The underlying idea of this project is to develop linked data ontologies for given scientific domains and map data from sources into those representations based on the DIG toolset (http://dig.isi.edu).
Our first area of exploration are Neuroscience Domain Insight Graphs (neuDIGs) to serve the needs if systems-level neuroscience: an advanced, complex scientific subject. We intend this work to provide a large-scale, practical, common representation for neuroscientific knowledge that are primarily concerned with properties and characteristics of neuron populations that may (or may not) be explicitly identified by name.
This repository houses the neuDIGs ontology, linked data sets that conform to it, tooling, documentation and reasoning/modeling/inference systems. It is an interpretive model (see Burns & Chalupsky (2014) "It's all Made Up" AAAI Workshop on Discovery Informatics) and is intended to be lightweight, practical representation linked data for neuroscience.