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Indigenous Data Sovereignty, in its proclamation of the right of Indigenous peoples to govern the collection, ownership , and application of data, recognises data as a cultural and economic asset. The impact of data are magnified by the emergence of Big Data and the associated impetus to open publicly held data (Open Data). Aboriginal and Tor-res Strait Islander peoples, families and communities, heavily overrepresented in social disadvantage related data will also be overrepresented in the application of these new technologies. But, in a data landscape Indigenous peoples remain largely alienated from the use of data and its utilization within the channels of policy power. Existing data infrastructure , and the emerging Open Data infrastructure, neither recognise Indigenous agency, worldviews nor consider Indigenous data needs. This is demonstrated in the absence of any consideration of Indigenous data issues Open Data discussions and publication. So, while the potential benefits of this data revolution are trumpeted, our marginalised social, cultural and political location suggest we will not share equally in these benefits. This paper discusses the unforeseen (and likely unseen) consequences of the influence Open data and Big Data and discusses how Indigenous Data Sovereignty can mediate risks while providing pathways to collective benefits.
Indigenous Data Sovereignty in the era of Big
Data and Open Data
Maggie Walter
Raymond Lovett
Bobby Maher
Bhiamie Williamson
Jacob Prehn
Gawaian Bodkin-Andrews
Vanessa Lee
University of Tasmania, Hobart,
Tasmania, Australia
Australian National University,
Australian Capital Territory, Canberra,
University of Technology Sydney,
Sydney, New South Wales, Australia
The University of Sydney, Lidcombe,
New South Wales, Australia
Maggie Walter, University of Tasmania,
Hobart, TAS, Australia.
Received 7 July 2020. Revised 1 October
2020. Accepted 1 October 2020
Indigenous Data Sovereignty, in its proclamation of the
right of Indigenous peoples to govern the collection, own-
ership, and application of data, recognises data as a cultural
and economic asset. The impact of data are magnied by
the emergence of Big Data and the associated impetus to
open publicly held data (Open Data). Aboriginal and Tor-
res Strait Islander peoples, families and communities, heav-
ily overrepresented in social disadvantage related data will
also be overrepresented in the application of these new
technologies. But, in a data landscape Indigenous peoples
remain largely alienated from the use of data and its utilization
within the channels of policy power. Existing data infrastruc-
ture, and the emerging Open Data infrastructure, neither
recognise Indigenous agency, worldviews nor consider
Indigenous data needs. This is demonstrated in the absence of
any consideration of Indigenous data issues Open Data discus-
sions and publication. So, while the potential benets of this
data revolution are trumpeted, our marginalised social, cul-
tural and political location suggest we will not share equally
in these benets. This paper discusses the unforeseen (and
likely unseen) consequences of the inuence Open data and
Big Data and discusses how Indigenous Data Sovereignty can
mediate risks while providing pathways to collective benets.
Aboriginal people, accountability, partnerships, policy, productivity
DOI: 10.1002/ajs4.141
Aust J Soc Issues 2020;114 ©2020 Australian Social Policy Association 1
Aboriginal and Torres Strait Islander
peopleslives and futures are intricately entwined with
Indigenous data. The realisation of articles of the United Nations Declaration on the Rights of
Indigenous Peoples (UNDRIP), the Uluru Statement from the Heart, the effectiveness of
Refreshed Closing the Gap partnership and an Indigenous Voice to Parliament are all reliant
on high quality, relevant, disaggregated Indigenous data that reect Indigenous perspectives,
priorities and needs (Taylor & Kukutai 2015; Davis 2015, 2016). But in Australian national
data collections, the place of Indigenous Peoples is predominantly limited to the object of
study, with data collection rmly focussed on how poorly our populations fare across health,
education, economic participation and other socioeconomic indices. As argued by Indigenous
researchers in Australia and elsewhere, this focus creates a dominant data narrative of Indige-
nous Peoples dened by their statistically measured disparity, deprivation, disadvantage, dys-
function and difference (referred to as 5D data) (references omitted to preserve the peer review
process; Smith 2012).
The simplistic, frequently aggregate presentation of such 5D data as found in the plethora of
governments reports (see, e.g., Overcoming Indigenous Disadvantage and the health and welfare of
Australias Aboriginal and Torres Strait Islander peoples) add to the inadequacy of this data environ-
ment. These data neither reect Indigenous realities nor provide the requisite data resources for
Indigenous communities and First Nations to fully participate in determining our own futures.
What they do reect is the state-preferred mode for the administrative ordering of an Indigenous
sub-population. And they are powerful. How the state seesits Indigenous population/s, is the
data lens by which Indigenous Peoples are made visible. It denes who and what Indigenous
Peoples are, and who and what we are not; it delineates what can be seen and perhaps more criti-
cally, what the state refuses to see (Scott 1998; Andersen 2014; reference omitted to preserve
the peer review process).
There are unique Australian issues here, but Indigenous data problematics are common, espe-
cially in the Anglo settler-colonial CANZUS countries (Canada, Australia, New Zealand and the
United States). Common also is Indigenous dissatisfaction, which has fuelled calls for more rele-
vant, Indigenous-led data frameworks since the mid-1980s (Davis 2016). The continuing lack of
progress in this area is the catalyst for the emergence of the Indigenous Data Sovereignty move-
ment. Centrally concerned with advocating and promoting Indigenous data rights and interests,
Indigenous Data Sovereignty networks are active across the CANZUS countries, including Aus-
The emergence of Big Data technologies and the associated impetus for increasing accessibil-
ity to publicly held data (Open Data) create new sites of Indigenous data tensions. These include
notions of risk related to Western ethical and privacy principles and the need to protect Indige-
nous knowledge (Battiste & Youngblood 2000; Kwaymullina 2016; Dunbar & Scrimgeour 2017).
There are potential benets, but the uncritical public sector enthusiasm for these data innovations
combined with a data infrastructure that does not recognise Indigenous worldviews or consider
Indigenous data quells Indigenous hopes and raises our level of concern (reference omitted to
preserve the peer review process). Heightened by the aligned big business and private sector
interest and investments in the political of data, this paper maps some of the unforeseen (and
likely seen) consequences of these technologies and practices. The paper also overviews people
how Indigenous Data Sovereignty can mediate some of the embedded risks in Open Data while
also providing pathways to, as yet, unrealised Indigenous collective benet.
©2020 Australian Social Policy Association
Indigenous data are any data, in any format, that relate to Indigenous Peoples, lands, resources,
communities, lifeways and cultures (Rainie et al. 2019). We limit our discussion to the multitude
of data, largely in digital form that is collected by Government entities, such as government
departments, government statutory authorities and data agencies such as the Australian Bureau of
Statistics and the Australian Institute of Health and Welfare. It is these data that are the target of
current Open Data processes (Productivity Commission 2017). They are also a central component
of the Indigenous data problem. The case outlining the inadequate and harmful nature of these
data has been demonstrated repeatedly, in Australia and globally (Kukutai & Taylor 2016b (refer-
ence omitted to preserve the peer review process); Rainie et al. 2019). With their limited scope,
aggregate format, decit focus and decontextualised framework, these data cannot, and do not,
yield meaningful portraits of the embodied realities of Indigenous lives (reference omitted to pre-
serve the peer review process). In their perpetual description of the problemin a seemingly end-
less trope of Indigenous decit, they are themselves part of the problem. They are essentially just
data of surveillance. They bear little resemblance to Indigenous life and, as such, fail to address
the critical, unfullled data needs of Aboriginal and Torres Strait Islander First Nations, commu-
nities or peak organisation (Rainie et al. 2019). The data mismatch map across ve categories, as
per Table 1, with existing data labelled by (reference omitted to preserve the peer review process)
as BADDR (Blaming, Aggregate, Decontextualised, Decit and Restricted) data.
TABLE 1 BADDR data versus Aboriginal and Torres Strait Islander data needs
Dominant BADDR data Indigenous data needs
Blaming Data Lifeworld Data
Too much data contrasts Indigenous/non-Indigenous
data, rating the problematic Indigene against the
normed Australian as the ubiquitous pejorative
We need data to inform a comprehensive, nuanced
narrative of who we are as peoples, of our culture,
our communities, of our resilience, our goals and our
Aggregate Data Disaggregated Data
Too much data are aggregated at the national and/or
state level implying Indigenous cultural and
geographical homogeneity
We need data that recognises our cultural and
geographical diversity and can provide evidence for
community-level planning and service delivery
Decontextualised Data Contextualised Data
Too much data are simplistic and decontextualised
focussing on individuals and families outside of their
social/cultural context
We need data that are inclusive of the wider social
structural context/complexities in which Indigenous
disadvantage occurs
Decit, Government Priority Data Indigenous Priority Data
Too much (way too much) 5 D data: This data that
focus on disadvantage, disparity, dysfunction,
difference, decit (Walter 2016) collected to service
government priorities
We need data that measures not just our problems but
data that address our priorities and agendas
Restricted Access Data Available Amenable Data
Too much data are barricaded away by ofcial
statistical agencies and institutions
We need data that are accessible and amenable to our
©2020 Australian Social Policy Association
A key Indigenous response to these and other data failures is Indigenous Data Sovereignty.
Indigenous Data Sovereignty afrms the rights of Indigenous Peoples to determine the means
of collection, access, analysis, interpretation, management, dissemination and re-use of data per-
taining to the Indigenous Peoples from whom it has been derived, or to whom it relates. It
derives from the inherent rights of self-determination as described in the United Nations Decla-
ration on the Rights of Indigenous Peoples (UNDRIP), and includes demand that data be used
in ways that support and enhance Indigenous Peoples collective well-being (Snipp 2016; Kuku-
tai & Taylor 2016a, 2016b; reference omitted to preserve the peer review process). A critical
central tenet of Indigenous Data Sovereignty relevant to Open Data processes is that Indige-
nous data governance rights apply regardless of where the data are held or by whom.
Informed by the ground-breaking work of the Canadian OCAP©(Ownership, Control, Access,
Possession) principles in the late 1990s (FNIGC 2014) and the seminal Workshop on Data
Sovereignty for Indigenous Peoples: Current Practices and Future Needs held at the Australian
National University in 2015 Indigenous Data Sovereignty networks are now active globally.
The United States Indigenous Data Sovereignty (USIDSN;, the Te mana
Raraunga Maori Data Sovereignty Network ( and the Maiam nayri
Wingara Australian Indigenous Data Sovereignty Collective ( are core
entities, with these groups coming together to form the Global Indigenous Data Alliance
(GIDA) in 2019 (see
Maiam nayri Wingara is an active advocate for Indigenous data practice change, nationally
and internationally. In 2018, Maiam nayri Wingara, with the Australia Indigenous Governance
Institute, convened a summit of Aboriginal and Torres Strait Islander leaders on Indigenous
Data Sovereignty. Based around the developing international scholarship, including earlier work
on Indigenous data governance in Australia (see Yap & Yu 2016; Smith 2016), this Summit
determined Aboriginal and Torres Strait Islander Peoples have the right to exercise control of
the Indigenous data ecosystem. Exercise of control is inclusive of data creation, development,
stewardship, analysis, dissemination and infrastructure to ensure that such data are as follows:
contextual and disaggregated; relevant and empowering of sustainable self-determination and
effective self-governance; accountable to Indigenous Peoples; protective of Indigenous individual
and collective interests (Indigenous Data Sovereignty Summit Communique 2018). Maiam nayri
Wingara, via its relationship with the Research Data Alliance (RDA) Indigenous Data Sover-
eignty Working Group and GIDA, participated in the rapid development (MayJune 2020) of
guidelines to protect Indigenous data interests in COVID-19 research. These guidelines, part of
the RDA COVID-19 Recommendations and Guidelines on Data Sharing (2020), outlined the
responsibilities of research funders, governments, researchers and data stewards in the collec-
tion, ownership, application, sharing and dissemination of Indigenous data on COVID-19-re-
lated issues. Within Australia, the Indigenous Data Network (IDN), based at the University of
Melbourne, is also active. Most recently, the IDN has undertaken a National Indigenous Aus-
tralians Agency funded project to establish data projects in six communities around Australia
(Wyatt 2020).
Over the last decade, the notion of Open Data, the idea that data should be available to be freely
used, re-used and redistributed (ODC 2020), has gained favour, globally. The International Open
Data Charter, to which Australia became a signatory to in 2017, describes itself as:
©2020 Australian Social Policy Association
...a collaboration between over 100 governments and organisations working to open up data
based on a shared set of principles. We push for policies and practices that enable government
to collect, share and use well-governed data, to respond effectively and accountably to our
most pressing, social, economic and environmental challenges. (ODC 2020)
The six principles espoused in the Charter are for data that are: Open by default; timely and
comprehensive, accessible and usable, comparable and interoperable, for improved governance and
citizens engagement; and for inclusive development and innovation. These principles are largely
reected in Australian Open Data strategic plans reected in documents such as the Public Data
Policy Statement (PMC 2015). More recently, Australia has moved to legislate to support better
sharing of government held data. An Issues Paper was released in 2018, and a Discussion Paper
in 2019. Data reform is now progressing to legislation in the near future under the Data Avail-
ability and Transparency Act (ONDC 2020).
Disturbingly, those in charge of instituting Open Data in Australia refuse to engage with
Indigenous data. In line with the preceding paper from the Productivity Commission (2017) Data
Availability and Use and The Governments Response to the that paper (PMC 2018), the New
Australian Government Data Sharing and Release Legislation: Issues Paper for Consultation (PMC
2018) do not include any mention of the terms Indigenousor Aboriginal and Torres Strait
Islanderin the 21-page document. Rather the data sharing principles used the 5-Safe Framework
devised for the United Kingdom Ofce of National Statistics in 2013. These are outlined, as per
Table 2, in accompanying Best Practice Guide for applying Data Sharing Principles (PMC 2019).
Given the now well-documented inadequacies of current Indigenous data, it would seem obvi-
ous that there are specic Indigenous data safety issues across all 5 themes. Yet, again, the key
document outlining how Australian data will be kept safe under this legislation, also fails to men-
tion the terms Indigenous or Aboriginal and Torres Strait Islander. Only after submissions from
Indigenous Peoples and organisations, including Maiam nayri Wingara, highlighting the specic
needs and unique risks to Indigenous Peoples in Open Data, did the next document, Data Sharing
and Release Legislative Reforms Discussions Paper (Commonwealth of Australia 2019), include any
recognition of Indigenous data needs. A new section now says:
We have heard the need to pay close attention to matters related to Indigenous data We
heard concerns relating to Indigenous access to Indigenous data and Indigenous data sover-
eignty. The National Indigenous Australians Agency is in the early stages of developing a
more effective approach to Indigenous data, including a possible whole-of-government Indige-
nous data strategy and we are working together to get it right. (PMC 2019: 7)
Despite such an afrmative statement, as of July 2020 there has been no further word on how
Indigenous data will be got right.And the foreshadowed Whole of Government Indigenous Data
TABLE 2 Five Safesframework
Safe projects Is this use of the data appropriate?
Safe people Can the users be trusted to use it in an appropriate manner?
Safe settings Does the access facility limit unauthorised use?
Safe data Is there a disclosure risk in the data itself?
Safe outputs Are the statistical results non-disclosive?
Source: Desai et al. (2016), Five Safes: designing data access for research:5.
©2020 Australian Social Policy Association
Strategyhas failed to eventuate. It is our conjecture that the lack of strategy or indeed, a wider
movement from within government, represents a refusal to seriously and meaningfully engage
with Indigenous data sovereignty. There is a fear that this refusal will bear long-term conse-
quences given introduction of Open Data legislation. It is clear that the cursory engagements,
such as those mentioned here, are more platitude than active process.
Yet, the approach we highlight here is supported by substantial academic literature identifying
how government (among others) can meaningfully engage with Indigenous Peoples. As Hunt
(2013:33) states, Indigenous engagement: best in a framework that respects Indigenous control and decision making and sup-
ports development towards Indigenous aspirations. Early engagement to enable deliberation
about shared goals is necessary, and support for Indigenous governance development and
capacity to engage is important.
Open Data processes and the place of Indigenous data with these are increasingly identied as a
site of tension, in Australia and globally (Rainie et al. 2019). Yet, the presenting rationale for
opening up government held data are framed almost as an unquestionable good. As per the Best
Practice document (2019:6), data sharing will enable data to be used more effectively to solve
complex policy issues that cant be addressed when data remains in siloes across government.
This is a laudable sentiment. But the stark absence of Indigenous Peoples in the establishment of
Open Data processes is for Aboriginal and Torres Strait Islander Peoples more threat than pro-
mise. While the Big Data technologies and its associated Open Data enablers are new to bureau-
cratic thinking, the thinking in relation to Indigenous data remains rmly xed in the past. Now,
as then, we are invisible and unconsidered. Yet as has been repeatedly shown, Indigenous data
are not just the dataabout Indigenous Peoples. They are data that underpin a data narrative of
decit (reference omitted to preserve the peer review process). Opening up such data without
appropriate safeguards is far more likely to perpetuate this narrative than solve any complex
Indigenous policy issues (reference omitted to preserve the peer review process).
Scotts 1998 thesis on how the Nation State makes sense of its populations is useful in unpack-
ing the risks of Indigenous Open Data under the current framework. Scott identies four intercon-
nected conditions aligned with seeing like a statethat if co-occurring can translate to policy
disasters of truly epic proportions. Of these, the rst two are most directly applicable, but all have
salience. The rst condition is the administrative ordering that the State undertakes to make a
society legible (i.e., Census). These, by necessity, use transformative and often radical simplica-
tions of social environments so that exceptionally complex, illegible and local social practices
(1998:2) are standardised to allow central recording and monitoring. The resulting data do not rep-
resent the reality of the society that is being depicted, only the slice that is of interest to the state.
Applied to Indigenous data, it is easy to see that the slice of Aboriginal and Torres Strait Islander
social and cultural life of interest to the nation state is limited to those that t into underpinning
framework of Indigenous Peoples as both problematic and in need (Andersen 2014). Making these
data available to outside researchers and/or data linkage processes will magnify not reduce the def-
icit trope. Aboriginal and Torres Strait Islander populations are heavily overrepresented in
©2020 Australian Social Policy Association
datasets that measure disadvantage and inequity, so are highly likely to be the objects of research
and analytical enquiry (reference omitted to preserve the peer review process). With no considera-
tion of the knowledge or capability sets of agency staff or researchers, determinations about how
these data will be used will be made without the expertise, agency, knowledge, involvement or
most particularly, the permission of the Indigenous Peoples to whom those data relate.
The second element of Scotts (1998) four conditions for policy disaster is what he refers to as
a high-modernist ideology. This term translates to a self-condence about scientic and technical
progress associated with a presumed rational design for social order. The relatively uncritical
embrace of Big Data and Open Data policies ts very snugly into this denition. And this high
modernist leads directly to another repeat mistake. An embedded belief in the rhetoric on Open
Data is in the potential of the computational power of Big Data technologies, and the huge pools
of administrative data they can analyse will allow social problems to be understood in ways not
previously possible. But more open data or bigger data are not necessarily better data. The value
of the data, no matter the size, depends on the validity and range of the variables represented. If
all that is available is a series of 5D datasets (health inequity, justice system over-representation,
poorer educational outcomes, labour market disadvantage, etc.), then the answer to whatever
complex Indigenous social issue is under investigation, no matter how complex the analysis, will
always be to x the decit Indigene (reference omitted to preserve the peer review process). With
nearly 200 years of failed Indigenous Policy based on such data, there is nothing to suggest that
Open Data and Big Data processes will not just lead to more of the same.
The third and fourth elements identied by Scott (1998:5) is an authoritarian state, willing to
use its power to bring high-modernist designs into being, combined with a society that lacks the
capacity to resist the machinations and policy imposition of the state. For Aboriginal and Torres
Strait Islander Peoples, our primary relationship with the Nation State has been and continues to
be framed around coercion (Smith 2012). The Northern Territory Emergency Response, the
forced imposition on Aboriginal communities of welfare quarantining(Davey 2017), provides
examples of the heavy ongoing use of State powers in state/Indigenous interactions. As Scott
(1998:97) himself notes, Colonial regimes are particularly prone to social policy experimentation
on Indigenous populations noting that [A]n ideology of welfare colonialismcombined with the
authoritarian power inherent in colonial rule have encouraged ambitious schemes to remake
native societies.The marginalised Indigenous position within the Australian nation state means
that we are far more likely to face the dangers inherent in Open Data and less likely to have the
resources or the position at the decision-making policy table to reap any benets. In data terms,
this power imbalance is manifest in how Indigenous Peoples continue to be so easily erased from
the systems that determine data access, use and interpretation.
Open Data risks moving Indigenous Peoples, already largely marginalised from Indigenous data
processes, even further away from the decision making on data of which they are the subject (ref-
erence omitted to preserve the peer review process). In Open Data terms, this is not to deny the
potential for good outcomes. Rather, it is our contention that the uncritical bureaucratic approach
limits both the ability of current data stewards to identify the unique risks that Indigenous Peo-
ples may face, or provide the data necessary for Indigenous Peoples, communities and First
Nations to realise their own goals. This is a situation of deep Indigenous unease. One of the
©2020 Australian Social Policy Association
common responses when Aboriginal and Torres Strait Islander Peoples seek control in relation
to data is that we are seeking special privileges. This line of logic fails to acknowledge that the
majority of other Australians have their power structures entrenched across all societal systems
including across data systems. These same systems were historically excluded Aboriginal and
Torres Strait Islander Peoples, and it is these systems that continue to exclude Indigenous Peo-
ples from Open Data processes.
Open Data require an Indigenous cultural and social licence and the Indigenous Data Sover-
eignty movement is actively advocating for the inclusion of Indigenous data governance systems
within Open Data systems. Indigenous data governance refers to formal mechanisms, which can
assert Indigenous data interests in relation to the when, how and why of how data are accessed
and used and ensuring Indigenous data practices reect Indigenous priorities, values, culture and
diversity (Maiam nayri Wingara 2018). This advocacy is national and international. For example,
the United Nations Special Rapporteur on the right to privacy has called for member govern-
ments to recognise Indigenous Data Sovereignty in the context of big and Open Data (United
Nations 2017; reference omitted to preserve the peer review process) to mitigate, at least to some
extent the signicant aws in mainstream assumptions of ownership, representation and control
in these data communities (Rainie et al. 2019). For example, asserting Indigenous interests casts
a different light on the ve Safe principles. Asking if the use of the data are appropriate, whether
the users can be trusted to use it in an appropriate manner, and if there is a disclosure risk in the
data itself are very different questions when asked from the perspective of Indigenous priorities
and values. Similarly asking whether an access facility can limit unauthorised use or whether the
results are non-disclosive has very different dimensions under an Indigenous data governance
framework. The key question is how to effectively navigate the intersections of Indigenous Data
Sovereignty, Indigenous Data Governance and Open Data to achieve impactful outcomes.
The Research Data Alliance (RDA) International Indigenous Data Sovereignty Interest Group
nominates three steps that the Open Data community and those constructing the Open Data
infrastructure, can take. The rst is the engagement of Indigenous Peoples, not as a group to be
consulted, but as partners and knowledge holders informing the stewardship of data within this
Open Data infrastructure. Second, is the engagement of Indigenous Peoples through capacity
enabled platforms such as the Indigenous Data Sovereignty networks. To be able to participate
meaningfully in Open Data decision making, those at the table need to have data capability.
Third, there needs to be the joint development of principles and protocols around the governance
and stewardship of Indigenous data that are formally applicable to those who currently hold
those data and those who would choose to analyse it (Rainie et al. 2019). None of these steps are
apparent at even the nascent stage in the Australian Open Data infrastructure and Open Data
processes. Rather, advocacy for Indigenous Data Sovereignty principles and Indigenous data gov-
ernance has resulted in interest, little or no implementation. We contend that moving Indigenous
Data Sovereignty principles to an operational form is achievable and offer three options. Each
has different considerations and resource requirements. These are as follows:
1. Incorporation and consideration of Indigenous Data Sovereignty principles into existing data
systems that requires agencies to adopt and implement Indigenous Data Sovereignty princi-
ples and could include an accreditation scheme.
2. Implement Indigenous data governance processes over existing data systems. This requires
the development of an Aboriginal and Torres Strait Islander governance structure, processes,
procedures and resourcing.
3. Development of an Indigenous data infrastructure and authority with Indigenous governance.
©2020 Australian Social Policy Association
All three mechanisms require the creation and management of data infrastructure that is gov-
erned and led by Aboriginal and Torres Strait Islander Peoples. The infrastructure would provide
the opportunity to progress the Indigenous Data Sovereignty agenda through the development
of a data ecosystem that is responsive to Aboriginal and Torres Strait Islander data needs includ-
ing data development while also repatriating Indigenous data to drive community development
and other needs. The structure could be established under existing processes and be enhanced
through the new legislative framework.
The Australian Open Data infrastructure, similar to those in other nation states, is inclusive of
the FAIR scientic data principles (Findable, Accessible, Interoperable, Reusable). These seek to
transform data for machine readability and other secondary use applications within open science
(Wilkinson et al. 2016). Developed in the Netherlands in 2015, FAIR principles have since been
taken up across the Western world as a way of sharing data that will maximise use and re-use.
The rationale is that making data FAIR, will support data and knowledge integration and pro-
mote sharing and re-use of data. FAIR also moves beyond guidance to providing advice and sup-
port of data-related practices that enable capacities to collect, collate and analyse multiple
datasets (ARDC 2020). The FAIR principles do not mention or address the specic concerns of
Indigenous Peoples in relation to Indigenous Data.
In 2018, the RDA International Indigenous Data Sovereignty Interest Group developed the
CARE Principles (Collective benet, Authority to control, Responsibility, Ethics). CARE principles
provide external data stakeholders with guidance and advice on governance practices and steward-
ship responsibilities for Indigenous data (IIDSIG 2019). The purpose in developing the CARE
principles is to complement FAIR principles, not displace them. Thus, Open Data Indigenous data
governance requires enacting FAIR, but with CARE. Implementing the CARE principles speci-
cally address the historical and current power imbalances through the creation of policies and prac-
tices for Indigenous data that are grounded in Indigenous worldviews (reference omitted to
preserve the peer review process). The CARE Principles are expanded in Table 3 below.
Big Data, Open Data and secondary Data Linkage projects raise ethical conundrums. Within
broader ethical frameworks, a particular concern could centre on the lack of general law relating
to privacy in Australia even though Australia is a signatory to the International Convention on
Civil and Political Rights (ICCPR) (Watts & Cassanovas 2018). From this, it is unclear how
Indigenous privacy will be protected under open data policies. Indigenous privacy relates to com-
munal as well as individual privacy. The central concerns of the CARE principles are already pre-
sent a plethora of Indigenous ethical and protocol guidelines that promote overlapping themes
(e.g., Australian Institute of Aboriginal & Torres Strait Islander Studies [AIATSIS] 2012;
National Health & Medical Research Council 2017; Aboriginal Health & Medical Research Coun-
cil of NSW 2020). Yet, Big Data, Open Data and secondary Data Linkage practices, largely dri-
ven by Western scientic epistemologies, actively disempower and silence Indigenous Peoples
(Cormack et al. 2019; reference omitted to preserve the peer review process).
These risks may be somewhat mitigated by the increasing recognition of the critical ethical
importance of Indigenous data governance. In 2019, AIATSIS released their draft AIATSIS Code
of Ethics for Aboriginal and Torres Strait Islander Research (due for release in later 2020). This
document is a signicant departure from the earlier Guidelines for Ethical Research in Australian
©2020 Australian Social Policy Association
Indigenous Studies (GERAIS) in its framework of four overarching principles for Indigenous
research (Indigenous Self-determination,Indigenous Leadership,Impact and Value, and Sustainability and
Accountability). The Code highlights that Indigenous research includes new or pre-existingdata,
stating within the principle of Indigenous leadership that: Ownership management and communi-
cation of research data and results should be negotiated between Indigenous Peoples and the
researcher or other parties based on the principles of Indigenous data sovereignty (AIATSIS 2019:19
italics added).The necessity of Indigenous data governance and the need for Indigenous data to be:
governed and owned by Indigenous Peoples from the very creation of data to its collection, access,
analysis, interpretation, management, dissemination, potential future use and storage(AIATSIS
2019:51) also chart a new ethical approach to data. The Code argues for meaningful collaborative
partnerships from creation, to analysis, to dissemination, to re-use of Indigenous data, clear memo-
randums of understanding, separate data management plan (e.g., returning data to Indigenous com-
munities) and the establishment of ongoing governance committees for larger projects.
The inclusion of Indigenous data rights as an ethical issue in new AIATSIS Code of Ethics
for Aboriginal and Torres Strait Islander Research is an important initiative. Many Indigenous
and First Nations scholars have long argued for the need for all researchers to directly, respect-
fully and (self)reexively engage with varying Indigenous ethics and protocol frameworks (refer-
ence omitted to preserve the peer review process; Kawymullina 2016; McPhail-Bell et al. 2016;
reference omitted to preserve the peer review process; Whetung & Wakeeld 2018). Under cur-
rent Open Data processes, there is an immense danger such critical responsibilities might be
easily sidestepped.
Indigenous data can be a cultural and economic asset, providing invaluable information for
Indigenous groups to set their own goals, make strategic decisions and measure their progress.
But inadequate data, the wrong data or the wrong approach to data are not only a waste of
TABLE 3 CARE principles of Indigenous data governance
CARE principle
C=Collective Benet: C1: Inclusive Development and Innovation
C2: Improved Governance and Citizen Engagement
C3: Equitable Outcomes
A=Authority to Control A1: Recognising Indigenous Rights and Interests
A2: Data for Governance
A3: Governance of Data
R=Responsibility R1: For Positive Relationships
R2: For Expanding Capability and Capacity
R3: For Indigenous Worldviews
E=Ethics E1: For Minimising Harm/Maximising Benet
E2: For Justice
E3: For Future Use
Source: RDA IG (2019).
©2020 Australian Social Policy Association
resources but can have negative scal and human well-being impacts on Indigenous Peoples.
With Aboriginal and Torres Strait Islander People, families and communities, heavily overrepre-
sented in administrative data, there is little doubt that we will also be overrepresented in the
application of these new technologies. Indigenous Data Sovereignty and its implementation mech-
anism Indigenous data governance provide a buttress to the likely negative consequences. But
without the enactment of systems that support Indigenous interests and Indigenous entitlement
to govern the stewardship and application data, the likely result will be just a continuation of the
long history of Indigenous data and policy failure. Australian Open Data processes we are wait-
ing for your action. Platitudes will not sufce.
The authors declare no conict of interest.
We use the term Aboriginal and Torres Strait Islanderto refer specically to Australias Indigenous Peoples. The term
Indigenousis also used both in reference to Australias Indigenous Peoples but also Indigenous peoples more generally through-
out the world. The term First Nationsand communityare also used to describe various and specic collective groups of
Indigenous Peoples. Indeed, the ability to quantify these different collective groups of Indigenous Peoples speaks to the heart of
the need to operationalise Indigenous Data Sovereignty and these terms are used interchangeable throughout this paper.
Aboriginal Health and Medical Research Council of NSW (2020) AH&MRC Ethical Guidelines: Key Principles
pdf. (accessed 25 February 2020)
Andersen, C. (2014) Metis: Race, recognition, and the struggle for Indigenous peoplehood, Vancouver, UBC Press.
Australian Institute of Aboriginal and Torres Strait Islander Studies (2012) Guidelines for ethical research in Aus-
tralian Indigenous studies, Australian Institute of Aboriginal and Torres Strait Islander Studies. https://aiat (accessed 25 February 2020)
Australian Institute of Aboriginal and Torres Strait Islander Studies (2019) 2019 Revision of the aiatsis guidelines
for ethical research in Australian indigenous studies,
pdf. (accessed 25 February 2020)
Australian Research Data Commons (ARDC) (2020) Australian Research Data Commons (ARDC), https://ardc.ed (accessed 25 February 2020)
Battiste, M. and Youngblood, J. (2000) Protecting Indigenous knowledge and heritage: A global challenge. Vancouver:
UBC Press.
Commonwealth of Australia (2019) National Aboriginal and Torres Strait Islander Health Plan 2013-2023 (978-1-
74241-980-0), Canberra,
0486C3BCA257BF0001BAF01/$File/health-plan.pdf. (accessed 25 February 2020)
Cormack, D., Reid, P. and Kukutai, T. (2019) Indigenous data and health: critical approaches to race/ethnicity
and Indigenous data governance,Public health,172, 116118.
Davey, M. (2017) Cashless Welfare Card Treats Aboriginal People as Third-Class Citizens’’, https://www.thegua (ac-
cessed 25 February 2020)
Davis, M. (2015) Closing the gap in indigenous disadvantage: A trajectory of indigenous inequality in Australia,
Georgetown Journal of International Affairs,16, 34.
©2020 Australian Social Policy Association
Davis, M. (2016) Data and the United Nations declaration on the rights of indigenous peoples. In T. Kukutai and
J. Taylor (eds) Indigenous Data Sovereignty, Canberra, ANU Press, pp 2538.
Department of Health, Implementation Plan for the National Aboriginal and Torres Strait Islander Health Plan
20132023, Australian Government, Canberra, 2015 Department of the Prime Minister and Cabinet (PMC)
(2015) Australian Government Public Data Policy Statement,
lic-data/australian-government-public-data-policy-statement. (accessed 25 February 2020)
Department of the Prime Minister and Cabinet(PMC) (2019) New Australian Government Data Sharing and
Release Legislation: issues paper for consultation,
s-paper-data-sharing-release-legislation. (accessed 25 February 2020)
Department of the Prime Minister and Cabinet (PMC) (2019) Best Practice Guide to Applying Data Sharing Prin-
mar-2019.pdf. (accessed 25 February 2020)
Desai, T.,Ritchie, F. and Welpton, R. (2016) Five Safes: designing data access for research. Economics Working
Paper Series1601. University of the West of England.
Dunbar, T. and Scrimgeour, M. (2017) LSIC: Procedural ethics through an Indigenous ethical lens. In M. Walter,
K. L. Martin and G. Bodkin-Andrews (eds) Indigenous Children Growing Up Strong, London, Palgrave Macmil-
lan, pp 6178.
First Nations Information Governance Centre (2014). Ownership, Control, Access and Possession (OCAP
): The
Path to First Nations Information Governance, First Nations Information Governance Centre Ottawa.
Hunt, J. (2013) Engaging with Indigenous Australia-exploring the conditions for effective relationships with Abo-
riginal and Torres Strait Islander communities,
59567/2/01Hunt_Engaging_with_Indigenous_2013.pdf. (accessed 25 February 2020)
Kukutai, T. and Taylor, J. (2016a) Data sovereignty for indigenous peoples: current practice and future needs.In
T. Kukutai and J. Taylor, (eds,) Indigenous Data Sovereignty: Toward an agenda, Canberra, ANU Press, pp 99
Kukutai, T. and Taylor, J. (2016b) Indigenous Data Sovereignty: Toward an Agenda, Canberra, ANU Press.
Kwaymullina, A. (2016) Research, ethics and Indigenous peoples: an Australian Indigenous perspective on three
threshold considerations for respectful engagement,AlterNative: An International Journal of Indigenous Peoples,
12 (4), 437449.
Maiam nayri Wingara (2018) Indigenous Data Sovereignty Communique: Indigenous Data Sovereignty Summit
1533808545167/Communique%2B-%2BIndigenous%2BData%2BSovereignty%2BSummit.pdf. (accessed 25
February 2020)
McPhail-Bell, K., Bond, C., Brough, M. and Fredericks, B. (2016) ‘‘We dont tell people what to do: ethical practice
and Indigenous health promotion,Health Promotion Journal of Australia,26 (3), 195199.
National Health and Medical Research Council (2017) Ethical conducting research with Aboriginal and Torres
Strait Islander Peoples and communities,
h-aboriginal-and-torres-strait-islander-peoples-and-communities.(accessed 25 February 2020)
Ofce of the National Data Commissioner (2020) New Legislation,
sharing/legislation. (accessed 25 February 2020)
Open Data Cube (ODC) (2020) An Open Source Geospatial Data Management & Analysis Platform.
PMC (2018) The Australian Governments response to the Productivity Commission Data Availability and Use Inquiry,
Canberra, Department of the Prime Minister and Cabinet,
access/data-availability-use-government-response.pdf. (accessed 25 February 2020)
Productivity Commission (2017) Data Availability and Use, Canberra,
ted/data-access/issues/data-access-issues.pdf. (accessed 25 February 2020)
Rainie, S.C., Kukutai, K., Walter, M., Figueroa-Rodriguez, O.L., Walker, J. and Axelsson, P. (2019) Issues in Open
Data: Indigenous Data Sovereignty. In T. Davies, S. Walker, M. Rubinstein and F. Perini (eds) The State of
Open Data: Histories and Horizons, Cape Town and Ottawa, African Minds and International Development
Research Centre, pp 300319.
Research Data Alliance (2020) RDA Recommendations and Guidelines on Data Sharing for COVID-19, https:// (accessed 25 February 2020)
©2020 Australian Social Policy Association
Research Data Alliance International Indigenous Data Sovereignty Interest Group (IIDSIG) (September 2019)
CARE Principles for Indigenous Data Governance, The Global Indigenous Data Alliance. https://www.gida- (accessed 25 February 2020)
Scott, J.C. (1998) Seeing Like a State: How Certain Schemes to Improve the Human Condition have Failed, London, Yale
University Press.
Smith, L.T. (2012) Decolonising Methodologies: Research and Indigenous Peoples, London, Zed Books Ltd.
Smith, D.E. (2016) Governing data nd data for governance: the everyday practice of Indigenous Sovereignty.InT.
Kukutai and J. Taylor (eds) Indigenous Data Sovereignty: Toward an agenda, Canberra, ANU Press, pp 117138.
Snipp, C.M. (2016) What does data sovereignty imply: what does it look like. In T. Kukutai and J. Taylor (eds)
Indigenous Data Sovereignty: Toward an agenda, Canberra, ANU Press, pp 3955.
Taylor, J. and Kukutai, T. (2015) Indigenous data sovereignty and indicators. Reections from Australia and Aotearoa
New Zealand. Paper presented at the UNPFII Expert Group Meeting on The Way Forward: Indigenous Peo-
ples and the 2030 Agenda for Sustainable Development.
United Nations (2017) Surveillance, big data and open data top UN experts privacy agenda, https://www.ohchr.
Watts, D. and Cassanovas, P. (2018) Privacy and Data Protection in Australia: a Critical overview (extended
Whetung, M. and Wakeeld, S. (2018) Colonial conventions: Institutionalized research relationships and decolo-
nizing research ethics. In L. T. Smith, E. Tuck and K. W. Yang (eds) Indigenous and Decolonizing Studies in
Education.New York: Routledge, pp 146158.
Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J., Appleton, G., Axton, M., Baak, A., Bourne, P.E. (2016) The
FAIR Guiding Principles for scientic data management and stewardship,Scientic Data,3(1), 19.
Wyatt, K. (2020) Aboriginal and Torres Strait Islander-led data project underway, Media Release 3 July 2020,
Department of the Prime Minister and Cabinet,
Y8mRS2Xxur68j00. (accessed 25 February 2020)
Yap, M. and Yu, E. (2016) Data Sovereignty for the Yawuru in Western Australia. In T. Kukutai and J. Taylor
(eds) Indigenous Data Sovereignty: Toward an agenda, Canberra, ANU Press, pp 223252.
Maggie Walter (Palawa) (PhD, FASSA) is Distinguished Professor of Sociology at the
University of Tasmania, Australia. Publishing extensively in the eld of Indigenous Data,
including Indigenous Statistics (with C. Andersen 2013 Routledge), Maggie is a founding
member of the Maiam nayri Wingara Indigenous Data Sovereignty Collective and the Glo-
bal Indigenous Data Alliance (GIDA).
Raymond Lovett (Ngiyampaa) (PhD) is Associate Professor of Epidemiology at the Aus-
tralian National University, Australia. Ray has published across diverse health and well-be-
ing issues and has a strong focus on Aboriginal and Torres Strait Islander data
sovereignty and governance. Ray is a founding member of the Maiam nayri Wingara
Indigenous Data Sovereignty Collective and the Global Indigenous Data Alliance (GIDA).
Bobby Maher (Yamatji) is a PhD candidate and research associate at the Australian
National University. Bobby is an epidemiologist and has an interest in social epidemiology
and evaluation. Bobby is also a member of the Maiam nayri Wingara Indigenous Data
Sovereignty Collective and the Global Indigenous Data Alliance (GIDA).
Bhiamie Williamson is a Euahlayi man from north-west New South Wales with familial
ties to north-west Queensland. Bhiamie has a Bachelor of Arts (Hons) from ANU and a
Masters of Indigenous Governance at the University of Victoria, British Columbia, Canada.
Bhiamie is a Research Associate at the Centre for Aboriginal Economic Policy Research,
ANU, and a member of the Maiam nayri Wingara Indigenous Data Sovereignty Collective.
©2020 Australian Social Policy Association
Jacob Prehn is a proud Worimi man living on Palawa Country. He is an Indigenous fel-
low and lecturer in Social Work at the University of Tasmania. Jacob is completing a PhD
on the topic of Aboriginal masculinities. His publications comprise quantitative and qualita-
tive data, exploring a range of themes including Aboriginal men, children, families, social
work and the strengths of Indigenous culture on well-being. He is also a qualied Social
Worker, Aboriginal Health Worker and member of the Maiam nayri Wingara Indigenous
Data Sovereignty Collective.
Gawaian Bodkin-Andrews is a Dharawal scholar whose research engages with Indige-
nous Research Methodologies, Indigenous Data Sovereignty, and Indigenous Storywork
and Storytelling frameworks. Through these methodologies, his research seeks to centre
critical Aboriginal Australian standpoints across a diversity of disciplines and topics includ-
ing racism, identity, mental health, education, mentoring and bullying. Gawaian is a found-
ing member of the Maiam nayri Wingara Indigenous Data Sovereignty Collective.
Vanessa Lee (Yupungathi and Meriam) (PhD, SFHEA) is Senior Lecturer who focuses on
the social epidemiology of Aboriginal-Torres Strait Islander people at the University of
Sydney. In 2005, she was awarded a community award for her social impact work. Vanessa
publishes across a diverse platform of health and wellness. Vanessa is a founding member
of the Maiam nayri Wingara Indigenous Data Sovereignty Collective.
How to cite this article: Walter M, Lovett R, Maher B, Williamson B, Prehn J, Bodkin-
Andrews G, Lee V. Indigenous Data Sovereignty in the era of Big Data and Open Data.
Aust J Soc Issues. 2020;00:114. doi: 10.1002/ajs4.141.
©2020 Australian Social Policy Association
... My positionality presents potential risks to the participants of this study, including (but not limited to) misrepresentation and/or exploitation of their knowledges and experiences and risk to participant data sovereignty (Kwaymullina, 2016;L. T. Smith, 2012;Walter, 2016;Walter et al., 2021). Additionally, there is risk to the validity of this work in relation to the interpretation of findings because I am non-Indigenous (Kwaymullina, 2016). ...
... Ahead of the interviews, participants self-selected up to ten individually created and posted documents from their own digital feeds which they then used to lead the discussion while we explored their interpretation of their posts. Through this, and through using digital documents that participants have created themselves, they were able to define their own reality and produce their own data, albeit shaped by the project brief and interview guide (Walter et al., 2021). This method made the interpretive process increasingly equal and ensured that participants could exercise their own expertise and agency (Barton, 2015;Pain, 2012), and have a pro-active role in the research processes (Edmondson et al., 2018). ...
... Through elicitation techniques the expertise and agency of participants is valued and privileged (Grant, 2019). Elicitation techniques enable Indigenous data sovereignty to a greater degree than standard qualitative techniques because they encourage participants to exercise their own control in data analysis and narration (Pain, 2012;Walter, 2016;Walter et al., 2021). Further, they increase the likelihood of responses being grounded in own experiences and knowledges, recognise and privilege participants experiences as a valid basis of knowledge and can reduce power imbalances between researcher and participant making research processes more collaborative (Barton, 2015;Grant, 2019;Sunseri, 2007). ...
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Aboriginal and Torres Strait Islander gender and sexuality diverse peoples are harnessing digital spaces to transcend territorially defined place-based communities of the past, and create new, informal, digital identity communities. These communities are composed of relatively homogenous subjectivities and are centred on shared identities, histories, experiences, practices and resistances. Drawing from in-depth qualitative interviews with Aboriginal Queer women who are content creators and the theory of the Cultural Interface, this article explores how participants cultivate identity communities and kin through TikTok, Instagram and Spotify. Additionally, it exposes the significance of Indigenous Queer digital communities and chosen families to participants experiences of Social and Emotional Wellbeing. Through their digital cultures of care and kin-making participants reveal how Social and Emotional Wellbeing is relationally practiced online and how they harness media technologies to continue and augment existing Indigenous practices and Queer approaches to family that thrive and survive on reciprocity, responsibility and love. In doing so, participants demonstrate how they embody oppositional intimacies, kinship groups and Indigenous LGBTIQ+ identities which transgress and challenge settler norms of intimacy, family, identity, gender and sexuality.
... Consistent with bestpractice guidelines for linked data (Australian Institute of Health & Welfare, 2012), Indigenous status was assigned if an individual had ever self-identified or been labelled within a system as Indigenous (Aboriginal and/or Torres Strait Islander) in any of the QCRC databases. We recognise the problems inherent in using the overarching term of Indigenous status, since it obscures the diversity of the more than 500 Aboriginal and Torres Strait Islander nations in Australia (Walter et al., 2020). However, the use of this overarching term is unavoidable in our analyses, as the QCRC datasets do not provide further detail on Indigenous identity. ...
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Mental illness is firmly established as a risk factor for criminal legal system contact, particularly for women and Indigenous people. While patterns of criminal legal contact vary by gender and Indigenous status, we do not know how mental health contacts factor into these patterns. The aim of this research is to examine whether mental health characteristics and service contacts vary across patterns of criminal legal system contact defined by group-based trajectory modelling and to explore whether any such variation is consistent across gender and Indigenous status. Using linked administrative data from a 1990 Australian birth cohort (to age 23/24 years, N = 45,141), we estimate trajectories of criminal legal system contact and assess variation across groups defined by gender and Indigenous status. We then examine whether types of mental illness diagnoses and mental health service contacts varied across trajectory groups and whether this was consistent across gender and Indigenous status. Findings point to important differences in mental health system contact across offending trajectory groups. Differences are suggestive of variation in mental health system utilization at the intersection of gender and Indigenous statuses that are conditioned by patterns of criminal legal system contact. We conclude by outlining the implications of these patterns for life course theories of offending and for gender and culturally informed support and interventions directed towards system-involved individuals with mental health needs.
... Indigenous data sovereignty: is ". . . in its proclamation . . . the right of Indigenous Peoples to govern the collection, ownership, and application of data, [and] recognises data as a cultural and economic asset" [83]. ...
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Indigenous Peoples around the globe make up approximately six percent of the global population , yet they sustainably care for around eighty percent of the world's remaining biodiversity. Despite continued political, economic, and racial marginalization, as well as some of the worst health inequities on the planet, Indigenous Peoples have worked hard to maintain their cultures and languages against all odds. Indigenous Peoples' close connections to land, water, and ecosystems, however, have placed them at increasing vulnerability from the effects of climate change. With this, the health risks from climate change have unique considerations within Indigenous Nations for both mitigation and adaptation responses that are largely unappreciated. This Indigenous narrative review will synthesis the current climate and health landscape of Indigenous Peoples at a global, high-level scale, including relevant international mechanisms and considerations for Indigenous Peoples' health. This Indigenous narrative review will also explore and reflect on the strengths of Indigenous traditional knowledges as it pertains to climate change and health.
... As a result, indigenous communities have become increasingly distrustful of external researchers and institutions that collect and use their data (Figueiredo et al., 2020). The field of indigenous data sovereignty has emerged in response to these issues Walter et al., 2021). This field recognises that indigenous communities have the right to own, control and govern their data. ...
This chapter introduces a framework for indigenous research and data management in electronic archives that aligns with indigenous worldviews and practices. It discusses indigenous communities' challenges in owning and controlling their data and the need for a culturally relevant framework for managing indigenous data in electronic archives. The proposed eight-step framework emphasises community control , data sovereignty, and ethical data management practices; and includes key components such as community engagement, informed consent, and culturally relevant metadata standards. Best practices for data sharing and partnership building with non-indigenous institutions are also discussed, as well as the steps for implementing the framework and the role of stakeholders in the process. Evaluation metrics for measuring the framework's success are proposed. The chapter concludes by emphasising the importance of community control and ethical data management practices in preserving and protecting indigenous cultural heritage and identity in electronic archives.
... enabling risk assessment (Gillingham, P., 2016;Grządzielewska, 2021), increased quality and impact e.g. of services (Kum, Joy Stewart, Rose, & Duncan, 2015;Pan et al., 2017;Santiago & Smith, 2019), transparency and user orientation (Bako et al., 2021;Cresswell et al., 2020). On the other hand, it is important to consider its limitations, which are just as diverse: Dehumanization (Devlieghere, Gillingham, P., & Roose, 2022;Fink, 2018), data safety and security (Keen et al., 2021;Ranerup & Henriksen, 2022), data and algorithmic Injustice (Eubanks, 2018;Walter et al., 2021;Whelan, 2020) and as result inequalities (Eubanks, 2018) or misperception and bias (Cresswell et al., 2020;James & Whelan, 2021;Landau, A. Y. et al., 2022). These limitations are particular relevant to the human service context as human services professions are based on strong ethical and moral foundations (Rodriguez, DePanfilis, & Lanier, 2019;Schneider & Seelmeyer, 2019) work with often overlooked and marginalized, stigmatized, and discriminated groups and with very sensitive and complex psychological and emotional issues. ...
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CfP Special Issue „AI in Human Services“ I Journal of Technology in Human Services Abstract submission: September 1, 2023 Together with various colleagues from research and practice, we are guest editors for a special issue on "AI in human services" (e.g. social work) in the Journal of Technology in Human Services. The vision of the special issue is to take a closer look at different application areas, the possibilities/limits or levels (micro/individual, meso and macro) of artificial intelligence in human service organisations. We also want to create a research community in this context. More possible research questions can be found in the CfP. #AI #ArtificialIntelligence #SocialWork #HumanService #BigData #Automation #SocialBusiness
... Secondly, the high-speed feature means that massive data can be created or moved quickly. The internet has the characteristics of timeliness, real-time, and cross-time, which provide a good transmission medium for data [15]. BD relies on the internet as the transmission hub to achieve high-speed efficiency. ...
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With the emergence of Artificial Intelligence technology and the advancement of science and technology, the current mainstream path of social development is continuously updating and improving various industries using technology. Therefore, in order to promote the development of sneaker consumer culture, this study explores the use of technological means to improve the dissemination effect of symbolic culture in sneaker consumer culture. Firstly, the development concept and mainstream direction of sneaker consumer culture in the era of big data are discussed, and the application principle of big data technology is introduced. Then, a sneaker culture dissemination model based on big data technology is designed. Finally, the model is optimized using a Convolutional Neural Network (CNN), and its effectiveness is evaluated. The results show that the Convolutional Neural Network-Big Data (CNN-BD) model designed in this study has the highest fitting degree of 93% and a lowest fitting degree of 78% in the UT-Zap50K dataset. In the Ai2 dataset, the highest fitting degree of the big data classification model is 94%, and the lowest is 76%. In the Kaggle Women's Shoe dataset, the highest fitting degree of the big data classification model is 92%, and the lowest is 77%. In the Kaggle Men's Shoe dataset, the highest fitting degree of the big data classification model is 94%, and the lowest is 79%. The designed model has the highest accuracy rate of 93% in sneaker classification, while other models have the highest accuracy rate of around 82% in sneaker classification. Compared with traditional big data technology, the designed model has greatly improved and can adapt to more working environments. This study not only provides technical support for the application of big data technology but also contributes to improving the dissemination effect and promoting the comprehensive development of sneaker consumer culture.
Through digital transformation, lots of personal data are captured, but individuals often do not have ownership or control over them. This results in the emerging Web 3.0, where people demand for data sovereignty. There are actually two conceptually related terms, data sovereignty and digital sovereignty. This paper first explains these two concepts in terms of their points of focus, guiding principles, laws and regulations requirements, and then analyses the requirements and technical challenges of their implementation. To understand the emerging trend shift in digital sovereignty towards individuals taking control of security and privacy preserving over their own digital assets, this paper conducts a systematic review and analysis on Self-Sovereign Identity (SSI), which is a user-centric decentralized model and autonomy for an individual to self-determine the access and use of one's identity and credentials. The review covers existing SSI solutions and points out that an efficient key management system, the scalability and interoperability of the solution, and a well-established standard are some of the challenges for SSI deployment. Finally, the paper concludes with open issues about digital identity, including dynamic attributes, persona, and attribute ownership, that challenge the current reference architecture of SSI as well as its implementation.
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Introduction: Globally, primary care organisations responded rapidly to COVID-19 physical distancing requirements through the adoption of telehealth to maintain the delivery of health care to communities. In Australia, temporary Medicare Benefits Schedule (MBS) telehealth items were introduced in March 2020 to enable the provision of telehealth services in the primary care setting. These changes included funding for two modes of telehealth delivery: videoconferencing and telephone consultations. As primary care organisations, Aboriginal Community Controlled Health Organisations (ACCHOs) rapidly adopted telehealth consultations to maintain the delivery of primary care services to Aboriginal and Torres Strait Islander clients. The aim of the present study was to evaluate the implementation (specifically the uptake, acceptability and requirements for delivery) of telehealth primary healthcare services for Aboriginal and/or Torres Strait Islander peoples by a rural ACCHO during COVID-19. Methods: A single-site convergent-parallel mixed-methods study was undertaken in the context of an ongoing research partnership established between a rural ACCHO and a university department of rural health. De-identified health service data from March 2020 to March 2021 was extracted, including MBS telehealth consultations and client demographics (eg age, gender and postcode). Variables were analysed using descriptive statistics to examine the uptake of telehealth by Aboriginal and Torres Strait Islander clients. A geographical analysis of postcode data was also undertaken. Semi-structured interviews were undertaken concurrently with a purposive sample of health service personnel (including health professionals) involved in the implementation or delivery of telehealth, and Aboriginal and/or Torres Strait Islander clients who had accessed telehealth, to explore the acceptability of telehealth and requirements for delivery. Thematic analysis using an inductive approach was undertaken. The analyses of quantitative and qualitative findings were merged to identify key concepts pertaining to the uptake, acceptability and requirements for telehealth delivery. Results: During the first year of implementation, 435 telehealth primary healthcare consultations were delivered to Aboriginal and/or Torres Strait Islander clients. Seven health personnel and six Aboriginal and/or Torres Strait Islander clients participated in interviews. Merged findings from an analysis of quantitative and qualitative data were grouped under three concepts: uptake of telehealth consultations by Aboriginal and Torres Strait Islander clients, maintaining the delivery of ACCHO services during COVID-19, and implications for sustaining telehealth in an ACCHO. Findings identified that telehealth maintained the delivery of ACCHO services to Aboriginal and/or Torres Strait Islander clients across the lifespan during COVID-19, despite a preference for face-to-face consultations. A greater uptake of telephone consultations compared to videoconferencing was identified. Barriers to the utilisation of videoconferencing were largely technology related, highlighting the need for additional support for clients. Conclusion: Telehealth was a useful addition to face-to-face consultations when used in the appropriate context such as the administration of long-term medication prescriptions by a GP. Engaging the ACCHO sector in the policy discourse around telehealth is imperative for identifying requirements for ongoing implementation.
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Indigenous population represent about 6% (up to 7.4 million) of the total population in Mexico. It is integrated by more than 60 different ethnic groups distributed throughout the country but with mayor presence in the southern states on Oaxaca, Chiapas and Guerrero as well as the Yucatan Peninsula states. There is a clear relation between indigenous population distribution and marginalization: the most marginalized municipalities are those where indigenous communities are settled. It is widely documented that indigenous communities are among the population with the poorest living standards and most disadvantages regarding education, health and income opportunities. For instance, according to the Interamerican Development Bank there is a significant gap between indigenous and non-indigenous population regarding access to their right to education, particularly for indigenous women which present the lowest levels of education and the highest illiteracy. State efforts in relation to public policy have not been effective to provide indigenous communities with better opportunities, mainly because there is a huge gap between policy makers and indigenous communities in terms of the understanding of perspectives and priorities. Indigenous communities participation regarding public policies should be enhanced whilst promoting their sovereignty and governance. Data sovereignty stands as a relevant element towards regaining governance and promoting proper participation of indigenous communities in the establishment and defense of their priorities and perspectives in relation to their resources. This chapter will address these issues for the case of Mexico.
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Key points ■■ Indigenous Data Sovereignty (IDS) has emerged as an important topic over the last three years, raising fundamental questions about assumptions of ownership, representation, and control in open data communities. ■■ IDS refers to the right of Indigenous peoples to control data from and about their communities and lands, articulating both individual and collective rights to data access and to privacy. ■■ Ideas from IDS provide a challenge to dominant discourses in open data, questioning current approaches to data ownership, licensing, and use in ways that resonate beyond Indigenous contexts, drawing attention to the power and post-colonial dynamics within many data agendas. ■■ Growing IDS networks are working to shape open data principles to better respect the rights of Indigenous peoples.
Background Despite evidence that 1 of every 3 American Indian / Alaska Native (AI/AN) elders will develop dementia, they remain substantially underrepresented in Alzheimer’s disease and related dementias (ADRD) research. In our partnership with the Oneida Nation of Wisconsin, scientists from the Wisconsin Alzheimer’s Disease Research Center (ADRC) find ourselves at the intersection of two influential and opposing movements: 1) a movement to ensure Tribal data sovereignty, driven by abuse stemming from unrestricted access to AI/AN data and samples; and 2) researchers' push toward free and unfettered access to big datasets, including genetic data. National ADRD datasets include information from AI/AN participants for whom Tribal affiliation is unknown and there is little to no guidance on how to conduct research with datasets where AI/AN race is identified but Tribal affiliation is unknown . We see a need to establish guidelines for researchers utilizing ADRD big datasets and repositories containing data and samples from AI/AN of unknown Tribal affiliation. Method We have contacted stakeholders of ADRD research using AI/AN data of unknown Tribal affiliation, including the National Institute of Aging (NIA) Alzheimer’s Disease Research Centers Program, the NIA Office of Special Populations, the National Alzheimer’s Coordinations Center, the National Centralized Repository for Alzheimer’s Disease and Related Dementias, the National Institute of Health Tribal Health Research Office, and AI/AN scientists who are stakeholders in the use of AI/AN data. Future efforts will involve Alzheimer’s Disease genetic, biomarker sample, and data repositories, and AI/AN elders, youth, and Tribal members. Result We plan to develop a process through which proposed analyses that include AI/ANN data will be culturally informed and reviewed by AI/AN scientist ‐ e.g., an AI/AN Advisory Committee. This would ensure that proposals to use AI/AN data and samples from ADRD big datasets and repositories do not inflict further harm to this historically marginalized group. Moreover, the review would ensure that data sovereignty measures are addressed prior to analysis and publication. Conclusion We propose to convene an AI/AN Advisory Committee to guide ADRD researchers on culturally responsible management of data, samples, and genetic information collected from AI/AN participants, their Tribes, and their Nations.
'Race'/ethnicity data have become increasingly institutionalised within research on Indigenous health. While these data are important to monitoring the differential distribution of health risks and benefits in racialised societies, their uncritical and undertheorised use can perpetuate harmful biologically deterministic and essentialist approaches to Indigenous health. In addition, narratives of Indigenous health are often still shaped by colonial logics, with Indigenous data rights, priorities and governance overlooked or ignored. Researchers need to critique the use of 'race'/ethnicity concepts and data in Indigenous health research. This requires an explicit shift away from describing 'race'/ethnicity as 'risk factors' to examining processes by which 'race'/ethnicity become meaningful in relation to health outcomes for Indigenous communities. In addition, researchers need to consider how Indigenous rights to health data are recognised, including the application of frameworks or principles of Indigenous data sovereignty.
An increasing number of Australian universities are committing to Indigenous Graduate Attributes across a wide range of academic disciplines. This paper critiques not only the slow up-take of Indigenous Graduate Attributes in the last 10 years, but also how such attributes may realistically contribute to university students graduating with increased ‘awareness’, ‘knowledges’ and ‘abilities’ to work with Aboriginal and Torres Strait Islander peoples and communities. It is reasoned that any commitment to Indigenous Graduate Attributes must be carefully and critically monitored for the silencing effects of colonial narratives that also are prevalent throughout Australian Indigenous Studies (which is arguably the foundation of realising Indigenous Graduate Attributes). Drawing from a diversity of Indigenous standpoint theories, critical studies and research methodologies, the paper offers a critical evaluative framework through which both Indigenous Graduate Attributes and the content within the teaching and learning of Australian Indigenous Studies may be evaluated. This includes an acute awareness of imposed colonial narratives, a critical awareness of one’s own positioning, engagement with Indigenous voices, knowledge of Indigenous Research Methodologies, and more meaningful levels of Indigenous engagement through Indigenous ethics and protocols.
The field of Indigenous methodologies has grown strongly since Tuhiwai Smith’s 1999 groundbreaking book Decolonizing Indigenous Methodologies. For the most part however, there has been a marked absence of quantitative methodologies with the methods aligned with Indigenous methodologies predominantly qualitative. This article proposes that the absence of an Indigenous presence from Indigenous data production has resulted in an overwhelming statistical narrative of deficit for dispossessed Indigenous peoples around the globe. Using the theoretical concept of Indigenous Lifeworlds this article builds on the core premises of Walter and Andersen’s 2013 book Indigenous quantitative methodologies. Arguing for a fundamental disturbance of the Western logics of statistical data the article details recent developments in the field including the emergence of the Indigenous Data Sovereignty movement. The article also explores Indigenous quantitative methodologies in practice using the case study of a Tribal Epidemiology Centre in New Mexico.
Statistics about Indigenous peoples are a common feature of Anglo-colonizing nation states such as Canada, Australia, Aotearoa New Zealand, and the United States (CANZUS). The impetus for the production of most Indigenous statistics is the shared position of Indigenous disadvantage in health and socioeconomic status. In this chapter, we contrast statistics about Indigenous peoples with statistics for Indigenous people and statistics by Indigenous people. There are very significant differences between these categories of Indigenous statistics. At the heart of these differences is the methodology that informs the research processes and practices. Statistics about Indigenous peoples often reflect the dominant social norms, values, and racial hierarchy of the society in which they are created. In the CANZUS states, these statistics are deficit focused and, at times, victim blaming. Also missing from these statistical portrayals is the culture, interests, perspectives, and alternative narratives of the Indigenous peoples that they purport to represent. We contrast these statistics with those from statistical research using processes and practices that are shaped by Indigenous methodologies. Indigenous methodologies are distinguished by their prioritization of Indigenous methods, protocols, values, and epistemologies. We conclude with two examples of what Indigenous quantitative methodologies look like in practice from Aotearoa NZ and Australia.