Manuals

This model contract regulates the transfer of data by researchers to research data centers for the purpose of reuse. The Consortium for Social, Behavioral, Educational, and Economic Sciences (KonsortSWD) has developed a model contract for data collection in research data centers. This model takes into account a wide range of practical applications and has a modular structure. Within the framework of VerbundFDB, the KonsortSWD model contract has been adapted and shortened to meet the specific needs of research data centers collaborating in VerbundFDB.

The aim of this guide is to highlight the requirements, opportunities, and challenges associated with sharing teaching videos for reuse by third parties. This publication is intended to help researchers make an informed decision between making their data available and archiving it internally within their project. The guide is aimed at researchers who collect data in the field of video-based teaching research. It can be used as a research data management tool. The prerequisites mentioned are the necessary legal clarifications, the existence of informed consent, and ethical considerations. The potential benefits of sharing data are discussed as opportunities. These include increased transparency and legitimacy of findings, as well as positive effects on the scientific reputation of the primary researcher. The higher the analytical potential of the teaching videos, the greater the benefits of data sharing. The increased effort involved in providing teaching videos is discussed as a challenge.

This guide is intended for researchers in the educational and social sciences who are planning online surveys and provides practical advice on compliance with data protection regulations. It offers a comprehensive overview of data protection aspects that need to be considered when planning and conducting online surveys. Topics covered include selecting suitable software, recruiting and managing participants, and designing and obtaining informed consent.

Editable sample contract (only available in German) In the digital world, it is increasingly common for data collected by non-scientific actors to be of interest to scientific research. In educational research, for example, this includes data generated through the use of learning platforms or digital learning tools. In order to use this data for scientific purposes, a contractual agreement is required. Below is a sample contract for the scientific use of such a database belonging to a non-scientific actor.

This publication aims to help researchers identify and reflect on the requirements and processes involved in collecting and using social media data, thereby enabling and facilitating the productive and legally compliant handling of this data. This guide first presents a general introduction to the definition of social media (Chapter 2) and discusses various ways of accessing social media data and linking this data with data from other collection formats (Chapter 3). It then takes an in-depth look at key areas of law that may be affected by research involving social media data (Chapter 4). The description refers to relevant laws and regulations, but also aims to reflect on the legal basis and its significance for research practice using practical examples. Chapter 5 discusses the aspect of data protection in concrete terms using the topic of informed consent, with a special focus on the particularities of collecting data in and with social media. Finally, the guide provides tips and recommendations for archiving and publishing social media data, with references to more in-depth sources of information on this topic (Chapter 6).

When collecting qualitative research data, it is very important to systematically document contextual information about the survey situation so that the data is also comprehensible to third parties, thereby enabling the data to be reused. This guide provides guidelines for contextualizing qualitative survey data. 

When processing quantitative data, missing values in a data set should generally be treated with the same care as valid values, i.e., missing values should also be coded, named, checked for inconsistencies, and declared as such (cf. Trixa et al. 2019; Jensen et al. in press; Jensen 2012: 31 f.). [...] To assist with coding, VerbundFDB has developed this guide based on standards applied by the German Center for Higher Education Research and Science Studies (DZHW), the Research Data Center at the Institute for Quality Development in Education (FDZ at IQB), and the GESIS Data Archive.

In order to ensure the traceability of research data for secondary users, i.e., researchers not involved in the survey, the data must be prepared accordingly and the associated documentation materials must be made available in a consistent and traceable manner. A number of minimum requirements should be observed in this regard. Against this background, this document provides 1. an overview of the data and documentation to be submitted, 2. a checklist of the necessary steps for providing quantitative data, and 3. detailed explanations on the preparation of quantitative data. 

This publication provides text modules as a guide for drafting a consent form for empirical studies. This usually consists of an information section describing the study and presenting the request (for consent), information on data protection, and the consent form itself, which must be signed by the data subjects. 

This publication provides text modules that serve as guidance when drafting consent forms for participants in empirical studies in plain language. These consent forms usually consist of an information section describing the study and the request for consent, information on data protection, and the consent form itself, which must be signed by the participants.

Data protection requirements influence research practice in many ways and at different stages of a research project. Compliance with these requirements in the research process is a key prerequisite for being able to use the collected research data in the desired manner. This applies to the evaluation of data, the publication of results based on this data, and its archiving and provision to a research data center, which is increasingly being required of project participants by research funding agencies. Against this background, this text deals with the problems and challenges that arise for research projects in connection with data protection requirements and the reuse of research data. The guide is intended to support researchers in the field of empirical educational research in taking data protection requirements into account in their research activities. This paper is based on experiences from the project “Securing and Reusing Research Data from the BMBF Framework Program for the Promotion of Empirical Educational Research” (duration 10/2014 - 09/2016). This project was a collaborative project between the data centers of the three institutes DIPF, GESIS, and IQB, which joined forces to form the “Research Data Education Network” (cf. Meyermann et al. 2017). In the second funding phase (10/2016 - 09/2019), the plan is to further expand the Research Data Education Network (VFDB) within the research data infrastructure, thereby creating a joint, central point of contact for researchers in empirical educational research. At www.forschungsdaten-bildung.de, researchers can record their own research data, search for and find empirical studies and data from others, and obtain information on topics related to research data management. 

The following section first lists typical funding requirements that stipulate the archiving of data. This is followed by examples of deletion requirements under data protection law (section 2). These are then compared with some examples of approval requirements under school law (section 3). Based on this, the relationship between all legal requirements is clarified and possible solutions are presented using examples (section 4), before a conclusion summarizes the results (section 5). In the appendix, interested readers will find a discussion of the basic principles of data protection law and their relevance for the collection of video data. 

Personal data is collected and used in various ways in the context of research projects. As a rule, this requires the consent of the individuals whose data is involved, but sometimes also the consent of legal guardians.

The legal requirements for such consent to be valid are high. However, whether personal data of the persons concerned may be collected and used at all depends on the correct fulfillment of these requirements. The validity of the consent obtained therefore determines the admissibility of the respective research project and the admissibility of any subsequent use of the data by third parties.

The checklist presented here is therefore intended to provide assistance in drafting declarations of consent. 

A methodology or field report documents information about data collection. This information is necessary to ensure that research data can be interpreted correctly by third parties—researchers who were not involved in the collection process. This text provides specific guidance on what to consider when preparing a methodology or field report.

The checklist provides an overview of the various components of data management and can be used as a basis for a data management plan. A brief introduction explains the purpose of data management for social science empirical research. 

This document is intended to serve as a practical guide for researchers on the anonymization of quantitative data. 

This publication summarizes the workshop entitled “Introduction to Research Data Management in Empirical Educational Research,” which was developed by the Research Data Education Network and conducted by CESSDA Training (GESIS) on May 18-19, 2015, at the GESIS site in Cologne. The workshop concept addresses relevant topics in research data management and comprises six modules: Module 1: Introduction – What is Research Data Management (RDM)?, Module 2: Metadata and Documentation, Module 3: Ethics, Anonymization, and Data Protection, Module 4: Data Administration and Storage, Module 5: Copyright and Licensing, Module 6: Data Transfer and Reuse. 

Compliance with data protection regulations and the protection of the personal rights of research subjects are key requirements for the archiving and reuse of personal research data. One of the building blocks for this is the anonymization of research data. The term “anonymization” refers to the process of removing information from research data that would enable the identification of specific individuals. This guide provides an overview of the anonymization of qualitative interview transcripts and qualitative audio and video materials, which are frequently used in empirical educational research, especially in school and classroom research. 

The productive diversity of data types in interdisciplinary and multi-method educational research leads to a high degree of heterogeneity in data description. This particularly affects the findability of research data, which makes it difficult to reuse. One of the goals of the Verbund Forschungsdaten Bildung (VerbundFDB) is therefore to increase the visibility of data via the VerbundFDB portal and to centralize the indexing of research data from various research data centers (FDZ).To this end, VerbundFDB has developed a common metadata standard for describing studies, which is strongly oriented toward the needs of the educational research community. This includes, for example, the harmonization and standardization of metadata documentation, which can be used to make decentralized data sets visible and searchable in a central location. To expand its central indexing system, VerbundFDB developed a technically scalable solution (harvesting) with and for its cooperation partners, which enables the continuous integration of reliable metadata via the DOI registration agency da|ra.Since mid-2020, this low-threshold metadata integration service has been available to all da|ra users and is already being used by several FDZs. A prerequisite for the integration of data records via da|ra is the use of the metadata standard defined by VerbundFDB and the provision of information about the data in the scope and form of a defined metadata core set (VerbundFDB core set for educational research), which is intended to ensure the quality of data description across institutions. The solution outlined above can also be adapted to other fields of research. 

The publication was developed as part of the “Verbund Forschungsdaten Bildung” network and offers a compilation of sample wording for terms of use for research data centers. The sample wording is designed as a modular system. Various text modules are available for different areas, which can be compiled as needed and addressed in the terms of use. The aim is to provide research data centers with wording aids and ideas for 1) which specifications and regulations they can establish within the framework of their data provision processes and 2) how their own terms of use can be developed or existing ones adapted. In this publication, each topic area is explained in more detail, regulatory requirements are derived, and appropriate wording examples are provided.

In the last decade, the call for sharing research data has intensified within the educational research community in Germany. This development has taken place within the professional communities and it has been spurred by research funding organizations mandating researchers to share their research data. However, researchers and data centers alike are aware that not all data might be fit for re-use. Therefore, research data should be evaluated with respect to their analytical potential for re use. Yet, criteria and processes for identifying data with high re-use potential are lacking. Thus, a workshop on the topic "Re-use potential of research data" was held on June 19th, 2018, at the Institute for Educational Quality Improvement, which was organized within the German Network for Educational Research Data (Verbund Forschungsdaten Bildung, VerbundFDB). Participants were ten researchers from different disciplines of empirical educational research in Germany. Representatives from the educational sciences, psychology, economics and sociology were present. The aim of the workshop was to develop and discuss quality criteria for research data from the perspective of secondary users of research data.

This manual provides a detailed introduction to the metadata set of the Research Data Education Consortium. The metadata set is divided into project, study, and data collection levels. The data elements of all levels are clearly presented and described in tabular form. 

The VerbundFDB offers an automated way to integrate research data registered with da|ra into the VerbundFDB search. This guide lists the da|ra metadata elements that must be specified for this purpose and describes how to enter them in the da|ra entry form. 

Ensuring sustainable and fundamentally open access to research data and results for scientists is crucial for gaining knowledge, ensuring quality assurance, and ultimately for the success of scientific research. Against this backdrop, the Research Data Education Network (VerbundFDB) has been working on behalf of the BMBF since October 2013 to establish and design a research data infrastructure for empirical educational research.

This publication begins by describing the requirements for a research data infrastructure for empirical educational research, which arise from the special characteristics of this field of research. It then presents the three central services offered by VerbundFDB. Looking back, it briefly describes the experiences gained during the first funding phase of VerbundFDB and provides an outlook on future tasks. The concluding summary discusses future tasks and challenges.

This volume documents the contributions and results of a workshop on “Archiving and Access to Qualitative Data” organized by the German Data Forum (RatSWD) and the Qualiservice Data Service Center at the University of Bremen on April 27 and 28, 2018. The aim of the workshop, which was attended by more than 50 researchers from various social science and humanities disciplines as well as representatives of research data centers, was to evaluate previous experiences and identify requirements for an improved archiving infrastructure in qualitative research.

On June 19th, 2018, a workshop on the topic "Re-use potential of research data" was held at the Institute for Educational Quality Improvement, which was organized within the German Network for Educational Research Data (Verbund Forschungsdaten Bildung, VerbundFDB). Participants were ten researchers from different disciplines of empirical educational research. Representatives from the educational sciences, psychology, economics and sociology were present. The aim of the workshop was to develop and discuss quality criteria for research data from the perspective of secondary users of research data. 

The article reports on the workshop of the same name, which took place at DIPF in November 2017. It was organized by the Commission for Qualitative Education and Biography Research of the DGfE and the German Network of Educational Research Data.