Project planning
Research data management considerations arise in the planning and preparation phase of research projects. This document is provided as a source of information regarding data management plans, Research Data Management requirements, conducting searches for usable research data and legal issues connected to RDM.
Data management plans
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Why have a data management plan?
A data management plan (DMP) provides a useful structure for the handling of research data gathered in a research project. The plan is a forward-looking effort to organize the research project, addressing technical, methodological, logistical and legal considerations pertinent to the handling of digital data. A well-structured DMP is useful for avoiding unpleasant surprises and having to spontaneously come up with ad hoc solutions during project execution. DMPs facilitate conformity with Good Research Practice in several ways, particularly regarding transparency and the reproducibility of research results. Structured research data management is increasingly of interest to key third-party funding providers, such as the EU, the Federal Ministry of Education and Research (BMBF) and the German Research Foundation (DFG), and attaching a DMP can improve chances for a funding application.
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What content does a DMP have?
DMPs differ greatly in terms of scope and level of detail, depending on the research project and the specifications of funding providers and research associations. You should thus determine in advance what recommendations you should follow for your research project (see below). A DMP typically addresses the following, at a minimum:
- Background information on the research project, including the data controllers and project funding
- A description of the research data to be collected or reused
- Information on the standards applied for describing research data, documenting processing steps and generating metadata
- Information on data storage, backup and access control during the project term
- Information on what data will be published where and what long-term data archiving options will be used
Other issues may be relevant as well depending on the research project, such as legal and ethical questions, how to organize collaborative work and labor and non-labor costs connected with research data management.
DMP-Service
We support you with your Data Management Plan through our DMP-SERVICE.
RDM requirements
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RDM for FAIR data
Third-party funding providers, research communities and research institutions are increasingly requiring that research data be handled in structured fashion. In addition to promoting Good Research Practice, the view is often held that research data should be published in addition to the published text and such data rendered reusable — especially for data gathered using public funding. Numerous technical, documentation-related and legal requirements have to be met however in order to provide transparent, reusable data.
The FAIR-Principles are often cited as a set of guidelines for Research Data Management, according to which data should be findable, accessible, interoperable and reusable. These four principles allow deriving several specific data publication measures aimed primarily at enhancing metadata quality.
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Advice and further information
Our FAIR Data Quick Start Guide provides a practical introduction to the implementation of the FAIR principles in your research project.
For any questions you may have regarding requirements for Research Data Management, please contact us at [Email protection active, please enable JavaScript.]
Several discipline-specific resources on policies and guidelines can be found here: https://www.forschungsdaten.uni-bonn.de/en/fdm/disziplinspezifisch/disziplinspezifisch-enYou may also find the following external resources useful to become informed about RDM requirements relevant to you:
- Biernacka, Katarzyna et al. (2019). Wie FAIR sind Deine Forschungsdaten? https://doi.org/10.5281/zenodo.2547338
- An overview of the RDM requirements imposed by several different funding organizations is provided on the website forschungsdaten.info: https://www.forschungsdaten.info/themen/planen-und-strukturieren/foerderrichtlinien/
- The DFG has released general guidelines for the handling of research data: https://www.dfg.de/foerderung/antrag_gutachter_gremien/antragstellende/nachnutzung_forschungsdaten/ (in unseren disziplinspezifischen Materialien finden Sie ggf. die Konkretisierungen einzelner Fachkollegien)
- Humboldt-University zu Berlin provides model DMPs structured to meet DFG, BMBF and EU Horizon 2020 requirements: https://www.cms.hu-berlin.de/de/dl/dataman/arbeiten/dmp_erstellen
- A comprehensive list of data policies of different organizations is provided at forschungsdaten.org: https://www.forschungsdaten.org/index.php/Data_Policies
- The Thuringian Competence Network for Research Data Management has prepared an information sheet on the RDM requirements of the DFG, BMBF and EU: https://forschungsdaten-thueringen.de/files/material/Infomaterial/Handreichungen/handreichung_fdm_anforderungen.pdf
Finding research data
Generating research data is typically a complex and expensive undertaking. The FAIR principles for data publication are intended to enable the reuse of data for further research inquiry. You should focus on relevant data journals and repositories and utilize relevant search engines to locate datasets useful for your research project. Before deciding where to publish your own research data, please consult our advisories on publishing research data and our discipline-specific information.
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Data journals
Documented research data are published as data papers in data journals. A list of existing data journals is provided at Forschungsdaten.org: https://www.forschungsdaten.org/index.php/Data_Journals
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Repositorien
Datasets are stored and made available in data repositories, frequently in accordance with a profile of data collection criteria specific to the field of research. We generally recommend using the re3data registryto search for repositories.
Please read our discipline-specific advisories on repositories as well. Additional repository search options include- the Directory of Open Access Repositories: https://v2.sherpa.ac.uk/opendoar/
- and the Master Data Repository List of the Web of Science Group: https://clarivate.com/webofsciencegroup/master-data-repository-list/
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Search services
Some services can be used to search for datasets from multiple sources:
- the EU service B2FIND: http://b2find.eudat.eu
- Google Dataset Search: https://datasetsearch.research.google.com/
- DataCite Metadata Search: https://search.datacite.org
- FAIRsharing: https://fairsharing.org/databases/
- Mendeley Data: https://data.mendeley.com/
- OpenAire Explore: https://explore.openaire.eu/
- BASE (Dokumentart Forschungsdaten auswählbar): https://www.base-search.net/
- for the social sciences:
- GESIS Data Search: https://datasearch.gesis.org
- CESSDA Data Catalogue: https://datacatalogue.cessda.eu/
- UK Data Service: https://ukdataservice.ac.uk/
- Verbund Forschungsdaten Bildung: https://www.forschungsdaten-bildung.de/studienliste.php?la=de
- for the geosciences
- DATAONE: https://www.dataone.org/
- European Data Portal (search engine for public sector data) https://www.europeandataportal.eu/
For questions on conducting searches for usable research data, contact us at [Email protection active, please enable JavaScript.]
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You may find the following resources on finding research data useful:
- Gregory, Kathleen et al. (2018): Eleven quick tips for finding research data. In: PLoS computational biology 14 (4), e1006038. DOI: 10.1371/journal.pcbi.1006038.
Legal issues
Current legal issues connected to research data can be highly complex, concerning several different areas of law. You should explore any legal issues during the planning phase to ensure that your research project will be conducted in conformance with applicable laws, avoiding unpleasant surprises. Rights and obligations connected with the data have to be clarified if you intend to publish your research data at project conclusion. This is true in particular if you intend to license usage of the data (see Usage Licenses under Publishing Data).
Copyright law must be considered, first of all, under which rights of use to academic/scientific works accrue fundamentally to the authors. The intellectual or informational content is not, however, protected as a work, but rather only the expression or presentation thereof. Research data do not necessarily fall within the scope of copyright law, as copyright is predicated upon a certain degree of creation, i.e. being a product of one’s own creativity. This condition may not be fulfilled, such as where raw data from measuring instruments are concerned. Copyright law is thus generally more applicable to qualitative rather than quantitative data, as the former frequently involves the creative work of an author.
When data is organized in a database however, copyright-like protection may arise in the form of a database right if creation of the database required a “substantial investment” (§87a of the Copyright Act [UrhG]). And even a database can potentially constitute a work for the copyright purposes in certain cases (a “database work”).
Copyright law raises difficult questions in many cases because it is an absolute right accruing to the author personally and is only transferable to a limited extent. If multiple individuals are authors (joint authorship), they hold joint copyright. The situation may be complicated further if cooperation partners are located in different jurisdictions. Other legal areas such as ancillary copyright for press publishers and labor law may also be relevant. Rights of use to research data may also accrue to the employer (i.e. the University), for data generated by assistants or technical staff, for example.
In many research projects, data protection and personal rights play an important role, particularly when identifiable individuals are the focus of the research as is often the case in e.g. the medical and social sciences. The data protection law safeguards the control of individual personal data. Generally, individuals can decide freely on how their data is being used. In other words, personal data–which means all information relating to an identified or identifiable natural person (Art 4 Para 1 GDPR)–may only be collected and processed with informed and explicit consent of the data subject. As you must obtain such consent prior to collecting any data, you should plan in advance the handling of data for the duration of the project (and beyond). During the project, personal (or other sensitive) data must be protected from unauthorized access (see section on Storage and Security). Various data repositories offer special security measures for the archiving of such data (see section on Archiving). Prior to publication, personal references should generally be removed by applying anonymization methods.
Please contact us with any legal questions on research data you may have, but be advised that the Research Data Service Center does not provide binding legal advice. If you believe you may require specific legal advice, please contact the University’s Legal Department, the Data Protection Officer, or the advisory centers for research contrats an research ethics.
You may find the following law and research data-related resources useful:
- Bundesministerium für Bildung und Forschung (BMBF) (2019): Urheberrecht in der Wissenschaft (Copyright law in academia) (insb. 24ff) https://www.bmbf.de/SharedDocs/Publikationen/de/bmbf/1/31518_Urheberrecht_in_der_Wissenschaft.pdf?__blob=publicationFile&v=3
- Forschungsdaten.info: Datenschutzrecht (Data protection law )https://www.forschungsdaten.info/themen/rechte-und-pflichten/datenschutzrecht/
- Forschungsdaten.info: Urheberrecht (Copyright law): https://www.forschungsdaten.info/themen/rechte-und-pflichten/urheberrecht/
- Kreutzer, Till; Lahmann, Henning (2021): Rechtsfragen bei Open Science (Legal Issues with Open Science). Hamburg University Press http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:18-3-2112
- Kuschel, Linda (2018): Wem "gehören" Forschungsdaten? https://www.forschung-und-lehre.de/forschung/wem-gehoeren-forschungsdaten-1013/
- Lauber-Rönsberg et al. (2018): Gutachten zu den rechtlichen Rahmenbedingungen des Forschungsdatenmanagements (Expert opinion on the legal framework of Research Data Management) https://tu-dresden.de/gsw/jura/igetem/jfbimd13/ressourcen/dateien/publikationen/DataJus_Zusammenfassung_Gutachten_12-07-18.pdf
- Brettschneider, Peter (2020): Screencast Rechtsfragen beim Veröffentlichen von Texten und Daten (legal issues of publishing text and data) https://www.kim.uni-konstanz.de/openscience/onlinekurs-open-science-von-daten-zu-publikationen/rechtsfragen-beim-veroeffentlichen/
- Gerlach et al. (2020): Fact Sheet Personal Data https://doi.org/10.5281/zenodo.4035991
- Crews, Kenneth - Asking for permission https://copyright.columbia.edu/basics/permissions-and-licensing.html
- European Commission (2021): Ethics and data protection https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-and-data-protection_he_en.pdf
- HeFDI - Hessische Forschungsdateninfrastrukturen (2021): Rechtliche Rahmenbedingungen des Forschungsdatenmanagements. (Präsentationsfolien) Zenodo. https://doi.org/10.5281/zenodo.4625417
- European Commission: Data Protection Decision Tree https://ec.europa.eu/assets/rtd/ethics-data-protection-decision-tree/index.html
Image sources:
"Plan icon" by Maria Kislitsina from the Noun Project
"Plan Ahead" by skeeze from Pixabay
"Planning" by Digitalbevaring.dk (Jørgen Stamp)
"FAIR Principles" by FosterOpenScience "Nadel im Heuhaufen" by pixel2013 from Pixabay
"Hurdle" icon by Gan Khoon Lay from thenounproject.com
"Search" icon by Luis Prado from thenounproject.com
"Paragraph icon" by Veronika Krpciarova from the Noun Project
"Datenschutz" by Wilfried Pohnke auf Pixabay
Materials:
- Handout: FAIR DATA Quick Start Guide
- Guide to the ‘Handling of Research Data’ in DFG project proposals (en/de)