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

Community enabler(s)

For open data user communities to run effectively and sustainably, there must be a clear understanding of what enables the community group structure

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Last updated 2 years ago

  1. Funded or project-based communities

Some communities are lucky enough to be funded by an organisation or a collection of organisations. These might be community initiatives set up by an organisation or initiatives where community organisers have asked organisations to provide grant or project funding so the community is sustainable in the short term.

Funded communities are likely to have core funding, meaning they can exist to serve a broad mission and vision without necessarily needing clearly defined deliverables. They may also exist indefinitely, rather than having a specific lifecycle. runs its own as part of its core business model, which helps members to connect around data and work together to solve problems. Project-funded communities are more likely to have a set of predefined outcomes and outputs and will have a set timeline for the existence of the community group. For example, is a community-owned, research based initiative, where community members use data about themselves to deliver research that is commissioned by businesses and local governments.

  1. Membership communities

Membership communities are groups which require users to sign up to get full benefit from the community. These community groups have a clear individual or group that manages the community and facilitates access to the group for new members.

The type of membership model a community uses can vary; some will be free for anyone to join, such as the ; a member-based community that helps people to connect with each other around data and AI and learn new data skills in these areas. Other communities might require members to pay a membership fee, which allows community organisers to provide their members with more support and resources. For example , an open data publishing platform for researchers, runs a that allows members to access additional features, training and support on the platform and other perks.

  1. Self-organising communities

Self-organising communities are groups that do not have a formal membership structure. These groups can still have an informal membership, where individuals are invited to join via contacts who are in the community, but more often than not, the group will encourage new members to join through public channels, such as social media. The is an example of a self-organising knowledge-sharing community that uses social media as a platform for collaboration.

Self-organising communities tend to be smaller in scale, often working at a regional or local level and tend to encourage members to meet through specific events or to work informally through generic networking platforms. For example, the focuses on bringing people together to discuss how open data and civic technology can bring greater benefits for the city.

Data.world
open data community
Community Data Cooperative
Data Lab Community
Dryad
membership community
Open Data Community for Hong Kong
Buffalo Open Data Community