmmad Aqil Burney
  • Kashif Rizwan
  • Asadullah Shah
  • Adnan Nadeem

Abstract

Everything in this world is encapsulated by space and time fence. Our daily life activities are utterly linked and related with other objects in vicinity. Therefore, a strong relationship exist with our current location, time (including past, present and future) and event through with we are moving as an object also affect our activities in life. Ontology development and its integration with database are vital for the true understanding of the complex systems involving both spatial and temporal dimensions. In this paper we propose a conceptual framework for building spatio-temporal database model based on ontological approach. We have used relational data model for modelling spatio-temporal data content and present our methodology with spatio-temporal ontological accepts and its transformation into spatio-temporal database model. We illustrate the implementation of our conceptual model through a case study related to cultivated land parcel used for agriculture to exhibit the spatio-temporal behaviour of agricultural land and related entities. Moreover, it provides a generic approach for designing spatiotemporal databases based on ontology. The proposed model is capable to understand the ontological and somehow epistemological commitments and to build spatio-temporal ontology and transform it into a spatio-temporal data model. Finally, we highlight the existing and future research challenges.

Published
Oct 1, 2017
How to Cite
MEHMOOD, Nadeem et al. Building Spatio-Temporal Database Model Based on Ontological Approach using Relational Database Environment. Mehran University Research Journal of Engineering & Technology, [S.l.], v. 36, n. 4, p. 10, oct. 2017. ISSN 2413-7219. Available at: <http://publications.muet.edu.pk/index.php/muetrj/article/view/34>. Date accessed: 17 dec. 2017.