Data Bites: Research Data Management Essentials (Fall 2026)
Dates/times: every Tuesday, September 15 - December 1, 2026, 12:00 - 12:30 PM
Location: Harriet Irving Library Research Commons Innovation Hub (HIL 316) and via Microsoft Teams
Credential: Digital badge upon successful completion
UNB Libraries is pleased to offer a skills-based, professional development series in Research Data Management. Designed for upper-level undergraduate and graduate students, researchers, staff involved in projects funded by Canadian funding bodies and interested in improving their research data management (RDM) skills are welcome to attend.
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.
The series consists of three modules comprising twelve 30-minute lunchtime sessions that build toward RDM portfolio participants can use in their own research. Upon successful completion, participants will receive digital badge recognizing their RDM competencies. To earn the digital badge, participants will complete three short assignments throughout the course and submit a capstone Research Data Package at the end.
All sessions will be offered in person on the Fredericton campus and streamed via Microsoft Teams for remote attendance.
Registration is required for each session to receive the Teams link. Walk-ins are always welcome. Register for the complete series or pick the sessions of most interest to you!
Module 1: Organizing Data
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 practical workshop explores how selecting the right file formats can support long-term preservation, data sharing, and reuse. Learn best practices for choosing formats that align with FAIR data principles.
Participants will learn how to:
- Identify preferred file formats for preservation, sharing, and interoperability
- Distinguish between proprietary and open formats and understand their implications
- Apply practical guidelines for selecting file formats throughout the research data lifecycle
This practical workshop focuses on strategies for organizing research data using clear and logical directory structures. Manage files more effectively to support collaboration, reproducibility, and long-term data stewardship.
Participants will learn how to:
- Design directory structures that reflect research workflows and support project organization
- Implement naming and hierarchy conventions for easy navigation and version control
- Apply best practices to maintain consistency and clarity throughout the research lifecycle
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)
Module 2: RDM Foundations
This 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 session 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:
- Make research data FAIR through planning
- Describe your research data focusing on key questions
- Apply ethical, legal and commercial considerations to the research data
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:
- FAIR meets CARE: understanding the principles
- 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
Metadata is essential for making research data findable, understandable, and reusable. This workshop introduces the fundamentals of metadata and data dictionaries and demonstrates how they support FAIR principles and good RDM practices, with a focus on preparing datasets for deposit in the UNB Dataverse repository.
Participants will learn how to:
- Explain the role of metadata, disciplinary metadata standards, and data dictionaries
- Create basic metadata and data dictionaries for datasets in their discipline
- Prepare dataset documentation suitable for deposit in the UNB Dataverse Repository
Module 3: Sharing Research for Reproducibility
Sharing research data effectively involves more than making it available — it also requires clear citation and appropriate licensing to support attribution, reuse, and compliance with publisher and funder requirements.
Participants will learn how to:
- Distinguish between a data citation and data availability statement and meet publisher and funder requirements
- Select and apply appropriate licenses for research data to support responsible sharing, attribution, and reuse
- Incorporate data citation and licensing practices into research workflows to promote FAIR and Open Science principles
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 session provides a practical overview of depositing datasets into the UNB Dataverse repository, highlighting best practices for sharing and preserving research 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 repository
- Navigate the UNB Dataverse platform and complete metadata fields effectively
- Apply licensing, access controls, and versioning to support open, ethical, and reusable data sharing
GitHub is a widely used platform for managing, sharing, and collaborating on research code, documentation, and other digital research outputs. This workshop provides a practical overview of core features and demonstrates how researchers can use GitHub to improve collaboration, version control, and research reproducibility.
Participants will learn how to:
- Explain the role of GitHub in research collaboration, version control, and reproducible research
- Navigate key GitHub features, including repositories, commits, branches, and pull requests
- Identify practical ways to use GitHub to manage research code, documentation, and other digital research outputs.
RDM Resources
Resources
RDM Contacts
Contacts
UNB Libraries Research Data Management Services support team includes:
- Siobhan Hanratty, Director of Scholarly Technologies and Data/GIS Librarian
- Tatiana Zaraiskaya, STEM Librarian
- Mike Nason, Scholarly Communications Librarian
- Erik Moore, Librarian