Survey on Research Data Management Practices
1.
Which consortium are you affiliated with?
TRR 1583
TRR 221
TRR 295
TRR 225
SFB 1525
SFB 1583
GRK
GoFM
Other (please specify)
2.
What is your project number?
3.
What is your current job level?
4.
How familiar are you with the FAIR principles (Findable, Accessible, Interoperable, Reusable)?
I know and follow the FAIR principles to the best of my ability.
I am familiar with the FAIR principles and have implement them to a degree.
I have heard about the FAIR principles, but I am not sure how to implement them.
I do not know the FAIR principles / they are not applicable to my work.
5.
What guidance would you prefer from the Infrastructure (INF) projects and the Virtual Research Campus (VRC). Rate from lowest (0) to highest priority (3).
0
1
2
3
User meetings and consulting
0
1
2
3
Central data storage
0
1
2
3
Analysis tools and pipelines
0
1
2
3
No preference
0
1
2
3
Other (please specify)
6.
How do you ensure the findability of your research data within the research community?
Metadata Standards: I use standardized metadata schemas to describe my data, making it easier to locate and understand within databases and repositories.
Persistent Identifiers: I employ persistent identifiers like DOIs (Digital Object Identifiers) for datasets, ensuring that they can be reliably found and cited.
Data Repositories: I deposit my data in recognized, subject-specific or institutional data repositories that are widely used and trusted in my research community.
Search Engine Optimization: I use techniques like keywords, tags, and search engine optimization (SEO) to enhance the visibility of my data in online searches.
Data Catalogs: I list my datasets in data catalogs or directories to facilitate discovery by researchers in my field.
Community Platforms and Networks: I share information about my data through community platforms, networks, and professional groups specific to my field.
Collaborations and Networking: I rely on collaborations and networking with other researchers to spread awareness about my data.
Open Access Publishing: I publish data or data papers in open access formats, ensuring they are accessible to a wider audience.
Documentation and Data Papers: I create detailed documentation or data papers that describe my data sets, making them easier to find and understand.
Not Sure / Not Applicable: I am not sure how to ensure the findability of my research data, or this question is not applicable to my work.
Other (please specify)
7.
How do you make your research data accessible to other researchers?
Open Access Repositories: I use open access repositories to store my data, allowing any researcher to access it without restrictions.
Data Sharing Platforms: I share my data through specialized data sharing platforms or networks relevant to my field.
Institutional Data Repositories: I deposit my data in my institution's data repository, which is accessible to other researchers.
Licensing Information: I clearly provide licensing information (like Creative Commons licenses) that specifies how others can use the data.
Publishing Data Papers or Reports: I publish data papers or reports in academic journals to provide detailed descriptions and access instructions for my data.
Interoperable Formats: I ensure that my data is stored in formats that are widely recognized and easy to use across various software and platforms.
Data Accessibility Statements: I include data accessibility statements in my research publications, guiding readers on how to access the associated data.
Collaborative Networks: I engage in collaborative networks where data sharing is a common practice, ensuring my data is accessible to those within these networks.
Data Management Plans (DMPs): I create and follow a Data Management Plan that outlines how my data can be accessed and used by others.
Data Portals and Catalogs: I list my data in data portals and catalogs which are frequently used by researchers in my field to locate and access data.
Not Sure / Not Applicable: I am not sure how to make my research data accessible, or this question is not applicable to my work.
Other (please specify)
8.
How do you ensure that your data is structured and organized to enable interoperability with other datasets?
Standardized Data Formats: I use widely accepted and standardized data formats (like CSV, JSON, XML) to ensure compatibility with other systems.
Use of Controlled Vocabularies: I employ controlled vocabularies and ontologies for data categorization and tagging, facilitating data integration with other datasets.
Metadata Standards: I follow recognized metadata standards to describe my data, which aids in aligning it with other datasets.
Data Wrangling and Transformation Tools: I utilize data wrangling and transformation tools to reformat and structure data as needed for compatibility with other datasets.
Participation in Interoperability Initiatives: I engage in interoperability initiatives and consortia within my research community to align my data practices with broader standards.
Common Data Models: I adhere to common data models (e.g. BIDS, DICOM, FASTA, BioPax, GFF, Bio-Formats, OME-TIFF) or schemas relevant to my field, which promotes consistency and interoperability.
APIs for Data Sharing: I use or create APIs (Application Programming Interfaces) that allow for seamless data exchange and integration with other systems.
Data Harmonization Practices: I implement data harmonization practices to align my data with other datasets, particularly when collaborating with other researchers or institutions.
Regular Data Audits and Quality Checks: I conduct regular audits and quality checks to ensure data consistency and compliance with interoperability standards.
Not Sure / Not Applicable: I am not sure how to ensure the interoperability of my data with other datasets, or this question is not applicable to my work.
Other (please specify)
9.
How do you make your reserach data reusable within the research community?
Use Standardized Data Formats
Provide Comprehensive Metadata. Metadata should include detailed information about the data collection process, data structure, context, and any other information necessary for understanding and reusing the data. Adhering to established metadata standards in your field enhances the data's reusability.
Use Open and Accessible Repositories
Create Clear Data Documentation: Provide clear documentation, including data dictionaries, codebooks, and user guides (e.g. in eLabBook, tutorial, walkthrough, MDs). This helps others understand how to use and interpret your data correctly.
Version Control: If your data evolves over time, use version control to track changes and make different versions of the dataset accessible (e.g. github).
Publish Data Papers or Reports: Consider publishing data papers or detailed reports on your dataset. This can provide context, methodologies, and insights into the data, aiding in its reuse.
Maintain Data Quality: Ensure that your data is accurate, complete, and free of errors. Regularly review and update your data if necessary.
Encourage Community Feedback and Collaboration: Engage with the research community to get feedback on your data and collaborate with others to enhance its utility.
Ensure Legal and Ethical Compliance: Address legal and ethical issues, such as copyright, data privacy, and informed consent. Use appropriate licenses that clearly state how others can use your data.
Other (please specify)
10.
What types of data formats do you primarily work with in your research? (Select all that apply)
Text (e.g., CSV, TXT)
Raw scientific images (e.g., .czi, .lif, .tif, DICOM, Nifti, etc)
Processed images (e.g., JPEG, PNG, TIFF etc)
Structures (e.g., MMZIV)
OMICS (e.g., bam, sam, fasta, hd5)
Structured data (e.g., JSON, XML)
Audio (e.g., MP3, WAV)
Video (e.g., MP4, AVI)
Other (please specify)
11.
Approximately how much storage space does your research project occupy within the funding period?
less than 100 GB
100 GB to 1 TB
1 TB to 100 TB
more than 100 TB
Not sure
12.
How do you prevent data loss?
I store my data in an official Rechenzentrum (RZ) or Medizin-Informatik (MI) server
I store my data in an institutional or departmental server
I store my data in an institutional or departmental server with a backup system
I have my own backup system
I use my own hard drive
Other (please specify)
13.
What would you like to learn more about? Rate from lowest (0) to highest priority (3).
0
1
2
3
Data security
0
1
2
3
Data privacy
0
1
2
3
Where should I save my data and how should I save my data?
0
1
2
3
Guidelines, FAIR principles, good scientific practice rules
0
1
2
3
RDM plan for my project
0
1
2
3
Other (please specify)
14.
Do you use an electronic lab notebook (ELN) for recording your research activities?
Yes
No
15.
Do you use patient-related data in your project(s)?
Yes
No
16.
How do you organize pseudonymization, access and analysis of patient-related data?
Individually for each research group/ principal investigator
Centrally through the IT department
Other (please specify)
17.
Further wishes, questions, needs, or requests?