10 guidelines for ethical data research

Researchers identified 10 important rules to ethically conduct large-scale data research in a recent editorial for PLOS Computational Biology.

An interdisciplinary group of researchers developed the guidelines as part of a two-year project funded by the National Science Foundation.

The editorial — led by Matthew Zook, PhD, a geography researcher at University of Kentucky in Lexington — reflects the researchers' belief that those using big data have an ethical responsibility to minimize harm and public mistrust, since it engages with human subjects.

Here are the 10 rules.

1. Acknowledge that data are people and can do harm

2. Recognize that privacy is more than a binary value

3. Guard against the reidentification of your data

4. Practice ethical data sharing

5. Consider the strengths and limitations of your data; big does not automatically mean better

6. Debate the tough, ethical choices

7. Develop a code of conduct for your organization, research community or industry

8. Design your data and systems for auditability

9. Engage with the broader consequences of data and analysis practices

10. Know when to break these rules

"In short, responsible big data research is not about preventing research, but making sure that the work is sound, accurate and maximizes the good while minimizing harm," the authors conclude. "Fantastic opportunities to better understand society and our world exist, but with these opportunities also come the responsibility to consider the ethics of our choices in the everyday practices and actions of our research."

Click here to view the full article.

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