User-centric data publishing (Alpha)
  • User-centric data publishing
    • Introduction
    • Who is this toolkit for?
    • How to use this toolkit
    • Dictionary of data terms
  • Contents
  • Section 1. Building the foundation for open data
    • A basic introduction to open data
    • Understanding our rights to access data
    • Open data maturity
      • Resources: Open data maturity
    • Ethics and transparency
  • Section 2. Planning for impactful open data initiatives
    • An introduction to the Data Landscape Playbook
    • Play one: Explore the problem and how data can address it
    • Play two: Map the data ecosystem
    • Play three: Assess the policy, regulatory and ethical context
    • Play four: Assess the existing data infrastructure
    • Play five: Plan for impact when designing your data initiative
  • Section 3. A user-centric approach to publishing
    • Understanding the user journey
      • The use case
      • Understanding different user needs
      • Targeting intended audiences
    • Engaging effectively with data users
      • Two-way communication and feedback
      • From data to story
    • Building communities around open data use
      • Characteristics of an open data user community
        • Purpose
        • Community enabler(s)
        • Collaborative method
        • Other observations
      • The current landscape of open data user communities
      • Engagement with data communities
    • Resources: User-centric publishing
  • Section 4: Publishing guidance for new data publishers
    • Open data licensing
    • The FAIR principles of data access
      • FAIR data assessment tools
    • Data quality and metadata
      • Tools and frameworks to help you assess open data quality
    • Publishing data on the web
  • Thank you
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  • The Communication Loop
  • Suggestions for meaningful engagement at different points in the user journey
  1. Section 3. A user-centric approach to publishing

Engaging effectively with data users

A dynamic relationship ensures value is realised for everyone involved, and that there is transparency and openness within a productive open data ecosystem

PreviousTargeting intended audiencesNextTwo-way communication and feedback

Last updated 2 years ago

The Communication Loop

There is, ideally, a dynamic relationship between data publishers and data users. A dynamic relationship ensures value is realised for everyone involved, and that there is transparency and openness within a productive open data ecosystem.

The communication loop describes the productive two-way relationship necessary to fully understand what each party requires from open data publishing, and to facilitate the best ways to meet identified needs. This goes beyond simple feedback on likes and dislikes, but involves meaningful engagement with the aims of improving, collaborating and innovating.

The potential to enhance the value of data and the potential to enhance the value of relationships can be realised through more effective engagement between data publishers and data users. Similarly, there is ‘shared value’ to be gained through working towards a common goal or having similar ambitions in addressing a common issue, such as improving child wellbeing in an area or reducing carbon emissions, for example.

Do you have a relationship with your data users? How would you describe this relationship? Is there potential for increased shared value?

Suggestions for meaningful engagement at different points in the user journey

  1. Co-production of analytical innovation >> discussing novel ways to apply data at the beginning of a project or new data initiative.

  2. Building in feedback sessions at strategic points >> such as sense-check after analysis of data or a review prior to publication of a report.

  3. Follow-up once a data project has ended >> for the purpose of sharing 'lessons learned' at the end of a project (or within an agreed timeframe).

  4. Data showcasing sessions >> where data users come together to demonstrate how data was utilised, for example highlighting which reports, articles and publications the data contributed to, or what kind of policy decisions were influenced.