Towards the development of RDF-based statistical data: An open data perspective

Yu Wei Hsu, Jung-Hong Hong

Research output: Contribution to conferencePaperpeer-review


The revolution of GIS technology in the past 30 years have successfully transformed how information with location is used in science, technology and even human being daily lives. Nowadays we enjoy the luxury for using innovated applications via WebGIS to improve the quality of lives. Facilitating a better application environment for transparently accessing and integrating information from various domains becomes a challenge that should receive close and continuous attentions. With the increasing volume of data sharing in internet, the lack consideration of semantics to the distributed data apparently becomes impediments hindering the development of cross-domain applications. This paper intends to examine the use of the Resource Description Framework (RDF) for enriching the semantics of distributed geographic data and explores the advantages of developing internet-based sharing environment with Linked Open Data (LOD). Statistical data is chosen in this paper for analysis because it is a widely used type of data for understanding the changing status of the real world, even before GIS spatially enabled its geographic illustration. As a variety of domains may generate and publish their statistical data, how to integrate cross-domain data should receive special attention. A comprehensive mechanism that can effectively conquer the semantic heterogeneity issue and correctly link statistical data from different domains can hence improve the interoperable use of cross-domain statistical data. A RDF architecture based on the Taiwan Geographic Statistical Classification is proposed and tested to demonstrate its ability to link related data and enable interaction between different domains. The research results contribute to the future strategies to facilitate a better collaboration between different domains at the national level.

Original languageEnglish
Number of pages8
Publication statusPublished - 2018 Jan 1
Event39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018 - Kuala Lumpur, Malaysia
Duration: 2018 Oct 152018 Oct 19


Conference39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018
CityKuala Lumpur

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Earth and Planetary Sciences(all)
  • Computer Networks and Communications

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