Community-Centric Data Principles.

Welcome to Data Uncollected, a newsletter designed to enable nonprofits to listen, think, reflect, and talk about data we missed and are yet to collect. In this newsletter, we will talk about everything the raw data is capable of – from simple strategies of building equity into research+analytics processes to how we can make a better community through purpose-driven analysis.

What would you say if I said – based on all that we are learning, hearing, talking, and sharing in the community – it's time we create this "living document" to state the principles of community-centric, justice, and inclusion grounded data?

 We have been exploring data from different angles in this newsletter for these past few weeks. You and I are building this space of good-struggle together. Shouldn't we tap into that energy to claim more clarity around data? Today, we are doing something different, critical, and hopefully shorter than our usual 2500-words "talk" here.

 You and I will put our minds together to lay some fundamentals around data.

 Now I will be honest. I struggled with this article's title (how do I put all my intentions into 3-5 words of a title?). Should it be IDEA-grounded Data Principles? Community-Centric Data? Justice-driven Data? Or maybe Data Uncollected Network Principles? Finally, I realized titles don't matter (just like it doesn't matter if I call myself Founder, Chief, or Consultant – what matters is my intention to show up and explore solutions with you).

 So, listen to my intentions, not just the words in the title. I am laying 6 truths here that I hope you and I can call our "data fundamental". We all have a relationship with data – some collect it, some passionately analyze it, some build tools and tech around it, and some consume it via insights. Simple or complicated, by choice or not – we all have a role and responsibility when it comes to data. Any denying of that relationship (with data) affects our community, our people – because then we give unknowingly green light to all sorts of behaviors, expectations, and future ignorance towards data. Data about you and me. Hopefully, this evolving set of truths will guide us as we take turns learning and unlearning for a purpose-driven approach to our data works.

 Here goes the list:

1. The data we collect – be it for internal analysis or AI-driven tools – centers the people going to be impacted by that data, especially those usually marginalized by design.

(Example: if you plan to collect data from the stakeholders for strategic planning, include some representatives directly from the community you serve. It is not only during impact assessments that we need to collect numbers from the community but also when we are planning on the next strategic and sustainable steps).

2. The data we collect, analyze, and consume empowers and acknowledges generosity from all voices that matter.

(Example: if you are looking to broaden your understanding of engagement and philanthropy trends towards your mission, design your actions by including all people and not be limited by questions/population sample driven by upper limit giving thresholds. Generosity comes in more forms than one, and we need to account for it. For some, it might be changing the engagement analysis formula; for others, it could be tweaking the survey questions.)

3. The data we collect – be it for internal analysis or AI-driven tools – prioritizes the needs of the community over the intentions of individual (or a group of) collectors.

(Example: every occasion we get to evaluate what data we are collecting for all forms of analysis/AI tools, discuss and define why those data points are collected vs. those that are retired/uncollected. The more we become comfortable with this why-driven struggle, the better we will learn to center the needs of the community).

4. We acknowledge that the data in itself are just numbers and text. It alone cannot create change. It is the history, context, and narrative from that data that empower us to create change. So, 

• a.  the data we consume transparently builds accountability on/from all involved stakeholders,
• b.  the what, what-next, and how decided from the data are just as crucial in centering the people.

(Example: how you hold the space for conversation from the output of data analysis (internal or given by AI tools), who is involved in the conversation, and what actions are taken next – all that matters. Collecting data by itself does not create the awareness of accountability.)

5. The data we collect represent people. So, it prioritizes ethics during collection and is used to build narratives as humanly as possible.

(Example: Words we choose to communicate matter. Therefore, the words we used to collect data, say in the surveys and draw insights in the reports matter. Those words give or diminish power from all those impacted by the outcomes of such a report.)

6.  We (as data collectors, scientists, technologists, consumers, and any other relevant forms) are not the experts of data. We are evolving continuous learners – of the needs of the community we live in, the ethical practices of data collection + analysis, the gaps between intentions, and the knowledge we possess.

(Example: We will never be perfect in the solutions we design and adopt. We can, however, improve and adapt. Let's add that humility in the way we interact with data.)

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This is not a one-time, one-size-fits-all list. This is a start – of some agreements, some healthy challenges, and a chance to reflect through them.

That is why you and I will revisit these truths once again in the next few months. We must - for the social justice you and I seek.

*** So, what do I want from you today (my readers)?

Today, I want you to

• Share what resonates and is missing in these principles? What else must we ask and acknowledge through this list?
• Remember these principles. The power of this list lies when we consciously follow it together.

***For those reading this newsletter for the first time, here is some intro of this newsletter for you. :)