Neuroinformatics is an essential aspect of Blue Brain’s methodology and provides a fundamental data management structure and set of activities by which Blue Brain operates. Blue Brain Nexus has been built by the Blue Brain Project to organize, store and process exceptionally large volumes of data and support usage by a broad number of users.
Blue Brain Nexus is a provenance based, semantic enabled data and knowledge graph management platform enabling the definition of an arbitrary domain of applications for which there is a need to create and manage entities as well as their relations (e.g. provenance). Blue Brain Nexus is instrumental in supporting all stages of Blue Brain’s data-driven modelling cycle including, but not limited to experimental data, single cell models, circuits, simulations and validations.
Various types of data (e.g. electrophysiology recordings, morphologies, ion channel properties, parameters, single cell models, circuits, simulation) which are collected in the data acquisition phase are stored by the Blue Brain’s central neuroinformatics infrastructure powered by Blue Brain Nexus. Data curation in Blue Brain Nexus may take a variety of forms including data registration into brain atlases, integration of specialized data repositories and scientific manuscripts. From Blue Brain Nexus, they can be searched, downloaded for analysis or automatically incorporated in Blue Brain’s reconstructions and simulations. This approach requires adherence to the FAIR (Findable, Accessible, Interoperable and Reusable) data principles.
A great advantage of Blue Brain Nexus is its ability to enable scientific process automation, offering machine-readable data and automatic data integration. Already there are over 400,000 data items in Blue Brain Nexus with great heterogeneity and all are machine accessible.
Building and using Knowledge Graphs from heterogenous sources, brain regions and formats often require many components ranging from data transformations (e.g ETL), ontologies and schemas (e.g brain regions and cell types ontologies) defining the targeted domain, scalable stores for managing the resulting graph, as well as data and factual knowledge search and access. While many systems and tools that implement these components exist separately, they often come with a high level of complexity when dealing with data, ontologies and schemas.
To make building and using Knowledge Graphs simpler, the Blue Brain team has open sourced Blue Brain Nexus Forge– enabling data scientists, data and knowledge engineers to uniquely combine these components under a consistent, single and generic Python Framework. With Blue Brain Nexus Forge, non-expert users can build and use Knowledge Graphs to: