Basics

Research Ethics

Working with research data is a responsible task. This is particularly true for social, behavioral, educational, and economic sciences, where people are often the subject of research and thus sensitive, personal data form the core of research. In this context, various ethical principles can come into conflict, where the goal of openness and transparency in the research process may contradict the protection of research subjects. Institutions and professional societies have therefore developed guidelines to safeguard good scientific practice, which include ethical principles. Legal requirements, such as data protection or copyright laws, also serve to regulate the handling of research data at EU, national, or regional level.

Adhering good research data management practices can help you consider important ethical and legal aspects throughout all phases of the data curation lifecycle, from planning to archiving and reuse stage.

This article provides an overview of the key ethical topics of data management. The content related to legal aspects is associated with each individual process step.

Good scientific practice

Ethical considerations are relevant throughout the whole data curation lifecycle, including data collection and processing, storage and deletion of data, archiving, and reuse phases. Misuse and unethical use of data can occur at any stage of the data curation lifecycle. Some examples of the unethical use and data misuse are the following:

• Collecting personal data without informed consent from the individuals being surveyed
• Storing personal data without adequate protection and security measures (e.g., making them accessible to unauthorized individuals)
• Publishing data that violates the privacy of the survey participants (e.g., not anonymized)
• Reusing data published by other researchers under a CC-BY 4.0 license without attributing the names of the authors.

Therefore, it is important to incorporate research ethics considerations into the research proposal and when writing a Data Management Plan (DMP). This helps prevent data misuse and unethical use of data and promotes responsible handling of research data.

To counteract the misuse of research data and establish ethical research principles, organizations such as the DFG (German Research Foundation) have formulated principles of good scientific practice:

The consideration of ethical issues is particularly important for the social, educational, and behavioral sciences, as disciplines which often work with sensitive personal data. In addition to the ethical conduct of researchers within the scientific community, the protection of research subjects (the ‘researched individuals’) is vital.

Ethical and legal principles towards the researched individuals:

• Voluntariness of participation as a prerequisite for a study
• The principle of informed consent
• Protection of participants by ensuring anonymity
• Risk avoidance
• Safeguarding personality rights (of third parties)

Ethical and legal principles towards the scientific community and fellow researchers:

• Safeguarding the right to one’s own work (cf. copyright)
• Identifying one’s own and others preliminary work and proper citation of third parties
• Recognizing and avoiding scientific misconduct, e.g. data fabrication

What are particularly sensitive data?

An important aspect of good research data management (RDM) is understanding the sensitivity of certain data. It has to be ensured that appropriate measures are taken in the data curation process to ensure their adequate protection. This is particularly relevant in the fields of social sciences, education, and behavioral sciences, where personal data or data that could be linked to individuals are often processed.

To regulate the processing of personal data, the European Union has had the General Data Protection Regulation (GDPR) since 2016. Article 4 of the GDPR defines personal data as “any information relating to an identified or identifiable natural person.” Particularly sensitive personal data is further highlighted in Article 9, which includes, among other types of information:

• Ethnic origin
• Political opinions
• Religious or philosophical beliefs
• Trade union membership
• Genetic, biometric, and health data
• Data concerning a person’s sex life or sexual orientation.

The processing of these sensitive data is generally prohibited under the GDPR, unless the data subjects explicitly consent to it, or another law permits it. For this reason, it is particularly important that these conditions, such as the presence of valid informed consent, be considered from the outset in the RDM process when working with this type of data.

To ensure the ethically and legally sound publication, archiving, and secondary use of data, several conditions should be met, including:

• Researchers should have obtained the informed consent for data processing and storage from participants before data collection.
• Data managers and institutions should offer/enable the possibility of secure publication, possibly with the option to choose protection levels.
• Both researchers and data curators should be familiar with and adhere to necessary guidelines and points of contact for relevant questions (e.g., discipline-specific guidelines, the responsible ethics committee for the respective institution, applicable laws).

Even if all these conditions are met, not all data can be published. In this case, still, it should be ensured that at least the Metadata is openly accessible – because even if a dataset cannot be released for reuse, this information and its findability can still be of great value for research.