Research Integrity

Regardless of whether your research involves personal data, Tilburg University expects all researchers to follow responsible research data management practices.

Effective management of research data is essential for ensuring its integrity, accessibility, transparency and long-term availability. Funders, publishers, and institutions increasingly require clear data management plans that adhere to the principles of Findability, Accessibility, Interoperability, and Reusability (FAIR).

Source: Digitalbevaring.dk / Jørgen Stamp – used by Aarhus University

Research Data Management Regulation
Tilburg University's Research Data Management Regulation embodies the university’s commitment to responsible data handling, emphasizing proper management and sustainable availability of research data. These regulations outline key principles, codes of conduct, roles, and responsibilities to ensure data quality, accessibility, and compliance with legal frameworks, including:

• Netherlands Code of Conduct for Research Integrity
• The Tilburg University Code of Conduct
• General Data Protection Regulation (GDPR)
• Code of conduct for using personal data in research
• Copyright law

The Research Data Management (RDM) regulation can be found on the following webpage: https://www.tilburguniversity.edu/intranet/research-support-portal/rdm/regulation 

The RDM regulation covers several critical areas:

1. Responsibilities: The researcher ensures secure data storage, compliance with regulations, and the creation of a Data Management Plan (DMP) before starting research. They must follow policies for handling personal data, research with third parties, and supervising students and PhD candidates.The DMP is a dynamic plan, it is created at the start of the research and can be adapted and updated during the research. More information is available in the factsheet “Tips For Writing a Data Management Plan”.
2. Storage and Access: Research data must be securely stored with metadata and necessary information for verification and reuse, using Tilburg University-designated facilities or certified third-party repositories. Encryption keys must be kept separate from encrypted data. More information about where to store your data during your research is available here.
3. Storage Period: Unless otherwise required, research data must be stored for at least 10 years after the research is formally completed.
4. Ownership: Research data generated through employment, internships, or secondments at Tilburg University belong to the university unless stated otherwise in a contract. The Research Data Office (researchdataoffice@tilburguniversity.edu) provides guidance on ownership.
5. Public Disclosure: Research data should be publicly available whenever possible unless restricted by funder agreements, confidentiality obligations, GDPR, or third-party intellectual property rights. Metadata must always be public. The Research Data Office offers guidance on disclosure.
6. Personal Data: Personal data must be managed in accordance with GDPR. 
7. Third-Party Research Collaboration: External researchers must comply with Tilburg University’s data policies and GDPR. Agreements with other institutions must clarify data storage rights. Research conducted for external clients must ensure Tilburg University retains data management rights. The School’s Dean must approve any deviations from standard policies in third-party agreements. If you have questions, contact your school’s data representative.

Proper organization and documentation improve data retrieval, reuse, and accuracy while preventing errors.  

1. Data Organization:  
   • File Naming: Use a clear, consistent system. Include elements like **date (YYYY-MM-DD), content description, creator name, or version number** (_v01, _v02) to uniquely identify files.
   • Versioning: Always retain the original raw data. Avoid vague names like *final* or *new*. Instead, use major versions (v1, v2) and minor updates (v1.1, v1.2), with change documentation.
   • Folder Structure: Plan a logical structure beforehand to streamline file access, support collaboration, and avoid time-consuming reorganization.
2. Data Documentation: Good documentation makes data understandable, discoverable, and reusable. Essential levels include:
   • Project-level: Research questions, hypotheses, methods, and data collection details.  
   • File-level: A README file explaining file relationships, formats, and order.
   • Variable-level: Definitions of variables, labels, codes, missing values, and syntaxes/commands.

Systematic documentation enhances data quality, ensures long-term usability, and supports research replication. Journals and funders may also require a data package.

A data package includes:

• Data files: Include both raw and processed data.
• Data documentation: Describe the project (e.g., purpose, research questions, hypotheses) and provide essential data details for reuse and replication (e.g., variable definitions, value explanations, units, missing data). This can be part of the dataset or in a separate codebook.
• Materials: Include all digital materials needed to replicate the study, such as questionnaires (if permitted), instructions, scripts, and participant materials like the information letter and blank consent form.
• Analyses: Add syntax files, code, or scripts used in the analyses to allow full replication of the reported results.

Documentation can be provided via README files, codebooks, text files, or embedded in data files/syntaxes. Some schools have specific requirements. Contact your school's RDM contact person before creating your package.

More information on creating a data package can be found here.

The university's basic principle is that research data should be made available as openly as reasonably possible for scientific research. This may not be possible due to agreements with research funders, confidentiality obligations, privacy and/or intellectual property rights of third parties.  In any case, the metadata should be made openly available. In case it is not possible to make the data openly available, it may be possible to set up the data availability under certain specified terms of access and or use.

Tilburg University Dataverse is the university’s certified, central repository for archiving and sharing research data, managed by the Research Data Office (RDO). TiU Dataverse is not suitable for data that are traceable to individuals and for data that TiU does not (co-)own. Please contact the Research Data Office via dataverse@tilburguniversity.edu before uploading files that may contain sensitive data. Guidance and best practices for data archiving and sharing, including use of the TiU Dataverse, are available here. 

Publishing your research data increases visibility and impact. Data published in TiU Dataverse is indexed by OpenAIRE and search engines, enhancing discoverability. Publishing your research data creates additional exposure for your research. When you publish your data in TiU Dataverse, your data are harvested by and search engines. Before depositing data, check funder and journal requirements.

It is possible to publish research data in other (e.g., discipline-specific) repositories if they meet the requirements specified in the Research Data Management Regulation. For an overview of repositories, visit re3data.org.

• Avoid sending sensitive research data via email. Instead, use SURF Filesender (supports files up to 100 GB).
• For highly sensitive data it can be recommended to encrypt files. Use 7Zip; available in the software center.
  • Key management is crucial in encryption, since losing your password means losing access. Use Keeper for password storage and sharing.
• Private devices are discouraged. Tilburg University’s PCs and laptops have built-in security, including encrypted drives, antivirus, and firewalls. In addition, do not rely solely on laptops, PCs, or external devices (USBs, hard drives) for storage, as they can fail. If used, encrypt them with Bitlocker. 

The Research Data Management portal provides the necessary guidance, tools, and support to help you manage your research data in line with best practices and regulatory requirements. 

If you need help with Research Data Management, support is available in your school and at the central level (Research Data Office). Check the following link for more details: 
Research Data Management (RDM) & Research IT Support | Tilburg University

The RDO regularly offers training sessions and webinars on RDM topics. Information on upcoming sessions can be found via the Tilburg University LibCal platform, which also features other research-related events: https://tilburguniversity.libcal.com.