Data ethics is both the study and creation of theories and their application to data practices (government, education, industry, etc.) that addresses the collecting, generating, analyzing, and disseminating of data, and the resulting impacts. It includes addressing and recommending concepts of right and wrong conduct, with transparency in and defensibility of actions and decisions driven by automated/artificial intelligence (AI) in relation to data in general and personal data in particular.
Computing professionals' actions change the world. To act responsibly, they should reflect upon the wider impacts of their work, consistently supporting the public good. The ACM Code of Ethics and Professional Conduct ("the Code") expresses the conscience of the profession.
Department of Health and Human Services. Site includes educational resources on responsible conduct of research, U.S. legislation, guidelines governing federally funded research, and reports and news summaries of national and international misconduct.
maintained by the National Academy of Engineering, the Center includes a library of cases, online modules, and quality introductory articles on ethics in engineering and the sciences.
The Guide to Social Science Data Preparation and Archiving is aimed at those engaged in the cycle of research, from applying for a research grant, through the data collection phase, and ultimately to preparation of the data for deposit in a public archive. The Guide is a compilation of best practices gleaned from the experience of many archivists and investigators.
Sponsered by the U.S. Department of Health and Human Services, Office of Research Integrity, this guide covers data ownership, collection, storage, protection, and sharing.
Intellectual Property and Copyright
In general raw data on their own are considered facts and thus can not be copyrighted. However, data that are gathered together in a unique and original way, such as databases, can be copyrighted or licensed. It is important to understand data licensing from the perspective of both the data user and data creator.
When re-using existing data be sure to clarify ownership, obtain permissions if needed, and understand limits set by licenses. Be sure to provide appropriate attribution and citation. If licensing restricts sharing of the data, providing detailed information about where the data were obtained and how the data were analyzed can help with reproducibility.
There is increased pressure from funders and journals for researchers to release their research data. Applying appropriate licensing when data are released will help ensure proper re-use and attribution. There are many licenses available that represent the range of rights for the creator and licensee of the data. Two options for providing open licenses for research data are:
Creative Commons License - https://creativecommons.org/licenses/
Open Data Commons License - http://opendatacommons.org/licenses/