Access to Computational Resources and Expertise
Access and degree of services provided by a computer science department and/or data science center at the investigator’s institution.
Best Practices:
- Look to campus high-performance computing resources as a first start, if available.
- If not, look to the Computer Science department for cloud-based computing courses.
- Understand how others in the same field of research use cloud-based computing, and leverage their experience whenever possible.
- Participate in training courses for neuroscience data in the cCoud.
- Work with the Cloud vendor to understand options, costs, and programs to support your work.
Things to Avoid:
- Do not assume you know what resources are available without checking. You need to do due diligence to check on resources.
- Do not be limited by the computing power of your laptop. There are many resources that will get you computing for free or a low cost.
- Do not invest in solutions that do not have a clear track record and evidence of some longevity.
Value Set Definitions:
- Low: Researcher has access to few institutional resources. Researchers who would label themselves as low on this dimension should consider carefully whether they have the time and resources needed to develop the necessary expertise in order to use cloud-based resources for their projects.
- Mixed: Good neuroimaging expertise, but little institutional computer or data science support; or good computational expertise and resources but little neuroimaging expertise.
- High: Good neuroimaging expertise and strong institutional computer and data science support using Cloud Computing.
Value of Use Case Example:
Mixed - Jordan’s institute has a high-performance computing center for use by investigators with expertise in using containerized (i.e., pre-packaged) computing tools, and a data science center with “cloud office hours”, i.e., a dedicated help resource that can answer her questions about using the Cloud. Further, there is at least one investigator in another department that regularly uses cloud-based computing resources. However, no one in Jordan’s department does so. Jordan’s institution has been involved in a number of large-scale clinical studies that involved data sharing of clinical data, but has not done so with neuroimaging data in previous studies.
Discussion of Use Case:
Based on the resources available to Jordan, she should reach out to colleagues with specific expertise in cloud-based neuroimaging or consider taking a training course that provides training in cloud-based use of neuroimaging tools.
See Also:
- NeuroHackacademy: Summer school in neuroimaging and data science
- CloudBank: A cloud access entity that will help the NSF-supported computer science community access and use public clouds for research and education by delivering a set of managed services designed to simplify access to public clouds. Educational and training materials are available to all.
- STRIDES: NIH program that includes educational materials, training opportunities and other resources
- Neuroimaging Informatics Tools and Resources Collaboratory Computational Environment (NITRC-CE): NITRC-CE is an on-demand, virtual computing platform designed for neuroimaging researchers, incorporating many neuroimaging tools, and deployable on the Amazon Web Services (AWS) Elastic Cloud Computing (EC2) environment. The User Guide provides detailed instructions for using the NITRC-CE for cloud computing.
- Jetstream Cloud Resources: NSF-supported project led by the Indiana University Pervasive Technology Institute (PTI) designed for those who have not previously used high performance computing and software resources. The system is particularly geared toward 21st-century workforce development at small colleges and universities – especially historically black colleges and universities, minority serving institutions, tribal colleges, and higher education institutions in EPSCoR States.
- Cloud Carpentry for Genomics:on-line course materials for a Data Carpentry course providing practical training in understanding and using the Cloud for analysis
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