NeuroLex.org: Integrating a community-driven neuroscience ontology with the web of linked data

How many different kinds of cholinergic neurons are known to exist?  How many atlas-related resources exist in neuroscience?  NeuroLex.org, a project of the Neuroscience Information Framework (NIF), is a semantic mediawiki-based website that tracks and maintains a collaboratively edited ontology to keep track of the answers to these questions and more. Here we describe the work which connects this ontology with the growing web of Linked Data (Bizer, Heath, & Berners-Lee, 2009).

Building on an initial set of neuroscience ontology terms, imported from the NIFSTD (Bug et al. 2008), we have populated NeuroLex with pages describing NIF Registry content. This includes federated resources that have been annotated with ontology terms, enabling content-based search and analysis across these resources.  The NeuroLex is now a core component of the NIF search engine, serving as the default landing site for simple searches containing known terms in the lexicon, and linking out to the NIF resources via the “NIF Navigator”, an interface element that lists available resources by category type (Akil, Martone & Van Essen, 2011).   

From its inception, machine-readable NeuroLex content was available via comma separated files from the site directly.  Recently, NeuroLex has exposed its entire content to the web in the RDF format, as an hourly-updated rdf file, and as a Pubby web interface on top of a Talis n2 triple store (more info: http://j.mp/dNqjQn). This follows the recommendations of the Linked Data Consortium (Heath & Bizer, 2011).

This means of exposure has led to a set of tools & technologies utilizing the NeuroLex ontologies, such as the Web Image Browser (more info: http://j.mp/h9One7), an iMod plugin for naming segmented images (more info: http://j.mp/eZ6Xon), a project working to expose the connections between brain regions and nerve cells called the Multi-Scale Connectome Browser (http://connectomebrowser.org) and NeuroML, a growing standard in neural system simulations (more info: http://j.mp/gQVXfE).   

In addition, NeuroLex has been integrating its set of terms that span areas of neuroscience with established resources such as the Gene Ontology Consortium’s Cell Ontology (Bard, Rhee & Ashburner, 2005), and USC’s Brain Architecture Management System (Bota, Dong, & Swanson 2005).  

In the last year, NeuroLex has seen its average traffic grow three-fold, 80% of which is driven purely by users driven to the site via Google searches.  To this end, NeuroLex is continuing to serve as a useful rallying point for reconciling ambiguity in neuroinformatics.


References

Akil, H., Martone, M. E., & Van Essen, D. C. (2011). Challenges and Opportunities in Mining Neuroscience Data. Science, 331(6018), 708-712. doi: 10.1126/science.1199305.

Bard, J., Rhee, S. Y., & Ashburner, M. (2005). An ontology for cell types. Genome biology, 6(2), R21. doi: 10.1186/gb-2005-6-2-r21.

Bizer, C., Heath, T., & Berners-Lee, T. (2009). Linked Data - The Story So Far. International Journal on Semantic Web and Information Systems, 5(3), 1-22. Igi Publ. doi: 10.4018/jswis.2009081901.

Bota, M., Dong, H.-W., & Swanson, L. W. (2005). Brain architecture management system. Neuroinformatics, 3(1), 15-48. doi: 10.1385/NI:3:1:015.

Bug, W. J., Ascoli, G. a, Grethe, J. S., Gupta, A., Fennema-Notestine, C., Laird, A. R., et al. (2008). The NIFSTD and BIRNLex vocabularies: building comprehensive ontologies for neuroscience. Neuroinformatics, 6(3), 175-94. doi: 10.1007/s12021-008-9032-z.

Heath, T., Bizer, C. (2011) Linked Data: Evolving the Web into a Global Data Space (1st edition). Synthesis Lectures on the Semantic Web: Theory and Technology, 1:1, 1-136. Morgan & Claypool.

Yarkoni, T., Poldrack, R. a, Van Essen, D. C., & Wager, T. D. (2010). Cognitive neuroscience 2.0: building a cumulative science of human brain function. Trends in Cognitive Sciences, 14(11), 489-496. Elsevier Ltd. doi: 10.1016/j.tics.2010.08.004.