在生成式AI與資料驅動治理的趨勢下，政府資料治理已不僅是技術或資訊管理議題，而是牽動文官制度能否支撐數位轉型的制度性能力問題。本文整合資料生命週期理論與成熟度模型，建構「政府機關資料生命週期導向之資料治理成熟度評估架構」（the Data Lifecycle Management-based Data Governance Maturity Model, DLM-DGMM），並以問卷調查方式評估內政體系資料治理成熟度現況，進一步從文官制度視角診斷其結構性課題。實證結果顯示，整體成熟度穩定落在等級3，反映組織具備可持續遵循的標準化流程；惟各生命週期階段呈現「重保存、輕分析」之失衡，資料歸檔得分最高而資料分析相對不足，凸顯依法行政所促成之標準化成就，亦可能抑制資料應用與創新。分群比較顯示，不同世代、位階、職務與專業群體在成熟度知覺上存在顯著認知稜鏡；然而在控制年資、官等與職務屬性後，傳統科層變項之解釋力有限，資訊素養則與成熟度知覺呈現正向且顯著關聯，指向文官制度需由「身分治理」轉向「能力治理」。據此，本文建議將 DLM-DGMM 制度化嵌入考選、銓敘與訓練發展體系，建立以成熟度貢獻衡量數位功績、以診斷導向規劃學習路徑之管理循環，以強化我國文官制度面對數位治理的制度韌性。

[關鍵詞]：資料治理、資料治理成熟度模型、資料生命週期、文官制度、資訊素養

From Status-Based Governance to Capability-Based Governance: Implications of Data Governance Maturity for Taiwan’s Civil Service Reform

Lo-Wei Lee

Abstract

In the context of generative AI and data-driven governance, data governance in the public sector has become an institutional capacity, rather than just a technical, issue. This study integrates data lifecycle theory and maturity models to develop the Data Lifecycle Management-based Data Governance Maturity Model (DLM-DGMM). Based on a questionnaire survey of Taiwan’s Ministry of the Interior system, the study assesses the current state of data governance maturity and diagnoses structural challenges from a civil service perspective. The findings indicate that overall maturity is steady at Level 3, reflecting the establishment of standardized and sustainable processes. However, a clear imbalance exists across lifecycle stages: data archiving scores highest, while data analytics remains underdeveloped, suggesting a “preservation-over-application” pattern shaped by administrative standardization. Group comparisons reveal perceptual differences across generations, hierarchical ranks, and professional roles. Yet, after controlling for bureaucratic attributes, information literacy shows a significant positive association with perceived maturity, whereas traditional status-based variables have limited explanatory power. These results point to a paradigm shift from status-based governance to capability-based governance. The study therefore proposes institutionalizing the DLM-DGMM within recruitment, promotion, and training systems to support diagnostic, evidence-based civil service reform and strengthen institutional capacity for digital governance.

Keywords: Data Governance, Data Governance Maturity Model, Data lifecycle, Civil Service System, Information Literacy