Questions to Ask Frequently (QAFs) when working with Data and Marginalised Communities

This list of questions was derived during a session at the Responsible Data Forum in Oakland on March, 6th 2014. Our desire was to create a list of questions to ask yourself when working as an intermediary with marginalised communities. The answers you will come up with, might or might not require you to think in new ways or change what you are doing, but at least you might have a few more known unknowns that you can work on.

We chose this format because we do not know the answers or if lessons learned from previous projects can travel across contexts. It is a conversation we are just starting and we would love to get your input. Frankly, frequently asked questions (FAQs) would have been a little too passive, is a little too generic and assumes we know it all, which we don’t.
Questions to Ask Frequently (QAFs) about the Community

If you are gathering data, analysing it or designing data-driven advocacy strategies, you are doing it with and for a community.  You will only be able to do things well when you understand and respect them and your relationship to them.

  • Who is the community? What are the boundaries that surround it in terms of: ethnicity, identity, gender, race, class, sexuality, disability, language, religion, size, citizenship status, geography, etc?
  • What makes this community marginalised? Is it persecution and alienation from services and rights, or a combination?
  • Do you understand your own prejudice about the community? Can you keep an open mind and allow you biases to be challenged?
  • Do you fully understand the context and nuances of this community? What can you learn to assure your intervention will have a positive impact? What resources are available for training or advice?
  • Do you have ongoing informed consent with the community on your activities? How have you documented the consent?
Preparing data for examination by sex worker advocates

Preparing data on violence for examination by sex worker advocates

QAFs about empowerment and capacity building

Once you better understand the community and your relationship with them, you should assess how data literate they are, and what extent they comprehend what you want to do with them. Based on this, you might want to further investigate needs for capacity building or if a an intervention is needed to empower the community.
  • Do you understand the implications around data ownership? Are you taking power away from a community by being in control of the data?
  • Who is actually making the decisions about the data and what are the implications?
  • Are your activities dis-empowering the community?
  • Who should analyse the data? Is this an important skill for them to learn for the long run?
  • What does the data tell them? Do they understand the implications of sharing the findings?
  • How can you assure the community has the opportunity for relevant and effective learning in connection to the data?
  • Does the community have the capacity to store and protect the data adequately? Does the community have appropriate access to the data if they aren’t storing it themselves? In particular, what are the procedures to protect the data from loss?
  • Does the community have appropriate access to the data if they aren’t storing it themselves?
  • What are relevant data sets for correlation?

Q.A.F’s about privacy, security, threats and safety

Data, if analogue or digital, is fragile. It can be lost, stolen or tampered with and the consequences can be grave. These questions provide you with some guidance in discovering if your security plan is fail-safe and protected from intruders, or when the data is public, it cannot put vulnerable people at risk or identify those who have not given consent.

  • Do you have full understanding what is sensitive data in the context of this community?
  • Can you detail the risks and the threats? In particular, have you thought about displacement, imprisonment, death, violence/abuse, and exploitation?
  • What are the implications of data loss?
  • Is anonymising names enough to protect the community?  Can the data be triangulated to identify a vulnerable entity (i.e, an individual, a village, a district, etc.)? What are the implications when the data is being correlated to other data sets.
  • Is it appropriate to falsify names? (change the names to protect people)
  • How can the data be used for other purposes? Is there a possibility it can be misused (ie, a property developer using data about a slum?).
  • Are you behind or ahead of the curve for best practices of data management in your region/sector? What are other organisations doing?

Contributors to this list of QAF’s were Friedhelm Weinberg, Jordan Ramos, Tin Gerber,  Aseem Mulji, Michael Bochenek, Martin Dooley, Kellie Brownell, Adrian Sawczyn and Myself.  Read this blog post in Spanish on the Center for Economic and Social Right’s Website.