What Data Relationship are You In?

When we want to address equity in data science, we often need to talk about power and we sometimes need to talk about money. It can be useful to think about an individual’s data like a raw resource, you could call it something cheesy like “Dataonium”. There’s a reason that our icon for Step #4: Data Collection & Sourcing in the Data Equity Framework has a pickaxe in it. The fact that data science uses words like “mining”, “raw”, “refining”, “cleaning”, “pipeline”, “ETL (extract, transform, load)”, and more is no coincidence.

We’ve got other articles that deal with some of the issues around paying for data or crafting Funding Webs, but what I want to talk about today is the equity relationship that you (and your project) have with the people who are your data source. Well, I want to talk about the one you have versus the one you think you have.

Four intertwined ideas to think about when you’re looking at this:

1. Price: Who sets what the data is exchanged for.
2. Ownership: Who retains, gets, or loses; control, access, or proprietorship over the data.
3. Value: Who determines what the data is worth.