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Data Infrastructure for Common Challenges
  • Data Landscape Playbook
    • Data Landscape Playbook: status
    • What is this playbook for?
    • Who is this playbook for?
  • Play one: Explore the problem and how data can address it
    • Define how improving access to data can help address your problem
    • What type of data infrastructure does the initiative aim to create or maintain?
      • Build or manage data assets
      • Create or adopt data standards
      • Build or improve technologies
      • Create guidelines and policies
      • Build or support organisations and communities
    • Carry out initial research and engagement
    • Summary of Play One
  • Play two: Map the data ecosystem
    • Engage with key stakeholders
    • Create an ecosystem map
    • Identify gaps, barriers and opportunities
    • Summary of Play Two
  • Play three: Assess the policy, regulatory and ethical context
    • Understand the legal, regulatory and policy context of the initiative
    • Understand the ethical issues impacting your initiative
    • Summary of Play Three
  • Play four: Assess the existing data infrastructure
    • Make a data inventory
    • Assess open standards for data
    • Assess data skills and literacies
    • Summary of Play Four
  • Play five: Plan for impact when designing your data initiative
    • Plan an impactful initiative
    • Identify risks, assumptions and dependencies
    • Sketch your evaluation framework
    • Summary of Play Five
  • What comes next?
  • Acknowledgements
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  • Plan your data management
  • Consider the sustainability of the initiative
  • Refine your evaluation framework

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What comes next?

Resources to make your initiative trustworthy, sustainable and scalable

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Last updated 4 years ago

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You should now have a clear understanding of your data initiative, and the data landscape and infrastructure that it needs to collect, share and use data to achieve your desired outcomes. Below we provide some tips on how to make this infrastructure sustainable, trustworthy and relevant to its context.

Plan your data management

Designing a data management plan includes outlining the technical processes, roles and governance to effectively manage data, and the resources required to support its collection, access and use.

Creating a data management plan should, ideally, be a collaborative, iterative, process involving all stakeholders in a project. This guide: '', from CABI's Data Sharing Toolkit covers the main elements of a data management plan:

  • Assigning roles and responsibilities

  • Identifying the audience for the data

  • Defining the data to be managed

  • Planning and resourcing

  • Storing and securing data

Consider the sustainability of the initiative

Achieving impact through your initiative might hinge on your ability to make the initiative sustainable in the long run, or beyond its initial funding. An important consideration for sustainability is the business model of the organisations that steward data infrastructure – including data assets, standards, technologies and policies – longer term. The can support organisations as they reflect on their current state, and think about their revenue model’s sustainability when looking for long-term grant funding, building a monetisation strategy, or creating a data institution.

Your initiative will also need to be trusted by, and demonstrate trustworthiness to, different actors in your data ecosystem in order to continue to steward, shape or influence the data infrastructure necessary to achieve your desired impact. The provides guidance and tools to support your initiative in assessing the elements of trust that need to be strengthened.

Finally, when strengthening or designing the data infrastructure to tackle the problem, your initiative should consider how this solution can be scaled up across a wider ecosystem or different sectors or contexts. The can help you address barriers that can hinder the ability to scale data access initiatives and make a high level plan for the resources, technical aspects, knowledge and collaboration you need.

Refine your evaluation framework

Once the initiative is running, you should monitor progress in the indicators defined in your logic model. Some activities or outputs might change during the implementation process, as you learn more and test your assumptions, so you might also refine these indicators, and the logic model itself, over time.

We also recommend communicating progress and outcomes through blogs, use cases or evaluations to showcase how the initiative is evolving, maintain interest and momentum, and share lessons learned from the ground with others.

Additional resources:

360Giving (2020), ‘’

Energy Systems Catapult (2021), ‘’

DAMA International (2017), ‘’

Developing a data management plan
Sustainable Data Access Workbook
Trustworthy Data Stewardship Guidebook
‘Scaling data-enabled projects’ checklist
Data Strategy Canvas
Energy Data Management Canvas
DMBoK - Data Management Book of Knowledge