Managing
Research Data
From collection to archiving
Member of the Helmholtz Association
Research data
are data that result during the course of scientific research, experiments, measurements, surveys or polls. (DFG 2009)
Research data management (RDM)
RDM is the systematic handling of these data over their entire life cycle, starting with the collection and analysis of data and going all the way to (further) processing, archiving, and – if desired – publication.
Research funding
Evidence of structured data management both during and after the research process also has advantages when applying for external funding.
Research and data
What is RDM all about?
For more information, see forschungsdat
en.info (in German)
• Reduces the risk of data loss
• Makes data available and reusable
• Avoids “floods” of data
• Facilitates the implementation of ethical standards and principles of good scientific practice
• Provides legal certainty
• Enables better data exchange within research groups (e.g. data transfer between generations of doctoral researchers)
ADVANTAGES OF RDM
From the preamble to the “Principles for the Handling of Research Data”, Alliance of Science Organizations in Germany, 2010.
F indable
Your research data can be found and cited
ARE YOUR RESEARCH DATA FAIR?
A ccessible
Your research data can be accessed under specific conditions
Interoperable
Your research data can be reused in terms of technology (formats, software)
R eusable
Your data are understandable and can be reused
FAIR data principles
Optimal data practices for humans and computers
For more information, see go-fair.org
What’s it all about?
The FAIR principles are guidelines that are intended to make data reusable in the long term. FAIR stands for findable, accessible, interoperable, and reusable.
Applying these principles guarantees that data can be accessed and used across disciplines and countries.
„Quality-assured research data are a cornerstone of scientific knowledge and [...] can often serve as the basis for further research. [...] Preserving research data over the long term and making them available therefore does not only serve the verification of prior results, but also, to a large extent, the obtaining of future ones.“
Data management plans
Planning, structuring, and
coordinating how data are handled
What is a data management plan?
A data management plan (DMP) is an important tool for structuring how you handle your research data.
DMPs can serve as both checklists and ongoing documentation, from data collection right up to long-term storage or publication of the data.
More and more research funding bodies, such as the EU or the German Federal Ministry of Education and Research (BMBF), require DMPs to be submitted.
What information does a DMP contain?
A DMP consolidates information, in a structured manner, on how research data will be handled.
This includes determining responsibilities as well as providing information on existing rights and obligations, approaches to be taken, and storage and archiving aspects.
ADVANTAGES OF A DMP
• Easier coordination of data exchange in collaborative projects
• Easier documentation for reporting obligations
• Easier reuse of your own data
• Reduced risk of data loss
DMPs at Jülich
Create a DMP online for your funding application
What DMP tools are available at Jülich?
Jülich researchers can use our central DMP Tool to create DMPs online quickly and easily.
Using the question catalogue provided, data
management can be documented for both individual and collaborative research projects.
The user-friendly web application permits a
collaborative approach to creating DMPs by assigning various roles, and makes it easier to keep an overview of data in larger research projects.
You can use the templates provided to create DMPs that meet specific funding bodies’ requirements, and then use them directly for your funding applications.
What Jülich guidelines apply?
The Guidelines for Handling Research Data at Forschungszentrum Jülich recommend creating a DMP.
https://dmp.fz-juelich.de
CREATE YOUR DMP HERE:
Guidelines for Handling Research Data
https://intranet.fz-juelich.de/zb/rdm_guidelines
Publishing data
Substantiate your research results by making them accessible
Sharing is caring – and this also applies to research data. Data are not only valuable to your own research but can also provide important impetus for other work after your project is completed.
Where should I publish my data?
Online data repositories allow research data to be securely stored and found for longer periods of time.
• Data become verifiable and reusable by others
• Data are assigned a DOI
• Recognition for your work through data citation
• Better comparability of results
• Opportunity for meta-analyses
• Supports interdisciplinary research
ADVANTAGES OF PUBLISHING DATA
Discipline-specific data repository: established services exist in many specialist communities
Institutional data repository: Jülich DATA Generic data repository: e.g. Zenodo, RADAR
Data journals: focus on description and methodology of data collection
Jülich DATA
Forschungszentrum Jülich’s data repository
LEARN MORE ABOUT JÜLICH DATA:
https://data.fz-juelich.de What is Jülich DATA?
Jülich DATA is Forschungszentrum Jülich’s central data repository. It is primarily a central reference system for Jülich’s data output.
This is irrespective of where the data are actually stored. Data referenced in Jülich DATA are automatically assigned a DOI after publication, making them citable.
What is a DOI?
A digital object identifier (DOI) makes it possible to reference publications and data in a globally unique and permanent way. As a member of DataCite e.V., Jülich assigns its own DOIs.
How should I handle unpublished data?
Long-tail data can be managed in the long term through Jülich DATA. This refers to data that are either not yet published or intentionally will not be published.
Access restrictions ensure that only a limited circle of people, defined by the author, can access this data and will be shown the data as search results.
Metadata standards
Data about data
Metadata make it possible to find and use digital data and objects. This is why it is important to add comprehensive metadata to your research data.
Types of metadata
Bibliographic/administrative data
contain information on the creation and administration of the data as a whole. They are typically quite general and not very community-specific.
Descriptive/specialist data
describe individual aspects or data sets in more detail and offer additional information. They are structured differently depending on the discipline; specific metadata standards already exist for some disciplines.
For questions on metadata, please contact ZB’s RDM team at
forschungsdaten@fz-juelich.de
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Year Author
Keywords Title
Measurement method Sample
Device
Interviewee
Location Coordinates
Research software
Better software, better research
Research data often go hand in hand with research software. Such software is used to perform analyses, simulations, processing, and many other tasks in research.
Software is more complex than data because...
...it covers a wide range: from very extensive to minimalist, from large-scale projects to
“I programmed this over lunch”, from commercial to self-developed
... it involves many different areas:
copyright and licences, reproducibility and quality, documentation and long-term maintenance, etc.
Better software benefits science
The aim is to offer organizational and technical support that benefits sustainability and the open science mentality:
DFG: good scientific practice requires good software Helmholtz Open Science: Jülich is helping to prepare a guideline on sustainable research software at the Helmholtz centres
The Research Software Engineers association pushes for change on a national and international level (https://www.de-rse.org/en)
Active support at Jülich
Developers of research software can benefit from several services at Jülich:
GitLab: Joint development and much more https://intranet.fz-juelich.de/zb/rse_gitlab
Corporate Development (UE-I) offers developers advice on licensing issues:
https://intranet.fz-juelich.de/zb/rse_license
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Electronic lab notebooks
Simplify lab workflows by going digital
Lab notebooks are part and parcel of day-to-day research in the natural sciences. They are used to record measurement results, experiment sketches, and analyses.
But what if these data are in digital form? Do you print them out and stick them in the notebook? Hardly.
Electronic lab notebooks (ELNs) can help.
The introduction of electronic lab notebooks is each institute’s responsibility
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ELN guide from ZB MED (in German) https://doi.org/10.4126/FRL01-006415715
• Keep your lab notebook using your computer, smartphone, or tablet
• Full-text searches across all content
• Work collaboratively
• Data security, access control
• Ensures data integrity –
timestamps make data verifiable
• Import or link files as required
• Integrate other systems (API)
• Export to PDF and other formats
WHY USE AN ELN
Lifetime of storage media
Hard drives, DVDs, and USB sticks will always fail eventually. Often, they fail too quickly to conform with the rules of good scientific practice, which require research data to be stored for ten years.
If data are lost, research is lost. Regular data backups put you on the safe side. While cloud solutions are convenient, they are also problematic: it is often unclear where the data are stored and what happens if the provider is hacked or goes out of business.
Official services provided by your own institute or Forschungszentrum Jülich, and additional trustworthy cloud solutions like Sciebo, ensure your data are secure.
Storage done right
Hard drives can be lost, but repositories cannot.
Valuable data should be stored and secured so that they are permanently accessible. Repositories or services provided by Jülich, such as Jülich DATA, are suitable for this.
Storage media
No backup? No sympathy!
For questions on storage, please contact ZB’s RDM team at
forschungsdaten@fz-juelich.de
?!
DVDs:
up to 10 years
Hard drives: 2-10 years USB sticks:
max. 10 years
Tip: store 3 data copies on 2 different storage media, with 1 copy at an external location
TRAINING AND ADVICE
• Introduction to research data management
• Creating data management plans
• Describing data using suitable metadata
TECHNICAL INFRASTRUCTURE
• Institutional data repository “Jülich DATA”, which assigns DOIs
• Online DMP Tool
Contact and services
Support for your research
Contact
Central Library (ZB) Forschungszentrum Jülich RDM Team
forschungsdaten@fz-juelich.de https://www.fz-juelich.de/zb/rdm https://chat.fz-juelich.de/channel/fdm
Publication details
Published by: Forschungszentrum Jülich GmbH (FZJ);
conception: FZJ Central Library, based on flyers published by Digitale Hochschule NRW; layout: Thomas Arndt; image credits:
Forschungszentrum Jülich/Wilhelm Peter Schneider (poster); all other images, graphics, and icons were either created by FZJ or taken from https://unsplash.com and https://pixabay.com/de;
printed by: Porschen & Bergsch
