Annex A. Topic guide structure for roundtable discussions and in-depth interviews


What is one success you’ve had improving equality and inclusivity of data, statistics, analysis and their presentation (if any)?

What is one key question around inclusivity and representation you would like to be able to answer?

  • What successes have you experienced in trying to answer this question?
  • What struggles have you experienced in trying to answer this question?


  1. Data Sources
    1. What sources of data do you find most useful for addressing equality issues in your role?
    2. Any challenges with these sources?
    3. What sources of data do you often have issues with, in terms of inclusivity?
      1. What are these issues?
    4. If applicable: What are your views on the potential for administrative data sources to address your data needs?
      1. Any concerns about administrative data?
  2. Identified gaps and implications
    1. Are there any specific gaps in the data that you use that could be addressed?
    2. What barriers are there that prevent filling these data gaps?
    3. What are the impacts of these gaps on:
      1. Your organisation (such as in developing policy, communication and your  organisational aims?)
      2. Your key stakeholders?
      3. The equality groups that the data affects?
    4. What can be done to fill these data gaps or create more inclusive data?
  3. Research and survey design
    1. How does research and survey design create barriers to equality and inclusivity of data?
    2. How can we ensure everyone is included in data collection?
    3. Can we resolve these barriers? How?
    4. How do we ensure we’re asking the right questions?
  4. Engagement
    1. What steps do you take to encourage wide engagement and participation in research?
    2. What are the barriers to engaging with under-represented groups to encourage participation in research?
    3. How [else] can we address these?
    4. How can engagement be used to improve inclusivity?
    5. How can we ensure that the learnings from engagement are used widely?
    6. How do you engage with issues of trust about participation in research and data sharing among the general public or under-represented groups?
    7. How do we ensure all members of society feel represented in data, analysis and outputs?
      1. Any specific examples?
  5. Harmonisation and coherence
    1. What impact does harmonisation and statistical coherence have on the inclusiveness of data?
    2. What issues (if any) have you experienced with harmonisation and statistical coherence in your role?
    3. Are there changes that could be made to address harmonisation and coherence and improve inclusivity of data?
  6. Outputs
    1. How important is it that analytical outputs are accessible to all? (Produced by your and other organisations.)
    2. How represented do different sections of society feel in your analytical outputs?
    3. What more could be done? Current challenges?
    4. How can we make sure that even the digitally excluded are included in data collection and able to access the outputs?
    5. Do you have any strategies in place to reduce the barriers faced by the digitally excluded?
    6. Are there any further thoughts you had on how to make data, analysis and outputs that you use or produce more inclusive?

Finally, would everyone be able to tell me the top issue that they would like considered by the Inclusive Data Taskforce?

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