Glossary

Data stewards are experts in research data management. They support researchers in the sustainable handling of research data. In addition, data stewards act as a link between researchers and (research) software engineers, IT and other infrastructures. Other tasks include counselling, training and raising awareness of good practices in research data management.

Based on: https://forschungsdaten.info/praxis-kompakt/glossar/

Data Transfer and Use Agreements (DTUA, DUA) are contracts that regulate the exchange of data between two parties. A DTUA governs the disclosure of a specific data set, authorised uses and all data protection and security requirements relating to the receipt and processing of the data. For these purposes, DTUAs assign appropriate responsibilities to the recipients of the data.

Based on: https://www.purdue.edu/business/sps/contractmgmt/DataTransferUseAgreement.html 

A data management plan (DMP) is a structured document in which the handling of research data in a project is systematically described. It should contain information on how and with which tools (e.g. hardware and software) data is collected, processed, documented, stored, backed up, maintained, archived and, if necessary, published. The DMP also documents the necessary resources and responsibilities. Ideally, a DMP is drafted during the planning phase of a research project, but should be regularly updated and supplemented as the project progresses. The DMP is therefore an instrument for work organisation and project planning, but can also help third parties to interpret and reuse the relevant research data.

Based on: Glossary, Leibniz University Hannover (uni-hannover.de) 

Data provenance documents the provenance or origin of research data, and the processes, methods, tools and algorithms used to produce it. Information on the provenance of research data is crucial to ensure transparency/reproducibility of research and thus strengthen its credibility and trust in it. The relevant information can be recorded in readme files or metadata. Provenance information is central to the implementation of the FAIR Data principles.

Based on: eResearch Alliance: Data Provenance 

A declaration of consent (or informed consent) includes informing participants about what is planned with their data as part of a research project, the purposes for which the data is to be collected and published, and the consent of the participants. Informed consent forms the basis for participation in scientific studies and any subsequent use of the data. It is therefore the basis of research that implements legal provisions and ethical principles.

Electronic lab notebooks (ELN) and laboratory inventory management systems (LIMS) are digital tools that facilitate laboratory work, among other things. ELNs are used to store and record unstructured data, e.g. to organise protocols, notes and data from experiments. LIMS, on the other hand, are intended for structured and repetitive data that follow specific patterns, e.g. when tracking samples from precisely defined, repeated and routine tests.

Based on: https://www.scinote.net/blog/eln-vs-lims-how-to-choose/ 

The term FAIR (Findable, Accessible, Interoperable and Reusable) Data was first coined in 2016 by the FORCE11 community for sustainable research data management. The main aim of the FAIR principles is to optimise the preparation of research data, which should therefore be findable, accessible, interoperable and reusable for both humans and machines.

Based on: FDM Glossary, Freie Universität Berlin (fu-berlin.de); Wilkinson, Mark, et al. 2016. ‘The FAIR Guiding Principles for Scientific Data Management and Stewardship’. Scientific Data 3 (1): 160018. https://doi.org/10.1038/sdata.2016.18.

Research data refers to all data that is generated or used in the course of scientific work. It forms the basis of current and potential future scientific findings and is generally regarded in the scientific community as necessary for documenting and validating research results.

A distinction can be made between primary data (data collected specifically to answer a research question) and secondary data (data collected in a different context and used in research).

Metadata and the documentation of data collection and processing within a research project are essential for the (re-)usability of research data (FAIR Data). If research data is published under open licences, it is considered Open Research Data. 

A research data repository is an online platform for the publication of research data. In line with the principles of FAIR Data and Open Research Data, metadata and documentation (e.g. ReadMe file, codebook, protocol) should be entered alongside the research data in order to make the data easier to find, understand and reuse. Licences can be issued to regulate the subsequent use of the data. Access to sensitive data (e.g. personal data) can be restricted and regulated via a Data Transfer and Use Agreement (DTUA).

Long-term archiving means securing data and its usability across several generations of hardware, software and file formats.

Based on: University Library Bern, BerDA

A licence is a contractually agreed right of use. The rights holder thus authorises their contractual partner to use a work in various ways (e.g. to copy, save or make it digitally accessible). Standardised Creative Commons licences or instruments are generally recommended in the area of research data for which copyright claims exist, in particular CC BY and CC0.

Based on: https://forschungsdaten.info/praxis-kompakt/glossar / Creative Commons

Metadata is a highly structured, standardised description of objects (including data). It provides compressed information on content, structure, technical properties, usage rights and other properties. Standardised metadata makes information findable and usable for machines (e.g. algorithms, search engines). It is therefore central to the implementation of the FAIR Data principles.

Source: https://en.wikipedia.org/wiki/Metadata

‘Open data’ in the broad sense refers to all openly accessible and reusable data sets. In a narrower sense, the term is often used synonymously with ‘open government data’ (open administrative data) and in contrast to ‘open research data’ (open research data). Data is open if it is made accessible with as few legal and technical restrictions as possible. A highly restrictive licence or access barriers (e.g. payment or registration barriers) can lead to research results not being traceable and the subsequent use of the data being made difficult or impossible.

Based on: https://opendatahandbook.org/guide/de/what-is-open-data/

Persistent identifiers (PID) are permanent identifiers that are assigned to a digital object. In contrast to other identifiers such as URLs, PIDs always refer to the object itself. In this way, the identifier does not change, even if the location of the object (usually a website) changes. This ensures permanent traceability. Examples of PIDs are Digital Object Identifiers (DOI), Archival Resource Keys (ARKs), Handle.

Based on: https://forschungsdaten.info, CODATA Research Data Management Terminology

According to the Swiss Data Protection Act (DSG), personal data is any information relating to an identified or identifiable natural person. Personal data can be directly identifying information (e.g. name, address, IP address), but also information that can only identify a person in combination with other information (e.g. profession, place of residence).

Based on: Art. 5 DSG Data Protection Act Switzerland / Fact Sheet Data Protection (University of Basel)

Preregistration means publishing the plan for a research project before or at the start of the project. In specialised fields such as psychology, the procedure is used to strengthen the method-led approach and increase the quality and transparency of research. The aim is to avoid dubious scientific practice (such as the subsequent adjustment of the research question to the results obtained).

Based on: https://help.osf.io/article/145-preregistration

Research results are reproducible if identical results are produced when identical analytical procedures are applied to the same data. This requires that the methods and procedures used are documented correctly and precisely and that all steps of the scientific work are documented. Reproducible results enable transparency and traceability. In contrast, replicability means that the results of the replicated study can be confirmed with new data and the same or other methods. However, the definitions of the terms reproducibility and replicability can vary depending on the discipline.

Based on: https://book.the-turing-way.org/reproducible-research/reproducible-research / Plesser HE (2018) Reproducibility vs. Replicability: A Brief History of a Confused Terminology. Front. Neuroinform. 11:76. doi: 10.3389/fninf.2017.00076

According to the Swiss Data Protection Act (DSG), data relating to health, political or religious beliefs or genetic data, for example, are considered to be particularly sensitive personal data. Occasionally, this is also referred to as sensitive (personal) data. Even stricter protection requirements apply to this type of data.

In Switzerland, different terms are used for this type of data from canton to canton. In the canton of Basel-Stadt, for example, the term ‘special personal data’ is used (IDG, §3, para. 4).

Based on: Art. 5 DSG Data Protection Act Switzerland / Canton of Basel-Stadt, Data Protection Act

Supplementary material (or supplementary data) is material (including data) that cannot be integrated into the main text of a scientific article due to space limitations. This material is not directly necessary to understand the results and conclusions of the article, but may still be relevant to the reader for contextualisation or further research. It is recommended to publish Supplementary Material on a publication or research data repository that assigns DOIs or other PIDs.

Based on: International Journal of Epidemiology 

Large research funders such as the Swiss National Science Foundation, other national research funders or the European Union generally attach the condition of submitting a data management plan and making research data publicly accessible (open (research) data) to the award of project funding, provided there are no legal or ethical obstacles.

Based on: https://www.snf.ch/de/dMILj9t4LNk8NwyR/thema/open-research-data