Data Ethics

The Data Ethics Framework was created to give guidance to federal workers as they acquire and work with data, but the advice can be applied to non-governmental data work.  These seven tenets were published in the framework:

1. Uphold applicable statutes, regulations, professional practices, and ethical standards. Existing laws reflect and reinforce ethics. Therefore, data leaders and data users should adhere to all applicable legal authorities. Legal authorities often address historic situations and issues and may not keep pace with the evolving world of data and technology. Organizational leaders are encouraged to maintain up-to-date, comprehensive ethical standards regarding data use and staff are responsible for learning and applying agency guidance appropriately.
2. Respect the public, individuals, and communities. Data activities have the overarching goal of benefiting the public good. Responsible use of data begins with careful consideration of its potential impacts. Data initiatives should include considerations for unique community and local contexts and have an identified and clear benefit to society.
3. Respect privacy and confidentiality. Privacy and confidentiality should always be protected in a manner that respects the dignity, rights, and freedom of data subjects. In this context, privacy is the state of being free from unwarranted intrusion into the private life of individuals, and confidentiality is the state of one’s information being free from inappropriate access and misuse. An essential objective of privacy and confidentiality protection is to minimize potential negative consequences through measures such as comprehensive risk assessments, disclosure avoidance, and upholding data governance standards. Data activities involving individual privacy should align with the Fair Information Practice Principles (FIPPs).
4. Act with honesty, integrity, and humility. All federal leaders and data users are expected to exhibit honesty and integrity in their work with data, regardless of job title, role, or data responsibilities. Federal leaders and data users should not perform or condone unethical data behaviors. When sharing data and findings, personnel should report information accurately and present any data limitations, known biases, and methods of analysis that apply. It should also be recognized that no dataset can fully represent all facets of a person, community, or issue. Federal leaders and data users are expected to have humility when presenting data, be open to feedback, and when possible invite discussion with the public. In addition, federal data users should accurately represent their abilities when working with data.
5. Hold oneself and others accountable. Accountability requires that anyone acquiring, managing, or using data be aware of stakeholders and be responsible to them, as appropriate. Remaining accountable includes the responsible handling of classified and controlled information, upholding data use agreements made with data providers, minimizing data collection, informing individuals and organizations of the potential uses of their data, and allowing for public access, amendment, and contestability to data and findings, where appropriate.
6. Promote transparency. Individuals, organizations, and communities benefit when the ethical decision-making process is as transparent as possible to stakeholders. Transparency depends on clear communication of all aspects of data activities and appropriate engagement with data stakeholders. Promoting transparency requires engaging stakeholders through easily accessible feedback channels and providing timely updates on the progress and outcomes of data use.
7. Stay informed of developments in the fields of data management and data science. Advanced technologies provide great benefit to the public sector, but should be deployed with a commitment to accountability and risk mitigation. While traditional data use and analysis can introduce bias, emerging systems, technologies, and techniques require additional awareness and oversight because they can increase opportunities for bias. It is critical to remain informed of developments in the fields of data management and data science, especially as advanced methods impact future data collection, management, and use. In addition, new data innovations (e.g., systems, solutions, computational methods) emerge every day, increasing the importance for federal leaders and employees working with data to keep abreast of market innovations and learn how to ethically use new methods.

In U.S. law, intellectual works (books, recordings, images, etc.) are the property of their creators. These creators own the exclusive rights to copy and distribute their work from the moment the work is created. They may sue others who copy or distribute their work without permission. You can find the text of the law on the U.S. Copyright Office web site.

As decided in Feist Publications, Inc., v. Rural Telephone Service Co., data are not covered under copyright law. If you publish data you have collected, you would own the copyright to any text and visualizations that describe or organize that data, but others would be able to reorganize the data and illustrate it in different ways without infringing on your copyright.

Be aware: If you publish someone else's data, you may still be sued if the original publisher feels your work is too close to their own copyrighted work.