Data Bites! A Gentle Introduction to Research Data Management (Winter 2026)
UNB Libraries is excited to offer Data Bites! A Gentle Introduction to Research Data Management, a series of in-person workshops.
Research Data Management (RDM) is the practice of organizing, documenting, storing, and preserving research data during and after the research project. Adherence to RDM best practices promotes research integrity and data reuse. Researchers should be aware that a formal Research Data Management Plan (DMP) is now a standard component of applications for many Tri-Agency grants.
Workshop sessions will be available on both the Fredericton and Saint John campuses.
Fredericton
Designed for upper-level undergraduate and graduate students, researchers, and staff, these 30-minute lunchtime sessions will provide foundational RDM knowledge. The Winter 2026 series kicks off on Thursday, January 22, 2026!
- When: Thursdays, 12:00 - 12:30 PM, January 22 to March 26
- Where: Harriet Irving Library Research Commons, Innovation Hub (Room 316)
Join us for the full series, or just for the sessions of most interest to you! No registration required and everyone is welcome!
Online
An online session on March 24 will be offered to replicate some of the content from the full workshop series offered in Fredericton in a single 90-minute afternoon session. The session is designed for upper-level undergraduate and graduate students, researchers, and staff involved in research projects funded by Canadian funding bodies and interested in improving their research data management skills.
- When: Tuesday, 12:00 - 1:30 PM, March 24
- Where: Online (MS Teams)
Please register (Online session only) at: https://bookings.lib.unb.ca/calendar/hwk or in the session description below.
Fredericton Sessions
This hands-on workshop guides participants through the process of creating a simplified data management plan (DMP) using an open-source Canadian tool: DMP Assistant. Designed for research team applying for grant funding.
Participants will learn how to:
- Plan through the research lifecycle
- Describe your research data focusing on key questions
- Apply ethical, legal and commercial considerations to the research data
This workshop will introduce the landscape of research data repositories in Canada. It will provide a practical overview of how to discover, evaluate and select appropriate repositories for different data types and disciplines.
Participants will learn how to:
- Identify and assess trusted Canadian discipline-specific repositories for their research outputs
- Navigate the deposit process to increase data findability, accessibility and long-term preservation
This hands-on workshop focuses on how to use Markdown to create clear, professional README files for research projects. Markdown can simplify your documentation and improve the accessibility and longevity of research data.
Participants will learn how to:
- Apply Markdown syntax to structure and format effective README files
- Include essential elements such as project descriptions, file overviews, and usage instructions
- Use Markdown-based README files to enhance research transparency, reproducibility, and data sharing
This practical workshop explores how licensing supports the responsible sharing, reuse, and attribution of research data. The session highlights best practices for applying data licenses that align with FAIR and Open Science principles within the Canadian data landscape.
Participants will learn how to:
- Distinguish between copyright and data ownership
- Select appropriate licenses for research data reuse and sharing
- Apply Creative Commons licenses effectively
We’ve all been there — missing values and rogue inputs in our dataset. And who could forget data that should be in multiple cells squished into a single cell or multiple cells’ data that should really be in one cell. In this session, we’ll dive into practical, anxiety-lowering tips for cleaning up messy qualitative data in Excel.
This fast-paced workshop is meant for students who have basic to intermediate Excel knowledge. We will all work off a common Excel file filled with messy data and learn how to clean it up during the session.
Participants will learn how to:
- Transform text to all lower case, all upper case and title case
- Remove trailing blank spaces to fix comparability issues
- Join data from multiple cells into a single cell
- Separate data from a single cell into individual cells
- Deal with missing values in your data (time permitting)
- Use Data Validation to force Excel to accept only validated entries (time permitting)
This practical workshop introduces strategies for consistent and meaningful file naming to support better research organization, collaboration, and long-term data reuse. Avoid common pitfalls and adopt best practices in your research workflows!
Participants will learn how to:
- Apply clear and consistent file naming conventions
- Incorporate elements like version control, dates, and identifiers for easy file tracking and retrieval
- Avoid problematic file names that can cause compatibility issues across platforms and systems
This workshop will introduce practices of data citation, explaining its importance for giving credit to authors and enabling reproducibility. It will clarify the relationship between data citation and data availability statement, providing clear guidance on when and how to use them.
Participants will learn how to:
- Write a proper data citation for a datasets
- Distinguish between a data citation and data availability statement and understand publishers’ requirements
- Integrate data citation and availability statements into manuscript to meet journal and funder mandates
This hands-on workshop guides participants through the process of depositing datasets into the UNB Dataverse collection. Join us for a fast paced overview of best practices for sharing and preserving data in alignment with institutional and funder requirements.
Participants will learn how to:
- Prepare and organize research data and documentation for deposit into UNB Dataverse
- Navigate the UNB Dataverse platform and complete metadata fields effectively
- Apply licensing, access controls, and versioning to support open, ethical, and reusable data sharing
This workshop will provide a foundational introduction to the principles of data privacy. It will outline a practical process for assessing data sensitivity and applying key anonymization techniques. Attendees will learn to balance data utility with confidentiality to ensure secure data sharing and publication.
Participants will learn how to:
- Apply core anonymization techniques such as aggregation, suppression, and generalization to minimize disclosure risk
- Evaluate the effectiveness of anonymization efforts to ensure ethical guidelines and data sharing agreements
Online Sessions
This session focuses on best practices for organizing, documenting, and securing research data. Participants will learn essential practices for file naming, choosing sustainable formats, and optimizing directory structure for clarity and reproducibility. The session will also introduce READMEs and Markdown for documentation and cover data privacy basics, including methods for anonymizing datasets and minimizing disclosure risk.
Online via MS Teams
Please register at: https://bookings.lib.unb.ca/calendar/hwk/tidydata-sj26
Some session content has been adapted from workshops developed by the UBC Library Research Data Management Team.
RDM Resources
Resources
RDM Contacts
Contacts
UNB Libraries Research Data Management Services support team includes:
- James MacKenzie | Associate Dean
- Siobhan Hanratty | Data/GIS Librarian
- Tatiana Zaraiskaya | STEM Librarian
- Mike Nason | Scholarly Communications Librarian