Governance Frameworks
To address governance issues for a specific data initiative we need to understand:
- The policy landscape as it relates to the initiative.
- The regulatory environment
- The ethical issues and approaches to address them
- Power imbalances, especially in stakeholder and funder relationships
We see governance as a process, rather than a set of rules or agreements. It must continually evolve, and be able to address new and unanticipated questions. It must be sustainable over relevant periods of time, which means that it must remain relevant and empowered.
Data governance is an enabling mechanism, through which organizations can achieve better leadership, decision making, and adherence to mission. It is a critical part of your data and business strategy.
The sector needs models, templates, and frameworks for governance that will meet the needs of its data initiatives. We must be in these concepts, and build institutions that can support individual efforts.
Governance and Legal frameworks
- Governance principles
- Transparency safeguards
- Accountability
- Ethics committees and review boards
In recent years there’s been important advancements and creation of new tools to address governance issues.
Concepts and models for data governance and collaboration:
- Data Trusts
- Data Collaboratives
- Data Stewardship
- Data Institutions
Other: Policies and agreements
- Open data policies
- Data use agreements / data re-use agreements
References and recommended reading
- Mapping Policy Infrastructure from Stanford PACS
- Reclaiming data trusts in the public interest by Sean McDonald, Digital Public
- Data collaboratives: Creating Public value, a project by Govlab.
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