Fundamentals of Dynamic Data Governance with the MAST & IDEAL Methodology

Fundamentals of Dynamic Data Governance with the MAST & IDEAL Methodology

Fundamentals of MAST & IDEAL Metadata is a short-course in the MAST/IDEAL Methodology, a pragmatic framework for building understanding and organisational support for data management through good processes rather than specific tools or standards.

The MAST/IDEAL Methodology is a standards-agnostic and tools-independent approach that supports existing frameworks such as the Data Management Body of Knowledge and DDI Data Lifecycle, which focus on an expert audience. The MAST Methdology complements this by providing a step-by-step guide on how practitioners across the whole organisation can develop the skills and culture to perform these tasks.

Learning objectives:

• Understand the principles of the MAST (Metadata-Analysis-Standards-Teamwork) Manifesto
• Understand the stages in the IDEAL (Inventory-Document-Endorse-Audit-Leadership) Framework
• Communicate the importance of metadata for a range of audiences - from researcher and data staff to administrators and executives
• Identify skills for specialist teams to build a culture of peer review and support modern data governance
• Focus effort on the steps that maximise success in data documentation and governance initiatives
• Select appropriate metadata standards and software for successful data projects

Analogous to the Agile Methodology for Project Management, The MAST Methodology is designed to democratise Data Management, by making it easier for all users across organisations to understand their roles in data governance and metadata management.

Developed by Aristotle Metadata, the MAST Methodology was developed across projects with the health informatics and government sectors, and describes specific beliefs and behaviours of organisations that have implemented successful data governance programs. This Methodology has been published as a tools-agnostic, creative-commons methodology ( https://www.aristotlemetadata.com/about/mast-methodology), and can be implemented by organisations without requiring specific software or standards.

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