DPHU1008 Chap.3 Indigenous Data Sovereignty and 5D Data
Indigenous Data Sovereignty and 5D Data
A course learning outcome asks you to situate data in relation to settler colonialism and to engage with First Nations approaches to data and justice. The readings come from the collection Indigenous Data Sovereignty: Toward an Agenda. C.
Matthew Snipp defines data sovereignty as managing information according to the laws and customs of the nation where it sits, and sets out three features of decolonised data: communities decide who is counted, what data contain, and who may access them.
The lecture also lists 5D data.
In Maggie Walter's published framework the five Ds are difference, disparity, disadvantage, dysfunction and deprivation, and a statistical portrait built only from them describes a people solely through deficit.
Megan Davis writes about data at the United Nations, where self-identification and acceptance by the group keep membership decisions with communities.
These readings connect directly to the course outcome on First Nations approaches to data and justice, and they give you precise questions to ask of any data about a people: for whom were the data collected, how, what was measured, who controls the information and what is it for?
Snipp also notes two practical supports for sovereignty: in-house data expertise and tribal ethics boards that review research proposals.
What this chapter covers
- 01
Data sovereignty: managing information by a nation's own laws and customs
- 02
Who is counted: communities decide membership
- 03
What is collected: content reflects community priorities
- 04
Who has access: communities control dissemination
- 05
5D data: difference, disparity, disadvantage, dysfunction, deprivation
- 06
Self-identification and group acceptance in UN practice
- 07
Five expert questions: for whom, how, what, who controls, what for
- 08
Privacy and sovereignty in tension when small-area figures are suppressed
- 09
In-house expertise and ethics boards as supports for sovereignty
Worked example · free
Applying the three features to a census question
- +1Who is counted: the state, not the community, defines belonging through a box designed for its own categories.
- +1What is collected: one identity box records no nation, language or community priority, so the data serve administration.
- +1Who has access: results are released by the state, so communities depend on outsiders to see their own figures.
Key terms
- Data sovereignty
- The principle that information is governed by the laws and customs of the nation it concerns.
- Decolonised data
- Data whose membership, content and access are decided by the Indigenous community concerned.
- 5D data
- Walter's term for statistics that portray Indigenous peoples through difference, disparity, disadvantage, dysfunction and deprivation.
- Self-identification
- A person's own statement of Indigenous identity, paired in UN practice with acceptance by the group.
- Deductive disclosure
- The risk that individuals can be identified from small-area figures, which leads agencies to suppress them.
- Expert-group questions
- Five UN workshop questions asking for whom, how, what, under whose control and for what data are collected.
Indigenous Data Sovereignty and 5D Data FAQ
Who wrote 'What does data sovereignty imply' if Moodle lists Megan Davis?
The chapter itself names C. Matthew Snipp as its author, while Davis wrote a different chapter in the same collection on the UN declaration. Reference each chapter under its own author in your Harvard list.
Is 5D data about inaccurate statistics?
Not necessarily. Each figure can be correct; the critique concerns the pattern of choosing only deficit measures, which turns a whole people into a problem to manage and hides strengths that communities themselves would count.
How can privacy rules work against Indigenous communities?
Snipp shows that agencies suppress figures for very small areas to protect individuals, but that can leave a small tribe unable to document its own poverty. Privacy and sovereignty can therefore pull in different directions.
Why does the course connect data to settler colonialism?
One of its learning outcomes asks you to situate data in relation to settler colonialism and engage with First Nations approaches to data and justice. The readings show settler states defining membership, choosing measures and controlling access to data about Indigenous peoples.
What practical steps does Snipp suggest toward data sovereignty?
He names two mechanisms. Expertise in producing and managing data is essential, from surveys to archives and websites, and ethics oversight boards run by tribes can review research so that local knowledge is not exploited.
Assessment move
Make a one-page comparison of Snipp and Davis: his three features on one side, her five expert questions on the other. Practise applying both to a health or education infographic you find online. When you write about 5D data, pair every deficit measure you notice with a strength measure the community might choose, and reference each reading under its correct author.
Find one published statistic about a First Nations community and ask whether the community chose that measure or had it chosen for them. Note the publication details of each chapter as you read, since the authors are easy to confuse.
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