Research Data Management refers to all actions that are necessary to make digital research data permanently usable. The aim is to carefully organize and maintain the data generated in the research process and to make the research data freely accessible to all scientists in order to promote the public distribution of knowledge. This also supports also associated topics such as Open Data and Open Access.
The Alliance of the German Science Organization with its Principles and the German Research Foundation (DFG) with their guidelines have created the first fundamentals for handeling research data. They include without limitation following points:
- Planning for research data management must already be taken into account in the project planning and application phase
- The protection and free accessibility of the research data shall be granted provided that no scientific or legal interests are violated, for example in the form of data protection guidelines or obligations towards third parties
- The use of relevant standards and procedures should be followed in order to improve the quality of the data and to ensure its reusability
These guidelines are intended to help increase the recognition of researchers and the reputation of scientists. Many external funding organizations already demand to stick to the guidelines but also promote them in their projects.
Research data generally refers to all data that can be generated, collected, processed or analyzed during the research process. This includes research results and any necessary tools or procedures that have arisen in the course of research work and to solve research tasks.
Research data management describes the entire planning, recording, processing, documentation, archiving and publication of the research data.
The policy and recommendations for handeling research data at the Bauhaus-Universität Weimar
The Thuringian Ministry of Economics, Science and Digital Society (Thüringer Ministerium für Wirtschaft, Wissenschaft und Digitale Gesellschaft, TMWWDG) promotes several projects to improve the use of digital media as part of its strategy for digitization in higher education. This includes the development of a separate policy for handeling research data at every university in Thuringia. The »Guideline for handling research data« of the Bahaus University in Weimar was approved by the university management on February 12th, 2020.
After it was discussed in various university committees, the »Recommendations for Handling Research Data« was confirmed by the Presidium on October 13, 2021. It serves as a supplement to the already published guideline. The document describes the legal framework as well as the requirements of third-party funders and research communities for handling data in the various phases of a research project. Different focal points such as data management plans, personal data or the publication of research data are dealt with. It explains which models, services and support offers are available.
In addition to the recommendations, an adapted format for handling research data is offered in the Moodle course "Wissenschaftliches Arbeiten@Bauhaus - English" for students.
Organized Workshops
With the help of the TKFDM network and local institutions, various public workshops were held that dealed with developments related to research data management at the Bauhaus University. Here you will find a list of these workshops with further information and the possibility to download the materials.
18.06.2019: RDM-Days 2019
"Research Data Management at the Bauhaus-Universität Weimar and internationally"
(organized by TKFDM; Language: German)
[Download ] [More Information]
- Presentation of the TKFDM network
- Introduction to research data management
- Presentation of the survey results: Insights into the handling of research data at the Bauhaus University Weimar
05.06.2020 - Long Night of Academic Writing 2020
"Open Data: Organisation und Veröffentlichung von Forschungsdaten"
(organized by Bauhaus Research School, University Library and eLab; Language: German)
[Download ] [More Information]
- Definition and motivation for Open Data
- Presentation of the models for dealing with research data:
- 5S Data Model
- 3-2-1-0 Backup rules
- FAIR Principles
01.07.2020: RDM-Days 2020
"Data Management Plans: FAIRify your Data!"
(organized by TKFDM, Language: English)
[Download ] [More Information]
- Presentation of the guideline for dealing with research data at the Bauhaus University Weimar
- Presentation of various offers of help in relation to research data management
26.11.2020: Online Workshop in Bauhaus Research School *UPDATE 16.09.2021*
"Research Data Management: From Planning and Organization to Publication"
(organized by Bauhaus Research School, Language: English)
[Download] [More Information]
- Why Research Data Management?
- Policies and data management plan
- Introductions to models about research data management
27.01.2020: Coffee Lecture zu 5S Data
"5S Data: Setz dich auf deine 5 Buchstaben und organisiere deine Daten!"
(Thüringer Kompetenznetzwerk Forschungsdatenmanagement, Language: German, slides also in English)
[Download] [More Information]
- Origin of 5S?
- How can the 5S methods be fulfilled with research data management?
10.06.2021 - Lange Nacht des wissenschaftlichen Schreibens 2021
"Plattformen zum kollaborativen Schreiben"
(organized by Bauhaus Research School, Universitätsbibliothek and eLab; Language: German)
[Download] [More Informationen]
- Why are collaborative writing tools useful?
- Presentation: Nextcloud, Sharepoint, GitLab, Overleaf
- More tools and research environments
25.06.2021: RDM-Days 2021
"How to deal with Reseach Data – Recommendations for the Data Life Cycle!"
(organized by TKFDM, Language: English)
[Download ] [More Information]
- Presentation of the recommendations for dealing with research data at the Bauhaus University Weimar
- Current developments and offers
The Thuringian Competence Network for Research Data Management
Right now not every institution of higher education in Thuringia has a contact point for research data management. For this the Thuringian Competence Network Research Data Management provides a Thuringian-wide platform that not only contains information material and news about events, but also offers a help desk to which all questions about research data management can be addressed. Furthermore, events are held regularly and training courses for different target groups are also available on request.
The information website forschungsdaten.info
![[Translate to English:] forschungsdaten.info](/fileadmin/user/uni/zentrale_einrichtungen/ub_bibliothek/UB-Logo/fdi-logo.png){kind=logo}
The website forschungsdaten.info was created as a Germany-wide platform to provide materials in German language on the subject of research data management. On the platform are u.a. videos, tutorials and information texts that allow an overview of the topic as well as specific subject information. It will also cover specific subjects as well as presenting projects and organizations dealing with research data management in different regions.
The new DFG-Code 2019 and Research Data Management
![[Translate to English:] dfg-kodex-2019](/fileadmin/_processed_/b/8/csm_dfg-kodex-2019_83be9aa201.png)
On July 3rd 2019, the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) released new »Guidelines for Securing Good Scientific Practicehttps://www.dfg.de/download/pdf/foerderung/rechtliche_rahmenbedingungen/gute_wissenschaftliche_praxis/kodex_gwp.pdf« (Code), which becomes effective on August 1st 2019. The Code replaces the Position Paper »Protection of Good Scientific Practice« (2013) previously in effect. These guidelines are an important part of science, since a large part of the externally financed projects at the university institutions come from the DFG organization.
From the 19 guidelines formulated in the Code, the following ones are relevant to research data management.
Guideline 7: Cross-Phase Quality Assurance
- Continuous quality assurance throughout the whole project
- Presentation of the measures in the event of disclosure or publication of the data
- Publicly available data (including source code) must be persistent, citable and well documented
- Goal: replicability and transparency
Guideline 10: Legal and Ethical Framework Conditions
- Active information and knowledge obligation of the researchers
- Documentation of the rights of use of all research results
- Holder of rights of use are primarily the data authors and they decide on further access for third parties
Guideline 11: Methods and Standards
- Orientation on community standards
- Development of standards where none exist
- Quality assurance of research data
Guideline 12: Documentation
- Documentation according to standards in the field of expertise
- Protection of documentation against manipulation
- Documentation of the source code of research software
Guideline 13: Public Access to Research Results
- Open Data: Making research data, materials and methods openly available
- Orientation to the FAIR principles (Findable, Accessible, Interoperable, and Re-usable)
- Publishing on recognized archives or repositories
- Appropriate licensing especially for research software
Guideline 17: Archiving
- Archiving all publicly available research results for a reasonable period of time, if possible over 10 years
- Orientation to standards in the field of expertise
- In the case of opt-out: statement of reasons
- Universities ensure the infrastructure
The National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur, NFDI)
The various specialist consortia of the National Research Data Infrastructure have the task of systematically accessing, sustainably securing and making available the databases of science and research and of networking them (inter-) nationally. Thus, they represent an important role in the research data management of many scientific institutions. More information can be found here from the German Research Foundation (Deutschen Forschungsgemeinschaft, DFG). In 2020, the NFDI association was also founded, which reports on the consortia and further developments.
In cooperation with the Thuringian Competence Network for Research Data Management and the Service for Research Data Management at FSU Jena an Overview for the NFDI-Consortia was created. Also the contact persons are listed there.
In the three application rounds, consortia are selected to ensure coverage of the scientific disciplines within the NFDI: from cultural, social, human and engineering to life and natural sciences. The following consortia were created and are officially funded:
1. Round (start of funding October 2020):
- DataPLANT: Plant research data
- GHGA: German Human Genome–Phenome Archive
- KonsortSWD: Consortium for the Social, Educational, Behavioural and Economic Sciences
- NFDI4Biodiversity: Biodiversity, Ecology and Environmental Data
- NFDI4Cat: NFDI for sciences related to catalysis
- NFDI4Chem: Chemistry consortium for the NFDI
- NFDI4Culture: Consortium for Research Data on Material and Immaterial Cultural Heritage
- NFDI4Health: NFDI personal health data
- NFDI4Ing: NFDI for Engineering Sciences
2. Round (start of funding October 2021):
- BERD@NFDI: NFDI for Business, Economic and Related Data
- DAPHNE4NFDI: Data from PHoton and Neutron Experiments for NFDI
- FAIRmat: FAIR Data Infrastructure for Condensed-Matter Physics and the Chemical Physics of Solids
- MaRDI: Mathematical Research Data Initiative
- NFDI4DataScience: NFDI for Data Science and Artificial Intelligence
- NFDI4Earth: NFDI Consortium Earth System Sciences
- NFDI4Microbiota: NFDI for Microbiota Research
- NFDI-MatWerk: National Research Data Infrastructure for Materials Science and Materials Engineering
- PUNCH4NFDI: Particles, Universe, NuClei and Hadrons for the NFDI
- Text+: Language and text-based research data infrastructure
3. Round (start of funding January 2023):
- Process is running...
In addition to the consortia, there are cross-cutting issues that are treated as separate sections. These are:
Free Online Courses
Forschungsdatenmanagement auf einen Blick – eine Online-Einführung
(Projekt FOKUS - Forschungsdatenkurse für Studierende, 2019, Language: German)
[Project] [Online Portal] [Repository]
This platform was funded by the BMBF and is an introduction to research data management aimed at both students and researchers. It contains the following contents (translated):
- Introduction FDM
- FDM cycle
- Research data policies
- Good scientific practice
- Data Management Plans (RDMO)
- Metadata and metadata standard
- FAIR principles
- Data quality
- Data organization
- Data storage, backup and data archiving
- Privacy
- Copyright
- Promotion law
The Technical University of Darmstadt, Goethe University Frankfurt am Main, Justus Liebig University Gießen, Fulda University of Applied Sciences and Philipps University Marburg were involved in the preparation of the content.
MANTRA – Research Data Management Training
(JISC Managing Research Data Programme, 2011, Update 2017, Language: English)
[Project] [Online Portal] [Repository]
MANTRA is an online course aimed at doctoral students and other academic staff dealing with digital data. The portal includes the following contents:
- Research data in context (Introduction)
- File formats & transformation
- Data protection, rights & access
- Data management plans
- Documentation, metadata, citation
- Sharing, preservation & licensing
- Organising data
- Storage & security
- Data handling tutorials (e.g. based on SPSS, R, ArcGIS etc.)
The platform was created at the University of Edinburgh. On a blog and a Youtube channel they speak about the topic and innovations.
CESSDA Data Management Expert Guide
(CESSDA Training Working Group, 2017, Update 2019, Language: English)
[Online Portal]
The Expert Guide is designed by European experts to help social science researchers make their research data Findable, Accessible, Interoperable and Reusable (FAIR). The portal includes the following contents:
- Plan
- Organise & Document
- Process
- Store
- Protect
- Archive & Publish
- Discover
- Contributors
The Expert Tour Guide on Data Management is created for CESSDA ERIC by ADP, AUSSDA, CSDA, DANS, FORS, FSD, GESIS, NSD, SND, So.Da.Net and UKDS and is illustrated and edited by Verbeeldingskr8.