Data Justice


Data Justice is the promotion of truth and storytelling that rests on consent from community members seeking services and the organizations who provide services to support them.

Download the working document:      Click here!  


What is Data Justice? How does it show up? In the non-profit sector, data is often extracted from the community or program participants for purposes of reporting to interested groups and funders both public and private. The communities sharing data (including both individual program participants as well as non-profits themselves) are rarely involved in decisions about what data is collected, what happens with that data, and what actions are considered from data results. This is an imbalance of power and in a way, transforms the data into a form of currency that can be exchanged for basic needs, housing, or for nonprofit grant dollars. We posit that this relationship has a direct impact on harnessing truth, storytelling, and organizations’ ability to make data-informed decisions to improve the programs and services they offer. This relationship impacts community trust and the quality of the data that people choose to share about themselves and their situation. MACC Data Network envisions a new relationship and partnership with data, communities, non-profits, and funders grounded in data justice.


Defining Data Justice

Data Justice is the promotion of truth and storytelling that rests on consent from community members seeking services and the organizations who provide services to support them.

Data Justice seeks to bring light and awareness to the whole person and the whole community: strengths, talents, resiliency (not just flaws, traumas, and a percent of poverty level). Data Justice ensures that all interested groups are held accountable to the data they receive, that they honor the data and the person who shared it - in purpose, in use, in decision-making, in actions. Data Justice examines not just the use of data but also the methods of data collection: what questions asked, how the questions are framed and phrased, who collects the data, when the data is collected, where it is stored, and how it is maintained.  Data Justice is fluid and shifts in its learning. It holds a mirror to its past, is flexible in its path and is a vehicle to do better in the future.


Data justice is the collection, analysis, sharing, and use of data entirely in service of and with accountability to participants and their communities. Data justice is a lens to evaluate the intended or unintended consequences of researching or collecting data on individuals and communities. Data justice values the dignity, privacy, and humanity of all people. Data justice is active resistance to all oppressive systems within the arena of data as a part of building a better world that promotes dignity, consent, truth, accountability and learning. This work will be necessary as long as oppressive systems exist.


Data justice includes:

  • Collecting no more than the minimum amount of participant data required to provide services
  • Handling participant data securely and maintaining participants’ data privacy
  • The analysis and sharing of that data with intentionality, using an asset-based framework, and situated within the appropriate social contexts
  • The use of that data to support participants directly, respond to changing needs discovered through evaluation, and proactively address systemic challenges uncovered
  • Accountability to the people being served and their communities



Principles of Data Justice

Our principles of Data Justice for human services organizations:

  • Data that is collected from clients should ultimately serve the client and community
  • Data that does not serve clients/communities should not be collected
  • Data should be treated with care and maintained securely and privately
  • We should consider the emotional impact that the act of data collection can have on a person, particularly as it relates to sensitive topics.
  • We should consider the balance of power in the situations or circumstances in which data are shared
  • Narratives and information about communities and individuals should be true and not fabricated or assumed
  • Data should only be obtained, used, or distributed with consent and transparency
  • All elements of a data collection plan should be assessed through a data justice lens



Who is involved in Data Justice?

Some of the collaborators within Data Justice are:

  • Communities and individuals ​
  • Front-line workers and case managers ​
  • Managers and executive leaders ​
  • Data Administrators​
  • Grant Writers​
  • Evaluators /Story-tellers​
  • Government Contractors/Compliance department​
  • Funders​
  • Boards​
  • Strategic Planning Committees​
  • All of us!


A Note:
The language on this page and in the working document focuses on data justice within the context of community-based organizations and human service nonprofits. We acknowledge the work already done on this topic prior to our involvement and that parallel conversations are needed to address data injustice in all sectors from social media, healthcare, education, consumer capitalism, and beyond. We are starting our work at home, here in the non-profit sector in our role as the Metropolitan Alliance of Connected Communities. 



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