A Conceptual Framework for Linking Open Government Data Based-On Geolocation: A Case of Thailand

  • Punnawit BudsapawanichEmail author
  • Chutiporn Anutariya
  • Choochart Haruechaiyasak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11341)


Over the past decade, most governments have steadily progressed towards a policy for more openness, more accountability and more transparency. Such a strategy to publish open data, which are meaningful and valuable, has made available open government data (OGD) that are publicly accessible to everyone. To promote OGD usage, most OGD datasets are published in a tabular form or a CSV spreadsheet format, which can be easily browsed and downloaded by a human user. However, applications of OGD often require data from different datasets to be integrated. This is a challenging and cumbersome task which usually demand huge human effort, especially if metadata as well as data representation and encoding standards are not well defined. With a thorough analysis into Thailand’s OGD (ThOGD) having over thousand datasets, we found that OGD datasets often involve data related to geolocation, places or administrative division. Therefore, using such geodata as potential linking nodes is very attractive. However, this is not an easy task due to data heterogeneity issues. For example, a location might be represented using a geographic coordination system (e.g., latitude and longitude) or an administrative division which could be in a different level from highest to lowest division such as regions, provinces, districts, municipalities, etc.). Moreover, in Thailand geographical regions can be divided differently by different division schemes depending on the application domains, e.g., meteorology, tourism and statistics. To tackle this challenge, in this paper, we propose a conceptual framework for mapping and linking OGD datasets using geolocation data which could increase OGD usage and promote the development of new services or applications.


Open government data Linked open government data Geodata Data integration 


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Punnawit Budsapawanich
    • 1
    Email author
  • Chutiporn Anutariya
    • 1
  • Choochart Haruechaiyasak
    • 2
  1. 1.Asian Institute of TechnologyKhlong LuangThailand
  2. 2.National Electronics and Computer Technology CenterKhlong LuangThailand

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