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9 June 2020 “Of Course, Data Can Never Fully Represent Reality”
Marisa Elena Duarte, Morgan Vigil-Hayes, Sandra Littletree, Miranda Belarde-Lewis
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Abstract

Multiple terms describe Indigenous peoples' creative expressions, including “Indigenous knowledge” (IK), “traditional ecological knowledge” (TEK), “traditional knowledge” (TK), and increasingly, “Indigenous data” (ID). Variation in terms contributes to disciplinary divides, challenges in organizing and finding prior studies about Indigenous peoples' creative expressions, and intellectually divergent chains of reference. The authors applied a decolonial, digital, feminist, ethics-of-care approach to citation analysis of records about Indigenous peoples knowledge and data, including network analyses of author-generated keywords and research areas, and content analysis of peer-reviewed studies about ID. Results reveal ambiguous uses of the term “Indigenous data”; the influence of ecology and environmental studies in research areas and topics associated with IK, TEK, and TK; and the influence of public administration and governance studies in research areas and topics associated with ID studies. Researchers of ID would benefit from applying a more nuanced and robust vocabulary, one informed by studies of IK, TEK, and TK. Researchers of TEK and TK would benefit from the more people-centered approaches of IK. Researchers and systems designers who work with data sets can practice relational accountability by centering the Indigenous peoples from whom observations are sourced, combining narrative methodologies with computational methods to sustain the holism favored by Indigenous science and the relationality of Indigenous peoples.

Copyright © 2020 Wayne State University Press, Detroit, Michigan 48201
Marisa Elena Duarte, Morgan Vigil-Hayes, Sandra Littletree, and Miranda Belarde-Lewis "“Of Course, Data Can Never Fully Represent Reality”," Human Biology 91(3), 163-178, (9 June 2020). https://doi.org/10.13110/humanbiology.91.3.03
Received: 12 August 2019; Accepted: 18 December 2019; Published: 9 June 2020
KEYWORDS
data science
indigenous data sovereignty
Indigenous knowledge
informatics
information science
traditional ecological knowledge
traditional knowledge
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