Blue Brain Nexus - A knowledge graph for data-driven science
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bogdanromanx Revamped Nexus documentation for v1 (#123)
* Initial documentation structure

* Added minikube install instructions

* Corrected the minikube assets base

* Added wait for pods ready in between deployments

* Added missing kafka example, minor tweaks

* Running with Docker

* Replaced <mark> with bold

* Updated getting-started page names

* Added on premise instructions for dependent services

* Added the static schemas and contexts

* Added API docs on KG and ADMIN operations

* Updated material theme fixes bug

* Updated paradox version

* Add Web Apps standards page (#4)

* Updated build for automatic publishing to gh-pages

Additional fixes:
* removed duplicate software description from README.md
* minor formatting of markdown sources
* updated sbt to 1.2.4
Latest commit 2fa7c9b Oct 12, 2018

README.md

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Blue Brain Nexus - A knowledge graph for data-driven science

The Blue Brain Nexus is a provenance based, semantic enabled data management platform enabling the definition of an arbitrary domain of application for which there is a need to create and manage entities as well as their relations (e.g. provenance). For example, the domain of application managed by the Nexus platform deployed at Blue Brain is to digitally reconstruct and simulate the brain.

At the heart of the Blue Brain Nexus platform lies the Knowledge Graph, at Blue Brain, it will allow scientists to:

  1. Register and manage neuroscience relevant entity types through schemas that can reuse or extend community defined schemas (e.g. schema.org, bioschema.org, W3C-PROV) and ontologies (e.g. brain parcellation schemes, cell types, taxonomy).

  2. Submit data to the platform and describe their provenance using the W3C PROV model. Provenance is about how data or things are generated (e.g. protocols, methods used...), when (e.g. timeline) and by whom (e.g. people, software...). Provenance supports the data reliability and quality assessment as well as enables workflow reproducibility. Platform users can submit data either through web forms or programmatic interfaces.

  3. Search, discover, reuse and derive high-quality neuroscience data generated within and outside the platform for the purpose of driving their own scientific endeavours. Data can be examined by species, contributing laboratory, methodology, brain region, and data type, thereby allowing functionality not currently available elsewhere. The data are predominantly organized into atlases (e.g. Allen CCF, Waxholm) and linked to the KnowledgeSpace – a collaborative community-based encyclopedia linking brain research concepts to the latest data, models and literature.

It is to be noted that many other scientific fields (Astronomy, Agriculture, Bioinformatics, Pharmaceutical industry, ...) are in need of such a technology. Consequently, Blue Brain Nexus core technology is being developed to be agnostic of the domain it might be applied to.

More information

The Blue Brain Nexus documentation offers more information about the software, its architecture, an api reference and the current roadmap.

Please head over to the getting started section for a description of various options on running Nexus and introductory material to Linked Data and the Shapes Constraint Language.

For more details, you can talk with the development team directly on Gitter.