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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  1. Section 3. A user-centric approach to publishing
  2. Building communities around open data use
  3. Characteristics of an open data user community

Purpose

Having a common community purpose is important in helping members of communities to understand what they can do together as part of the community, as well as what other members might expect from them

PreviousCharacteristics of an open data user communityNextCommunity enabler(s)

Last updated 2 years ago

In our research to date, it is apparent that open data user communities exist primarily to serve one or more of three purposes:

  1. Knowledge sharing

Many open data user communities exist primarily to facilitate knowledge sharing amongst peers. This can include examples of ongoing work with data, best practice on specific topics or activities, challenges people have faced in their work with data and much more.

With knowledge sharing communities, participation is often self-motivated, as people are there primarily to learn and to be able to take those learnings away and apply them in their own work with data.

Knowledge sharing communities do not need to have a specific focus; there are many examples of these types of communities where data is the broad topic of conversation and community members come together to talk about things that interest them personally. For example, the , a community run by open data supporters across Canada, focuses on a range of topics, from use of data to advocacy for openness.

There are also some knowledge sharing communities that look at particular data or social challenges, or operate with a specific geography or scale in mind.

  1. Practical collaboration

Some open data user communities take a more practical approach to collaboration, with a focus on creating information from data – in the form of products and services, analyses and insights, or stories and visualisations – such as the on GitHub, a community set up to build useful visualisations for the spread of Covid-19 using biomedical and environmental datasets.

These types of communities are usually working to address specific shared social, economic or environmental problems that the community faces. is an example of a local community that aims to create positive impacts for the people in Bath and North East Somerset, UK, through more effective use and publication of data, looking at challenges around water and air quality, and education.

  1. Building infrastructure

Other open data user communities exist in a capacity to help people and organisations use data more effectively, by helping to collaborate around maintaining open data infrastructure. These communities could be working on the data itself, ensuring that it is fit for purpose, like the , which helps people to build a collective map of their local area and connect it with other community maps from around the world. Infrastructure communities may also be looking at data standards, technical infrastructure and processes around data access and use. For example, the hosts that focus on building standards to help others more effectively use data.

There are parallels that can be drawn between these types of open data user communities and the open source community, such as the tools that they use to collaborate, like , and the types of activities that they work on together, such as on the .

Canadian Open Data Society
Covid-19-Community
Bath: Hacked
OpenStreetMap Community
World Wide Web Consortium (W3C)
a number of community group forums
GitHub
collaborative maintenance of data