OMNI: Towards a comprehensive object model for neuroinformatics

Stephen Larson (Whole Brain Project, UC San Diego), Sean Hill (INCF)

Due to the broad activities of the International Neuroinformatics Coordinating Facility across different areas of neuroinformatics, a clear need is emerging for a unifying object model.  Such an object model would allow programmatic interoperability between activities of recognized importance such as multi-scale modeling, digital atlasing, ontologies for neural structures, and standards for data sharing.  Specifically, a programmer should be able to access a single abstraction layer of objects through an application programming interface that can expose access to primary data, enable the computational analysis of this primary data, and facilitate the transformation of these data into derived objects that can be incorporated into models and simulations.

Because XML schema provides a useful programmatic foundation for an object model, we have aligned several XML schemas used by tools in the Neuroinformatics community such as NeuroML, the Whole Brain Catalog, WaxML (Digital Atlasing Infrastructure), the Connectome File Format, the CARMEN project’s Neurophysiology Data Translation Format, and the Extensible Neuroimaging Archive Toolkit.  While not yet an exhaustive set, alignment of these schemas reveal some of the challenges of creating a single unifying object model across neuroscience domains.

In addition to schema alignment, we have generated java classes from the aligned schemas and packaged them together with a Jython interpreter, transforming the aligned schemas into a set of objects that can be made available to both Java applications and Python scripts.  This methodology and an early version of the object model has been used recently in an example case study of neuroinformatics data integration to access, analyze, and transform neuronal morphologies segmented from the olfactory cortex of mouse (Ghosh et al., 2011).  We have made the project available online at


Ghosh, S., Larson, S. D., Hefzi, H., Marnoy, Z., Cutforth, T., Dokka, K., et al. (2011). Sensory maps in the olfactory cortex defined by long-range viral tracing of single neurons. Nature, 1-6. Nature Publishing Group. doi: 10.1038/nature09945.

Preferred presentation format: Poster
Topic: General neuroinformatics

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