- What are the main DRI tools, services and/or resources you currently use in your research?
Gbrain and Cbrain from MNI, high performance computing from ComputeCanada, Data management services, ERIC searchable database and Canarie Services.
- Do you have access to all the DRI tools, services and/or resources you need for your research? What are they? What is missing?
Yes I have access to DRI tools services and resources. They are as listed above. What is missing is imaging data for EEG and MRI and fMRI for neurovascular research.
- What are your biggest challenges accessing and using the DRI tools, services and/or resources that do exist and are available to you?
The biggest challenges are getting access to source code for these tools. This stems from the ability to modify source code to meet individual research computing efforts. We also need dedicated cloud storage capabilities to allow distributed processing of data over cloud computing platforms.
Future DRI State
- What is your vision for a cohesive Canadian DRI ecosystem that would fulfill your research needs?
My vision is to allow for a platform to develop interoperability and imaging tools and packages to fulfill research needs. This means constant communication and interaction between research groups, data archiving and storage capabilities, pipelines in data flow and communication and software SDKs for high performance computing.
- What are the types of DRI tools, services and/or resources you would like to use, or envision using, in the future?
I envision using third party SDKs for visualization capabilities, image processing tools and resources for functional and structural imaging, surgical robotics software, machine learning capabilities and government support and funding for these capabilities at leading research and academic organizations.
- What challenges do you foresee while using integrated DRI tools, services and/or resources?
Current challenges include formulating a cohesive standard for use and deployment of software services, computational resources for data and CPU/GPU capabilities, cloud clusters and machine learning software availability to implement ideas in high throughput data processing.
How to Bridge the Gap
- What are the tools, services and/or resources NDRIO should leverage to achieve your desired future state?
Development of tools and services for high performance computing, funding from government clusters and agencies for enabling research and development, support from commercial entities in achieving said capabilities, publications and conferences for organizing, indexing and making services available to the research communities.
- How do you see NDRIO’s role in addressing current gaps in the national DRI ecosystem?
- What other suggestions do you have?
NDRIO can facilitate communication for enabling research capabilities. NDRIO can hold conferences for formulating strategy and achieving goals in high throughput data processing and it can enable and promote development of machine learning and visuailzation tools and services for achieving researchers needs. Tools such as the Gbrain initiative from MNI can enhance existing capabilities and promote a cohesive exchange of ideas and projects with researchers locally and globally.