Definitions
- with a focus on DTU’s Research Data Management Policy
DTU's Research Data Management Policy (pdf)
Associate researcher | A researcher who is not remunerated by the university, but is associated with the university or a research group to carry out specific tasks or functions. |
Biobank | A structured collection of biological material that is accessible according to certain criteria, and where the information linked to the biological material can be attributed to individuals. According to Danish law, biobanks are considered manual registers and are thus included in both the EU and the Danish data protection regulation. |
Confidential data | Information, which by law or agreement must be protected against unauthorized access, use, disclosure, alteration or destruction. This includes personal data, confidential company information and classified information. |
Copyright |
A right that gives the creator of a work the right to dispose of the work, e.g. to make copies of the work or to publish, distribute, reproduce, modify, adapt, transform, publicly exhibit and perform the work. To obtain copyright protection, the work must be original and in a fixed form. Examples of research results that can be protected by copyright:
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Data classification | Categorization into data types in relation to what it would mean to the university and the researcher if this data were lost or compromised. Data classification is the first step in making a risk assessment and taking appropriate security measures to secure data. |
Data license | A legal agreement that governs terms and conditions for the reuse of data by others. For example, Creative Commons licenses or Open-Source Software licenses. |
Data management plan (DMP) | A plan that is typically drawn up at the start of a project and which describes the actions to be taken to collect, process, store, secure, share, preserve and possibly reuse research data in a research project. A DMP is a good tool for aligning expectations between researchers, and it is increasingly a requirement from grant providers and institutions. The researchers can design their own plan or use existing templates, e.g. from their grantor or institution. A DMP can be updated throughout the phases of the project. |
Dataset | A structured collection of research data. |
FAIR principles |
A series of guiding principles to make research data findable, accessible, interoperable and reusable The researchers must follow the FAIR principles when sharing data with others. The principles are primarily recommendations to ensure a good and detailed metadata, as this will contribute to maximizing the reuse of data across technical, geographical and professional boundaries, promote research collaboration and have a positive impact on the usefulness of research.
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Intellectual property rights | Legal rights that exist or are granted for the purpose of securing intellectual creations. This applies, among other things, to copyright, patent rights, design rights and trademark rights. |
Metadata |
Information that describes the properties of an item or data set, and which enables the identification, retrieval and handling of the item or data set in question in the future, e.g. name, unit of measurement, date, contact information, etc. Metadata can take many different forms - from free text to structured machine-readable content. Some disciplines or repositories may have specific requirements for the format and content of metadata, possibly in the form of a formal standard. |
Open Access | Free, unlimited online access to research results such as journal articles, books and datasets. |
Open data | Data sets that anyone can use, reuse and redistribute. Open data is typically deposited in online repositories, where it can be accessed without restrictions on reuse, possibly subject to requirements for references (crediting those who created the datasets) or sharing on the same terms. |
Persistent identifier (PID) | A long-lived reference to a document, file, web page, or other object. In the context of FAIR data, a persistent identifier is an unbreakable and active link associated with a digital object on the Internet. Examples of persistent identifiers are Digital Object Identifiers (DOIs), typically used for journal articles and datasets, and Open Researcher and Contributor IDs (ORCIDs) to identify authors of scientific work. |
Personal data | Information about individuals who can be identified directly or indirectly using this data. E.g. pictures, names or information about CPR number and/or economic, social, cultural, physical, physiological or mental characteristics. |
Principal investigator |
A principal investigator is defined here as a researcher who is the lead researcher on a research project (research leader) and/or leads a research unit and/or has been assigned similar responsibilities by delegation. |
Project participants | Researchers and students who contribute to the research that takes place in a project. |
Repository |
Publication channel for research data. A distinction is made between three types of repositories:
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Research data | Physical material and digital data that has been collected, observed, generated, created or recycled as part of research activities at DTU. This includes all material and data that form the basis of the research, such as e.g. samples, (laboratory) notes, interviews, texts and literature, digital raw data, audio and video recordings, computer code, as well as the precise records of these materials and data that form the basis of the analysis on which the results are based, such as e.g. clinical records, sequence data, spreadsheets, interview files, etc. |
Research data management | A common term for planning, collecting, processing, storing, securing, sharing and archiving primary material and research data. |
Researcher | Anyone who carries out or supports research activities at DTU, including, among others, scientific staff, PhD students, visiting researchers and affiliated researchers. |
Research project |
A project in which a researcher/student or a team of researchers/students seeks answers to research questions by collecting information, after which the information is analysed, and conclusions are drawn based on the processed information. |
Research results | Conclusions based on research data. |
Risk assessment |
Analysis to assess risks to data confidentiality, data integrity and data availability. The risk assessment can be used to map which security requirements must be met and which precautions must be taken to prevent confidentiality breaches, data loss or compromised data integrity. For personal data, a GDPR risk assessment is an assessment of the risk to data subjects' rights. If the GDPR risk assessment reveals a high risk to the data subjects, an impact assessment (DPIA) must also be prepared together with the GDPR risk assessment. |
Supervisor | An experienced researcher who supervises a less experienced researcher or student. |
Third party | A person, a company or another university etc. who collaborates on a research project at DTU without being employed at DTU and who has not entered into a collaboration agreement of which DTU is a part. |
Visiting researchers | A researcher who is employed at another institution or company and who visits DTU for a limited period of time. When visiting researchers carry out research projects and/or handle research data at DTU, they must comply with the DTU policy for research data management as well as any other university policy, legislation or agreement that applies to research at DTU (e.g. legislation on personal data). |