By George Komatsoulis, Ph.D.
The Commons is a shared virtual space that exploits new computing models to be scalable, cost effective and simplify sharing with the objective of making the digital artifacts of biomedical research FAIR: Findable, Accessible, Interoperable, and Reusable. A successful Commons is not a unitary information system, rather, it is the sum of the infrastructure that supports it, the data that resides in it, and the services and tools that let investigators find, access, and derive knowledge from it. Over the last two years, the NIH Office of the Associate Director for Data Science (ADDS) has been working to make the Commons a reality through the Big Data to Knowledge (BD2K) program and other activities with many of the nation’s biomedical informatics professionals. The Commons Credits Model is one element of these activities and is focused on creating a part of the infrastructure of the Commons by simplifying access to one of the key technologies that underpin the Commons, cloud computing.
The Commons Credits Model is a new strategy for providing researchers access to cloud computing technologies that is predicated on creating a competitive marketplace for biomedically useful information technology services. The premise of the Credits Model is quite straightforward: investigators apply for and receive dollar denominated vouchers (“commons credits”) that can be used to purchase cloud computing resources from vendors that have met NIH standards for participation in the Commons (“conformant providers”). By distributing these credits to investigators, rather than directly to vendors, we align market forces for maximum efficiency: investigators are incentivized to use the vendor that provides the best value for their particular research need; vendors are incentivized to compete for investigator’s business by providing the best possible services at the lowest possible cost. Further, since vendors could provide Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and/or Software as a Service (SaaS), we hope to provide capabilities that can be useful to a broad range of researchers with different levels of sophistication in the area of cloud computing (or computing in general).
About a year ago, NIH ADDS began a three year pilot to test the Commons Credits Model. The pilot is being implemented via a contract to the CMS Alliance to Modernize Healthcare (CAMH) Federally Funded Research and Development Center (FFRDC). FFRDC’s are special purpose entities that are government owned, but contractor managed, that exist to meet special research and development needs that can’t be well managed by traditional grants and contracts. During the past year, the FFRDC team has been working with the ADDS Office to arrange the preliminary steps needed to open the credit program. This includes working with potential providers and investigators to define a set of conformance requirements and a process for vetting provider conformance, setting up a portal to enable investigators to apply for credits, defining the triage and evaluation criteria for making credit distribution decisions, and working through the financial mechanism to award credits.
I am pleased, therefore, to report that we have made excellent progress toward fully implementing the program. We have two fully conformant vendors (DLT, a reseller of Amazon Web Services, and IBM) that have fully executed the participation agreement with the CAMH FFRDC that enables them to accept credits. We have received another 10 applications, of which 5 have been certified as compliant with NIH requirements, but are still negotiating various aspects of the participation agreement required to accept credits. In addition, we have issued the first batch of credits to a test group of Commons investigators who are assisting us by critiquing the portal and processes as well as uncovering potential problems with the distribution and use of credits. Once we have resolved the issues reported by this initial group of investigators, the program will be opened to all NIH investigators. Announcements will be made via the ADDS Office program web page (https://datascience.nih.gov/) by the end of this year or in January 2017.