JUST Data Principles

JUST Data Principles

In partnership with Industry Commons Foundation


Data annotation through the lens of JUST principles—Judicious, Unbiased, Safe, and Transparent—intends to foster ethical practices among data researchers, owners, and managers, as well as to moderate the automated and autonomous behaviours of AI systems. This process involves tagging datasets using a simple metadata input interface that guides the development of equitable systems and embeds ethical considerations into the core of data handling practices.

By annotating data with an awareness of potential biases and ethical implications, we aim to cultivate a culture of responsibility and transparency within research, industry and the data science community, ensuring that data practices contribute positively to society.



The JUST Data initiative is founded on principles designed to enhance the FAIR data guidelines (Findable, Accessible, Interoperable and Reusable) by integrating ethical considerations, focusing on creating JUST data practices that aim to be Judicious, Unbiased, Safe, and Transparent.

  • Judicious: Emphasising the careful and informed use of data, considering the implications of its application in various contexts, ensuring decisions and actions are grounded in a deep and thoughtful understanding of that data’s limitations and potentials.
  • Unbiased: Striving to identify and mitigate biases within data sets. Acknowledging that while absolute neutrality is simply not achievable (there is no such thing as an “unbiased data set”), steps can be taken to minimise the impact of bias, particularly concerning gender, ethnicity and other social categories.
  • Safe: Ensuring that the usage of data upholds privacy and security standards, protecting sensitive information from misuse and respecting the rights and dignity of individuals and communities represented in the data.
  • Transparent: Advocating for openness about the data’s origins, methodology, and applications. Transparency is key to building trust, facilitating scrutiny, and enabling the replication of research findings.

Together, these principles guide the JUST Data initiative’s efforts to make data practices more ethical and inclusive, supporting the development of industrial, research and AI systems that are fair, equitable, and beneficial for all sectors of society.


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