These data must be effectively managed, processedand analyzed, all of which requires specialized resources and expertise that are all too oftenin short supply. Although many platforms have been built, most are available only to a subset of researchers, typically because they were designed to meet the needs of a particular research team, as opposed toatempting to service the broader research community.
We believe that the solution lies with an “informatics ecosystem”, in which sharing of developer and data science resources and open source development strategies are encouraged through mutually beneficial collaborations. Instead of trying to build “one size fits all” platforms, we make existing platforms interoperable, such that researchers can use the tools they want and it is the outputs that are federated.
Under our model, costs of software development and platform access are shared, and therefore reduced; the more collaborators who participate, the stronger and more cost effective the underlying platform becomes for everyone. And, since collaborators all usethe same interoperable architecture and processes, they can share and aggregate data between research programs with unprecedented ease.
Indoc Research leads the Indoc Consortium, a consortium of prominent data platform development teams. Shared vision, integrated personnel and standardized processes allow the Indoc Consortium partners to operate as a unified entity, thereby harnessing their collective capabilities while minimizing overhead and maximizing infrastructure investments.
The Indoc Consortium members include Indoc Research, the Centre for Advanced Computing (CAC) at Queen’s University, the Neuroimaging team from the Rotman Research Institute at Baycrest, and the Electronic Health and Information Laboratory (EHIL) at the Children's Hospital of Eastern Ontario. Capitalizing on each partner’s existing infrastructure, expertise and personnel, the Indoc Consortium is able to deliver a comprehensive, scalable and fully integrated package of research informatics solutions.
In partnership with the Ontario Brain Institute (OBI), the Indoc Consortium has developed Brain-CODE ( www.brain-code.ca), a data management and analytics platform that handles all research data collected in the OBI Integrated Discovery Programs.
Perhaps the most comprehensive and advanced application of the Ecosystem model is Brain-CODE, the Ontario Brain Institute's (OBI) extensible data management and analytics platform, which has been built and maintained by the Indoc Consortium.
Brain-CODE manages the clinical, molecular and imaging data from OBI’s large scale research programs in broad spectrum of CNS disorders:
Brain-CODE currently supports over 600 researchers and 100 research studies, and contains data from over 16,000 participants and 20,000 brain images.