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Resumen de Critical Factors in Central Government Information and Data Governance - Empirical Study

Chuan-Chun Wu, Hsin-Chung Chu

  • Along with the development of information and communications technology being popular, types of data become rich and multiple, the analysis scope changes from structured data to non-structured data without sorting context, and the data volume becomes huge and is continuously growing. When data application cases and value benefit are gradually noticed in past years, government agencies realize that data could develop the value through cross-boundary collaboration, rather than simple relying on internal processing and analyses, and the collaboration process allows the government cultivating to apply data with added-value and establish evidence-based governance. Aiming at employees in public sectors in the central government of Taiwan, total 320 copies of questionnaire are distributed and 247 valid copies are retrieved, with the retrieval rate 77% . The research results are summarized as below: (1) Regarding the curiosity and expectation of data analysis of the government, either directors of agencies or key case officers, with the expectation of applying the possessed data with added value, do not simply regard data as dead records, but attempt to apply data to solve specific public issues; (2) In addition to inducing the curiosity about data application in the internal organization, success cases of other agencies could facilitate the action of an organization participating in the project for expanding to central and local levels or cross-units inducing the agencies with similar businesses engaging in the project as well as accelerate project influence through experience sharing and reinforce the confidence of other units in information and data governance; (3) Information and data governance could benefit the government shaping positive image to interpret outcomes through data for the reference of future policies, strengthen the industrial and academic research energy of the business, as well as enhance public trust and agency transparency through cooperation with experts. According to the results to propose suggestions, it is expected to provide related policy suggestions for the government examining the internal organization from management to execution about the preparation for data governance and the reference for top decision-makers planning data application strategies, applying data to public-private collaboration, and improving existing data governance structure.


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