Data decolonization

Data Decolonization

Data decolonization is the process of divesting from colonial, hegemonic models and epistemological frameworks that guide the collection, usage, and dissemination of data related to Indigenous peoples and nations, instead prioritising and centering Indigenous paradigms, frameworks, values, and data practices. Data decolonization is guided by the belief that data pertaining to Indigenous people should be owned and controlled by Indigenous people, a concept that is closely linked to data sovereignty. Data decolonization is linked with the concpet of decolonization of knowledge.

Data decolonization seeks to counter the negative narratives that are reinforced by the colonial data practices that persist in a post-colonial era.

History of Data Colonization

In various colonial states, data was used to identify Indigenous peoples using Western classification systems, leading to erasure of Indigenous identities, and the origin of narratives that focus on disadvantages in Indigenous communities. The values that guide Western data practices, such as universalism, homogeny etc. diverge from Indigenous values such as principles that value diversity [cite healthcare] and valuing the individual viewpoints of the subject [cite sport]

Data Decolonization in Practice

Research

Researchers seek to engage in research that is holistic and grounded in Indigenous culture

Policies

UN Data Governance

Ottawa/Canada

Also look at

Indigenous Decolonization