Table 4 Framework for data ethics for data literacy (built on Atenas, Havemann, Timmermann & Kuhn, 2021)

Respect autonomy

This aims at enabling people, primarily as individuals, to make informed decisions about the potential uses of their data, through the concept of informed consent and transparency. In this case, informed consent needs to go beyond data collections, but clearly describe how and by whom data will be used and how the results will be published

Al-Nuaimi (2020), Buckingham and Crick (2016), Powell (2018), Wheeler (2018), Sloane (2019), Kumar et al (2020), Véliz (2019)

Data feminism

CARE Principles for Indigenous Data Governance

Global Data Ethics Pledge

General standards for data governance

Federal Data Strategy

Data Ethics Framework

Data Ethics Principles

Good Practice Principles for Data Ethics in the Public Sector

Universal principles of data ethics

Our Principles (SAS)

Respect privacy

To consider that some issues should not be part of the public sphere or a matter of public concern, people have a right to withhold such type of data unless there is a commonly agreed overriding reason for publicity (e.g. additional income by politicians)

Richards and King (2014), Yao-Huai (2005)., Pollach (2005), Schwartz (2011), Herschel and Miori (2017), Zimmer (2010), Lundberg et al. (2019), Stahl and Wright (2018), Véliz (2020)

Global Data Ethics Pledge

Australia’s AI Ethics Principles

General standards for data governance

Federal Data Strategy

Universal principles

of data ethics

Our Principles (SAS)

Promote fairness

This asks to treat like cases alike, and recognises that we may have to make special arrangements so that no one ends up undeservingly disadvantaged

Researchers must assess and decide whether those being directly or indirectly involved or affected in or by the research will be endangered, exposed, put at risk, unjustly treated, profiled or classified in a derogatory manner regardless of the interests or intentions of the researchers

Jo and Gebru (2020), Stoyanovich et al. (2018), Hoffmann et al. (2018), Richterich (2018), Ienca et al. (2018), Hand (2018), Bertino et al. (2019), Jobin et al. (2019), Johnson (2014)

Data feminism

CARE Principles for Indigenous Data Governance

Global Data Ethics Pledge

Australia’s AI Ethics Principles

Data Ethics Framework

Address equality

This means that rules should apply to all unless there is a publicly acceptable reason for exemption. It refers to the legal concept of equality, which means that every person has the same rights and should be treated in the same way regardless of their personal characteristics

Tusinski Berg (2018), Bogroff and Guegan(2019), Bezuidenhout et al. (2020), Kazim and Koshiyama (2019), Puaschunder (2019), Corple and Linabary (2020), Johnson (2014)

Data Ethics Principles

CARE Principles for Indigenous Data Governance

As compliance and accountability for all:

Data Ethics Principles

General standards for data governance

An Ethics Framework for the Data and Intelligence Network

Good Practice Principles for Data Ethics in the Public Sector

Data ethics framework

Universal principles of data ethics

Australia’s AI Ethics Principles

Our Principles (SAS)

Do no harm

This is often also labelled as non-maleficence, and refers to preventing data uses with negative consequence, for instance, by directly exposing or allowing the identification of individuals and groups

Raymond (2017), Kitto and Knight (2019), Loukides, Mason & Patil (2018), Berman and Albright (2017), Taylor et al. (2016)

CARE Principles for Indigenous Data Governance

Global Data Ethics Pledge

General standards for data governance

Data Ethics Framework

Universal principles of data ethics

Australia’s AI Ethics Principles

Our Principles (SAS)

Promote sovereignty

This means that subjects, both at individual and collective level, should be in a position to decide when and what data they wish to disclose and to whom, and that a refusal to share data, should not impede or obstruct their access to key information or to participate in political, cultural, scientific and economic life, and to welfare, education and health services. It also recognizes that affected people are the best advocates for promoting their own interests without misrepresentation

Kukutai and Taylor (2016), Walter and Suina (2019), Kukutai et al. (2020), Snipp (2016), Lovett et al. (2019), Ai-min and Jia (2015), Hummel et al. (2018)

CARE Principles for Indigenous Data Governance

Address bias

Epistemic structures influence the way we think about certain people and objects, sometimes giving them undeserved advantages or disadvantages

It refers to avoid portraying individuals or groups through prejudiced or predetermined ideas to influence decisions in a certain direction. Many claim that we all have biases, and that there are in a certain degree unavoidable, so we need to take action

Richterich (2018), Henderson (2019), Herschel and Miori (2017), Ienca et al. (2018), Mittelstadt et al. (2016), Buenadicha et al. (2019)

McDonald and Pan (2020)

Data feminism

Global Data Ethics Pledge

General standards for data governance

An Ethics Framework for the Data and Intelligence Network

Challenge power structures

Support individuals to confront and challenge existing power structures that exist to limit who can decide, and for how long their decision stands, and who can be forced to comply with those decisions within society, government and communities

Taylor (2016), Heeks and Shekhar (2019), Atenas et al. (2020), Dencik et al. (2016)

Dencik and Sanchez-Monedero (2022)

Goldkind et al. (2021)

Data feminism

CARE Principles for Indigenous Data Governance

As balancing power:

General standards for data governance