Endorsed 7. This Framework will not apply to: (a) Measures adopted by an ASEAN Member State to exempt any areas, persons or sectors from the application of the Principles identified under the Framework; and (b) Matters relating to national sovereignty, national security, public safety, and all government activities deemed suitable by an ASEAN Member State to be exempted. ASEAN Guiding Principles on Data Governance for the Digital Economy (“Principles”) 8. The Principles for each strategic priority aim to provide ASEAN Member States with guidance to develop data governance for the digital ecosystem based on each ASEAN Member State’s level of readiness and development. 9. Each ASEAN Member State will endeavour to take into account and implement within their domestic laws and regulations the Principles in accordance with this Framework. Where relevant, each ASEAN Member State should also encourage organisations to consider or incorporate these Principles when developing policies and practices. Strategic Priority 1: Data Life Cycle and Ecosystem 10. The Principles on the data life cycle and ecosystem highlight the importance of data governance at every stage of the data life cycle and how that can contribute to the overall integrity and usability of data. The data life cycle follows the various stages of data management – from the point when the data is generated or collected for specific functions or purposes, to the data being used (e.g. processed and analysed), including when the data is in transit or at rest and through to the final point where the data is eventually deleted. A. 11. Principle on Data Integrity and Trustworthiness The Principle on data integrity and trustworthiness recognises that access to accurate and reliable data is critical, especially when the data is used to analyse and support business decisions such as product development, service delivery or market expansion. This would include: (i) Tracking and documenting data sources to account for when data is procured externally or generated internally; (ii) Ensuring data accuracy, where practicable, over the entire data life cycle by implementing good data management practices, including managed data collection and creation, proper data recording and processing such that it does not affect the data quality, review and update internal databases to ensure data is up-to-date especially when the data is used to make a decision about individuals, and incorporate safeguards for data storage; and 3