Before your data collection starts, there are several aspects of your data management planning that need to be considered. First of all, it should be determined which policies apply to the project’s data management. If relevant guidelines have been identified questions on data ownership, possible third party rights, produced data types, archiving and preservation of data, as well as access and data sharing policies have to be clarified. Ideally, the results of these discussions should be documented in a data management plan. Finally, the ethical and legal framework of the project should be defined. Depending on these framework conditions and the considerations documented within the data management plan, ethics applications and consent forms should be prepared.
- Copyright & Data PrivacyIn this section we provide some basic information on copyright considerations in the context of research data as well as a systematic overview on the legally relevant corner stones for data protection compliant research. This includes a short description of relevant sections within the BDSG and relevant cross-references to the EU-GDPR as well as useful hands-on descriptions for carrying out a data protection impact assessment or writing a consent form. Copyright – Relevant paragraphs of the Federal Data Protection Act (BDSG) In general, primary data are not subject to copyright concerns (Guibalt & Wiebe, 2013; Hillegeist, 2012; Spindler & Hillegeist, […]
- Data Integrity & Data SelectionData Integrity The term data integrity occurs in different contexts, it may refer to the consistency of information recorded within the digital data object or to the consistency of the digital data object itself. Data integrity and Data Cleaning (consistency of information represented by data) Common flaws that can impair quality and consistency of the information that is recorded within a dataset are wild codes (e.g. three different values assigned to the variable sex), values that are out of range (e.g. the value 9 for items with a range from 1 to 5), inconsistent (illogical) values or implausible values. Data […]
- Data Management PlanWriting a data management plan (DMP) can be a useful way to outline and document the intended research data management process. A DMP generally includes all information that adequately describes and documents the collection, processing, storage, archiving, and publication of research data as part of a research project. Typical sections of a data management plan, which is subdivided in the three areas before data collection, during data collection and after data collection, are: Before data collection: Background of the research project Compilation of specific guidelines, recommendations, legal aspects, license contracts Clarification of roles and responsibilities Search and evaluation of […]
- Ethical ConsiderationsIn this section ethical concepts and procedures that should be applied in psychological research are explained. It starts with a short overview of the basic ethical principles, proceeds with a short definition of the conditions under which ethics approval is required and ends with a description of typical elements within an ethics application. Basic ethical principals The first priority of ethically responsible research is the respectful treatment of people who place themselves at the service of science for the purpose of research (DGPs, 2018). The first psychological ethical guidelines were presented by the American Psychological Association (APA) in 1952 and […]
- Roles & ResponsibilitiesTypically, many persons contribute to a research project. The documentation of your research project should include a list of all persons who contributed to parts of the project. Additionally, we recommend to document which persons were assigned to which subparts of the project (e.g. data collections, studies). Each contributor plays a more or less important role for successful data management. Defining the different roles and responsibilities of all contributors at the beginning of the project may help to assign tasks and define workflows, which is especially helpful if the project involves more than one institution. Important roles are for example […]