An Institutional Analysis of Indigenous Data Governance in Indonesia’s STI Systems

Winda Anestya Ayunda, Yogi Suprayogi Sugandi, Yanuar Farida Wismayanti, Wawan Budi Darmawan

Abstract


This article examines the institutional positioning of Indigenous Data Governance (IDG) within Indonesia’s Science, Technology, and Innovation (STI) policy framework. Using a qualitative analysis of key policy documents including Law No. 11/2019 on the National System of Science and Technology, Law No. 27/2022 on Personal Data Protection, and Law No. 6/2014 on Village Governance, this study explores how IDG is reflected in existing policies. The analysis is guided by an institutional perspective that focuses on three dimensions: regulative, normative, and cognitive elements. This approach enables an assessment of not only formal legal provisions, but also the values and underlying assumptions embedded in policy frameworks. The findings show that IDG remains weakly embedded within Indonesia’s STI policy framework. While certain regulative elements provide partial support particularly in relation to data protection and governance normative recognition of Indigenous communities and cognitive acknowledgment of Indigenous knowledge systems remain limited. As a result, policies tend to prioritize formal, individual-based data governance and overlook collective and culturally embedded dimensions of data. When interpreted within the broader STI system, these limitations are reflected in the insufficient inclusion of Indigenous actors, weak linkages between national policies and local governance structures, and the absence of a supportive enabling environment for IDG. This study highlights that the challenge of integrating IDG is not only a matter of legal recognition, but also of institutional alignment and system-level support. It contributes to the literature on STI governance by emphasizing the importance of incorporating diverse knowledge systems and strengthening coordination across governance levels in culturally diverse and decentralized contexts.


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DOI: http://dx.doi.org/10.14203/STIPM.2026.463

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