RDM at Fanshawe College
In response to Tri-Agency policy, Fanshawe College has drafted this strategy to support researchers and research staff in their adoption of responsible data management practices. This process included institutional assessments of capacity and identification of gaps across each stage of the research data life cycle. It is the college’s intention to continue developing RDM infrastructure and resources over the next 3-5 years. This RDM Strategy will be reviewed and revised accordingly.
What is Research Data Management?
Research data management (RDM) is a framework for organizing research data through the life cycle of a research project. It encompasses the processes to guide the collection, documentation, storage, sharing, and preservation of research data and allows researchers to find, access, and reuse data.
The Tri-Agency, the major Federal government funder of research in Canada, expects that the research it supports is conducted at the highest professional and disciplinary standards. These standards promote research excellence and ensure that research is done ethically, is replicable, and makes good use of public funds. In March 2021, the Tri-Agency launched a policy on Research Data Management. In an effort to promote data stewardship practices among Canadian researchers, this policy requires each post- secondary institution eligible to administer Tri-Agency funds to create an institutional RDM strategy.
Three phases of the policy
Phase One: Institutional Strategies – By March 2023, all institutions must have a published strategy on how they will support RDM.
Phase Two: Data Management Plans (DMPs) – In Spring 2022, the Tri-Agency began identifying the initial funding opportunities where researchers are required to submit a DMP with their grant proposal. Additional programs will require DMP submissions over the coming years.
Phase Three: Data Deposit – After reviewing the institutional RDM strategies submitted, and in line with the perceived readiness of the Canadian research community, the Tri-Agency will phase in the requirement to ensure data is deposited appropriately. Grant recipients will be required to archive in a digital repository all digital research data, metadata, and code that directly supports research conclusions.
Fanshawe College is committed to meeting these Tri-Agency requirements and supporting its researchers in adopting RDM best practises.
Importance of RDM
Making research outputs discoverable, reproducible, and reusable is a requisite characteristic of modern scholarship. Increasingly, data management plans and data deposit are required by funding agencies and journals, both domestically and internationally. While some research data must be safeguarded due to ethical, legal, or commercial reasons, the proper management and sharing of data has practical and financial benefits to the research landscape. Proper RDM will ensure the production of high-quality research data. It can also lead to an increase in the visibility and impact of that research, while enhancing research efficiency. The potential reuse of data should be considered in all stages of the research life cycle in order to achieve these outcomes.
RDM at Fanshawe College
By raising awareness on the best practices in RDM, Fanshawe College intends to reduce research duplication, lower unnecessary burdens on researchers due to repetitive sampling, increase accountability and transparency, allow replication of research results, foster collaborations, and increase academic output and innovative activities. As part of its strong commitment to foster research and research collaborations, Fanshawe College will lead in the development of tools, support, and guidance to enable researchers to manage their research data to the highest standards across the research data lifecycle. Fanshawe College will do this by leveraging relationships with stakeholders at the institutional, provincial and national levels.
- Any original investigation, undertaken to acquire new knowledge, or to apply existing knowledge in a novel way, directed primarily towards a specific practical aim or objective.
- The active management of research data throughout a project to produce datasets that are Findable, Accessible, Interoperable, Retrievable (FAIR).
- The transferring to a data repository of research data collected as part of a research project. The repository should have policies describing deposit and user licenses, access control, preservation procedures, storage and backup practices, and sustainability and succession plans.
- The process of destroying data stored on tapes, hard disks, and other forms of electronic media so that it is completely unreadable and cannot be accessed or used.
Data Management Plan (DMP)
- A formal statement that describes how research data will be managed and documented throughout a research project and outlines the terms regarding the subsequent deposit of the
data within a data repository for long-term management and preservation. Note that properly managing data does not necessarily equate to publishing or sharing that data.
- The process of safeguarding data from corruption, compromise, or loss. Data protection also encompasses safeguarding against unethical data usage.
- Infrastructure designed to preserve, manage, and provide access to many types of digital materials in a variety of formats. Materials in online repositories are curated to enable search, discovery, and reuse. There must be sufficient control for the digital material to be authentic, reliable, accessible, and usable on a continuing basis.
- The practice of checking the integrity, accuracy, and quality of data.
- The process of converting information or data into a code, especially to prevent unauthorized access.
- Primary sources that support technical or scientific enquiry, research, scholarship, or creative activity, and that are used as evidence in the research process and/or are commonly accepted in the research community as necessary to validate research findings and results. Research data covers a broad range of types of information and can be structured and stored in a variety of formats. Example of research data include documents, digital objects, laboratory notebooks, photographs, codebooks, audio and video tapes, models, specimens, etc.
Research Data Management (RDM)
- The processes applied throughout the lifecycle of a research project to guide the collection, documentation, storage, sharing, and preservation of research data.
- Classified, usually private, information that must be protected and is inaccessible to outside parties unless specifically granted permission.
Support research activities by encouraging sound data management and data stewardship practices at Fanshawe College. Provide an environment which ensures that research data is accessible, usable, safe, and trusted. Raise awareness about the benefits of and best practices in research data management. Provide clarity and strengthen researcher engagement by outlining procedures and supports available.
Following over two decades of education legislations, including the 2000 Postsecondary Education Choice and Excellence Act which enabled Ontario colleges to grant baccalaureate degrees, colleges have emerged as key players in advancing the national innovation agenda. Applied research is an essential component of college programming and much of the federal funding made available to colleges is in support of partner-focused applied research designed to meet the changing needs of the economy. As such, it is in the best interest of the College to equip both novice and more experienced researchers with skills and supports that will enable them to engage in a wide scope of research endeavours and apply RDM best practices to all activities. The following principles guide RDM at Fanshawe College:
- Support for Researchers
Create a culture of learning and build capacity of researchers through the provision of tools and training in order to incorporate best practises of RDM in all research endeavours. Focus on reducing real and perceived barriers throughout the research life cycle.
- Fostering of Collaborations
Support collaborative research activities with external partners (industry, non-profit, academic, and community partners) and across internal academic areas and departments.
- Promotion of a Context-Based Approach
Adapt awareness and training materials to a college context. Promote a flexible model of RDM that is adapted across different disciplines and domains. This is especially important for research involving traditionally marginalized communities and/or the collection of sensitive data.
This strategy applies to all research activities encompassed within policy A201 Scholarship, Research, and Creative Activity, and includes internally- or externally-funded and non-funded research activity associated with Fanshawe College that is conducted and/or supported by faculty, students, administrative employees, and support staff employees.
- Centre for Research and Innovation (CRI)
- Fanshawe Library
- Fanshawe IT
- Research Ethics Board (REB)
- Centre for Academic Excellence (CAE)
- Institutional Research
- Institute of Indigenous Learning
- Innovation Village
- Fanshawe researchers (faculty, staff, students)
Members of the RDM Steering Committee welcome feedback from the broader Fanshawe research community to enhance this strategy and implementation initiatives.
Contact email@example.com if you would like to learn more.
The Dean, Centre for Research and Innovation, is responsible for ensuring the creation and implementation of the RDM strategy, in compliance with Tri-Agency requirements. The steering committee is responsible for the consultation and development of the RDM strategy, and for ensuring progress towards implementation of the strategy.
Goals and Objectives
Goals and Objectives:
- Build Awareness of RDM within the Fanshawe community
- Ensure the RDM strategy is integrated with other relevant college strategies and policies
- Build dynamic process documents that articulate roles and responsibilities that are clearly defined and complementary across departments to support RDM strategy and any related policies
- Create ongoing communication channels so that researchers are knowledgeable about general RDM policies and processes and can identify and locate available services and supports
- Be responsive to changes in national policies and guidelines around RDM.
- Regularly communicate any updates in best practises for RDM and integrate into support materials.
- Provide support for Fanshawe researchers and encourage RDM best practises
- Provide training resources to increase the knowledge of RDM, RDM strategy, DMP, data curation, data deposit, data destruction, data validation, data protection and encryption, and related software available for Fanshawe researchers
- Ensure that researchers are aware of available services and have access to the resources required at all stages of the research project.
- Provide support so that researchers can identify and address security and risk related to research data, including legal, privacy, and vulnerability issues, and can categorize their data using Fanshawe’s classifications to assess their risk level
- Support access to, and training on, a variety of both licensed and open-source tools for data collection and analysis.
- Increase access to RDM-related infrastructure and tools
- Ensure appropriate infrastructure access and support for researcher data sharing and collaborations with external partners regardless of location
- Provide managed storage space for active research projects and ability for all participants to access as appropriate
- Provide storage space for projects that have sensitive, confidential, and/or proprietary data requirements
- Acquire and support an institutional data repository for uploading of datasets at project close
- Support tools and expertise to ensure preservation as dictated by College and/or funder policies, and commitment and space to maintain long-term integrity and access
- Support access to tools for security and encryption of research data
Short-term actions (3-year horizon):
- Formally focus portion of faculty support role within CRI to dedicate to RDM and determine the ongoing support needs over 3 years
- Stay apprised of and respond to funder requirements and associated deadlines related to RDM, data management planning, and data deposit
- Focus on awareness-building, training, and support
- Facilitate researcher access to internal and external tools related to data management planning and data collection and analysis
- Develop educational resources, deliver training sessions, and be available for consultation
- Define support model for RDM from the Library Learning Commons
- Facilitate access to institutional data repository
- Investigate support models for data curation, data deposit, data destruction, data validation
- Develop process to support researcher training between both Library and CRI
- Define the IT support model for RDM and other research activities (IT and CRI)
- Form working group with researchers, Institutional Research staff, IT, and CRI to understand in more detail what is needed, with regards to support and tools
- Develop IT role, either in IT or within CRI, dedicated to supporting research activities
- Ensure any current licencing agreements meet current needs
- Build multi-year IT roadmap to align with institutional budget cycles
- Consider need for additional personnel support for expanded RDM demand and services and impact on departmental budgets. This may necessitate role changes, hiring and training of new staff, etc.
- Develop communication plan to accompany strategy roll out (CRI)
- Update website to house all RDM information in one place (CRI)
- Launch joint initiative between CRI, REB, and Library to communicate who does what for Research at Fanshawe (including RDM, but not exclusively). Build new webpage to clarify. (CRI with REB and Library)
- Steering committee to review progress on strategy on annual basis
- Steering committee to confirm commitments towards strategy implementation on annual basis in alignment with institutional budget planning process
- Note one-off requests for additional support as they come up and as the researcher needs change
- Formalize the personnel support model