Canada is at the cusp of an historic opportunity as new computational paradigms emerge and data becomes more massive, more available, and more complex. This cuts across all disciplines and fields, and is changing the speed at which we work, how we work, and what we can accomplish. The competitive advantage of our research community is increasingly affected by these developments, and the ability to support a growing digital economy requires a proactive response.

We have a strong foundation from which to grow our position as a global leader in the knowledge economy. Canadians are among the best in the world at creating, interpreting, visualizing, and manipulating data. And currently, Canadian researchers, students and industry have access to extensive computing capabilities, ultra-high capacity networks, data management and storage, and highly trained personnel to manage the system.

However, our ecosystem is strained, and we stand to lose ground without progressive and integrated planning and support for advanced computing and analytics. Canada is facing a data deluge — and with that comes an opportunity for both significant innovation as well as for potential disruption.

Collective investment and coordinated stewardship of a world-leading, integrated DI ecosystem is now needed to secure Canada’s continued success in the global economy.

What Is DI

Canada’s advanced digital infrastructure ecosystem is holistic, integrated and includes:

  • A Framework – the policies and legal framework within which digital research is undertaken that includes coordination and alignment of various components of the digital research environment; the suitability of funding systems for e-research; and the capacity of Canada to deal with other international players in digital research;
  • Expertise and Skills – the sufficiency and quality of skilled personnel for effective use of the e-infrastructure;
  • Tools and Services – the software, applications and human support services that enable researchers to derive value from their data and to optimize the use of the digital infrastructure;
  • Research Data Management– the collecting, structuring, standardizing, archiving, and sharing of data, while ensuring flexibility, security, accessibility, interoperability, affordability, and high performance of the system;
  • Computational Resources – hardware, software and service resources that enable both compute-intensive and data-intensive research, including both Cloud and Grid computing;
  • Networks – the means by which researchers are connected, linking researchers to data sources, and transporting data among different locations; and
  • Collaboration – the means of connecting researchers within research initiatives that are geographically dispersed and/or are utilizing common datasets and tools.