​​​​​​​Methodology & Process

To assist in evaluating and planning, UBC selected to adapt the Research Infrastructure Self-Evaluation (RISE) tool, developed by the Digital Curation Centre in the United Kingdom. The RISE framework assists institutions to benchmark themselves in order to facilitate RDM service planning and development. The tool provides a framework for discussion, enabling relevant stakeholders to contribute their experience to all aspects of a holistically envisioned service to reach a shared vision of where the RDM service should be. This model provides a framework to assess the current level of RDM maturity across the institution and breaks down different goals that can be prioritized for the future. Based on this model, the UBC RDM strategy attempts to document both our current and desired state in the broad scope of RDM. A working group was struck from members of the steering committee to apply the RISE model, adapt it to the UBC context, and consult with the research community. Extensive consultation was, and remains, critical to this process.

Extensive consultation with the UBC research community formed an integral component of the development of this strategy—first when implementing the RISE model, establishing the maturity baseline and setting priorities for the future, and then once again during the drafting of this document.

The multifaceted approach to engaging with the community included town halls, focus groups, as well as sessions integrated into regular meetings of existing groups of stakeholders. Throughout the consultation period, a web-based form remained available to collect community feedback.

Key definitions

Research Data

Research data are data that are used as primary sources to support technical or scientific inquiry, research, scholarship, or creative practice, 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 may be experimental data, observational data, operational data, third-party data, public sector data, monitoring data, processed data, or repurposed data. What is considered relevant research data is often highly contextual and determining what counts as such should be guided by disciplinary norms.

Research Data Management

Research data management (RDM) refers to the processes applied through the lifecycle of a research project to guide the collection, documentation, storage, sharing and preservation of research data.

FAIR Principles

The FAIR Data Principles (FAIR is an acronym for Findable, Accessible, Interoperable, and Reusable), are a set of guiding principles proposed by a consortium of scientists and organizations and proposed in 2016 to support the reusability of digital assets. These principles have since been adopted by research institutions, funders, and journals worldwide. The guidelines are timely as we see the unprecedented volume, complexity, and speed in the creation of data.

CARE Principles

The ‘CARE Principles for Indigenous Data Governance' address concerns related to the people and purpose of data; Collective benefit, Authority to control, Responsibility, and Ethics, and their respective sub-principles. The CARE Principles detail that the use of Indigenous data should result in tangible benefits for Indigenous collectives through inclusive development and innovation, improved governance and citizen engagement, and result in equitable outcomes. use of data across time in order to minimize harm, maximize benefits, promote justice, and allow for future use.


First Nations land acknowledegement

We acknowledge that UBC's two main campuses are located on the traditional, ancestral and unceded territories of the xwmə0– kwəyˇəm (Musqueam) and Syilx (Okanagan) peoples, and that UBC’s activities take place on Indigenous lands throughout British Columbia and beyond.

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