Government data catalog is one of the major components in creating government data sharing infrastructure. A government data catalog usually provides tools to help the data users to find, access and reuse the data appropriately. There are typically two approaches to data catalog development: centralized and decentralized approaches. The centralized approach allows more quality control over data publication while the decentralized approach enables more autonomy. This paper proposes a hybrid framework for government data catalog development that combines both approaches. Metadata and API interoperability are among the key elements of the framework. The framework was adopted in the development of the government data catalog of Thailand. The design and implementation of the framework based on the CKAN software architecture are presented. The results in terms of adoption scalability demonstrate the effectiveness of the framework.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

A Hybrid Framework for the Development of Government Data Catalog: A Case Study of the Government Data Catalog of Thailand

  • Marut Buranarach,
  • Patipat Tumsangthong,
  • Theerawat Wutthitasarn

摘要

Government data catalog is one of the major components in creating government data sharing infrastructure. A government data catalog usually provides tools to help the data users to find, access and reuse the data appropriately. There are typically two approaches to data catalog development: centralized and decentralized approaches. The centralized approach allows more quality control over data publication while the decentralized approach enables more autonomy. This paper proposes a hybrid framework for government data catalog development that combines both approaches. Metadata and API interoperability are among the key elements of the framework. The framework was adopted in the development of the government data catalog of Thailand. The design and implementation of the framework based on the CKAN software architecture are presented. The results in terms of adoption scalability demonstrate the effectiveness of the framework.