OMNI: Towards a comprehensive object model for neuroinformatics

Abstract

Event Abstract Back to Event OMNI: Towards a comprehensive object model for neuroinformatics Stephen Larson1* and Sean Hill2 1 University of California, San Diego, Whole Brain Project, United States 2 INCF, Sweden 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 http://incf-omni.googlecode.com References 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. Keywords: General neuroinformatics, Neuroimaging Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011. Presentation Type: Poster Presentation Topic: General neuroinformatics Citation: Larson S and Hill S (2011). OMNI: Towards a comprehensive object model for neuroinformatics. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00136 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 17 Oct 2011; Published Online: 19 Oct 2011. * Correspondence: Dr. Stephen Larson, University of California, San Diego, Whole Brain Project, San Diego, United States, stephen.larson@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Stephen Larson Sean Hill Google Stephen Larson Sean Hill Google Scholar Stephen Larson Sean Hill PubMed Stephen Larson Sean Hill Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.