Before Data Collection – Overview

Before your data collection starts, there are several aspects of your data management planning that have to be considered. Writing a data management plan can be a useful way to outline and document this process. However, if you should decide that you do not want to invest time in  formalizing your data management planning, you should still at least consider the following aspects:

  • Is a new data collection really necessary for answering your project’s research question? Can you alternatively address its research question by reusing data, that already exist?
  • (How) Do you want to publish research data that are generated within this project?
  • Responsibilities: Who will be responsible for which aspects of the project’s data management?
  • Which policies do apply to your project’s data management?
  • For projects that receive third-party funds:
  • Who owns the research data that result from your research project?
  • Are there any project outputs that are subject to third party rights (e.g. of test publishers)?
  • Data protection issues
    • Do you collect personal data? How do you plan to maintain privacy and confidentiality of participants?
    • Do you have to obtain informed consent from participants? Does this informed consent interfere with your data sharing plans?
  • Do you have to obtain ethics review? Do data management related consequences arise from this ethics review?
  • Data integrity: How do you ensure that important files of your project will not be changed accidentally?
  • Data selection: Under which circumstances is which kind of data stored or discarded?
  • Transparent science: Whenever possible, openly document your data collection procedures and hypotheses before your data collection starts. Study pre-registration is a great way of doing this. You can use best practices on transparent science, that have been published by Cooper (2016) and Christensen (2016), as guidance.