Principles of Data Feminism,  Catherine D’Ignazio and Lauren F. Klein
Principle 1: Examine power
Data feminism begins by analyzing how power operates in the world.
Principle 2: Challenge power
Data feminism commits to challenging unequal power structures and working toward justice.
Principle 3: Elevate emotion and embodiment
Data feminism teaches us to value multiple forms of knowledge, including the knowledge that comes from people as living, feeling bodies in the world.
Principle 4: Rethink binaries and hierarchies
Data feminism requires us to challenge the gender binary, along with other systems of counting and classification that perpetuate oppression.
Principle 5: Embrace pluralism
Data feminism insists that the most complete knowledge comes from synthesising multiple perspectives, with priority given to local, Indigenous, and experiential ways of knowing.
Principle 6: Consider context
Data feminism asserts that data are not neutral or objective. They are the products of unequal social relations, and this context is essential for conducting accurate, ethical analysis.
Principle 7: Make labor visible
The work of data science, like all work in the world, is the work of many hands. Data feminism makes this labor visible so that it can be recognized and valued.