Data Hub Content
Data Hub
The Data Hub centralizes support for student and faculty use of numeric, qualitative, and spatial data throughout its lifecycle. With the help of the three desktops on the second floor of the Library and an in-house Data Librarian, users can find the appropriate resource in the form of software and expertise to collect, manage, analyse, store, and publish data for teaching, learning, and scholarship.
Data services can be accessed beyond its physical presence in the Library. The MRU Community may participate in workshops, one-to-one consultations, and access data collections as well as website support for data use.
Areas of support
Find Data
Receive support for data searching and access with:
- Data collections
- Individualized consultations
- Curriculum-integrated data literacy sessions for students
- Workshops for students and faculty
Data Collection tools
The Data Hub provides support for introductory use of data collection and analysis tools. Novice users may also get assistance with accessing and setting up software or importing data.
Assistance with statistical analysis or advanced research methodologies is not provided.
Data Management
Research data management (RDM) is the process of organizing and safeguarding data to ensure it remains accessible.
RDM includes:
- Data management planning
- File organization and security
- Documentation and metadata development
- Archiving and publishing data
The Data Hub will work with instructors to integrate RDM practices into research-focused courses (i.e. research methods, honours, and capstone courses) to encourage the development of these skills alongside existing research pedagogy.
Training in RDM will be offered to student research assistants (RA), in addition to existing RA training services.
Through collaboration with The Office of Research, Scholarship and Community Engagement (ORSCE), the Data Hub will support faculty in these areas through workshops and consultations.
Software and Tools
The Data Hub will provide access to software and online tools that support data collection and analysis. Software is accessible on all data workstations and a selection are available remotely. Broad categories of software and tools made available through the data hub include:
- Quantitative data analysis
- Qualitative data analysis
- Spatial data analysis
- Data visualization
For a full list of software available on the data workstations please check out the Find Software in the Library tool, search by location 'Data Hub'.
Workshops
Choosing a Repository for Your Research Data
Large publishers like Public Library of Science and Springer Nature now require authors to make their data publicly accessible, with few exceptions. The Tri-Agency will soon be implementing a research data management policy that expands its open data archiving requirements for funded research. But not all of these bodies offer guidance on selecting an appropriate repository for data. In this session, we’ll outline some of the factors to consider when choosing a repository for your research data and discuss specific repository options across disciplines.
Research Data Management and the Tri-Agency’s Draft Policy
A growing number of funders and publishers are implementing policies requiring researchers to plan and document their data management practices and to archive their research data. In this session, we will discuss the Tri-Agency’s Research Data Management Draft Policy and go over the principal elements of research data management, including organization, documentation, storage, and data publishing.
Creating a Data Management Plan
Get introduced to the fundamental elements of research data management planning using the Portage Network’s DMP Assistant. Attendees will have the opportunity to sign up for a DMP Assistant account and begin writing a data management plan. Participants are encouraged to come with an existing research project in mind, but practice projects will also be available.
Collecting Social Media Data for Research
Social media are potentially rich sources of data for research, but it can be difficult to systematically collect these data without coding skills. In this session, we will cover tools and methods for gathering data from social media sites, including Twitter, Facebook, and other platforms, that don’t require coding. Participants will have an opportunity in the workshop to use some of the tools and begin collecting data.
