One of the earliest success stories in the sharing of neuroscience data is NeuroMorpho.Org, a free public repository of neuronal reconstructions. These reconstructions are three-dimensional computerized tracings of nerve cells that capture the structural detail underlying brain connectivity and signal processing. After 11 years of operation, NeuroMorpho.Org hosts over 70K reconstructions contributed by hundreds of laboratories worldwide. Each neuron deposited is the result of many hours of skilled labor involving sophisticated experiments performed in vitro, in vivo, or from live imaging of a behaving animal.
As data continues to accumulate from dozens of different animal species, anatomical regions, neuron types, experimental conditions, and technical approaches, the challenge is progressively transitioning from data production to data access. The authors of this study engineered OntoSearch, a smart solution to find and download neuronal reconstructions from NeuroMorpho.Org based on conceptual hierarchies harnessed from evolving neuroscience knowledge. This required the re-organization of neuronal metadata into machine-readable ontologies encompassing animal taxonomies, brain region parcelations, and cellular lineages across morphological, functional, and molecular dimensions.
This new search capability serves the end users through hierarachical reasoning and simple ergonomics. Simple keyword queries retrieve matching data as well as possible hits by crawling each available hierarchy upward (generalization), downward (specialization), and laterally (implication); meanwhile, auto-completion assists the search powered by controlled vocabularies. At every new data release, the corresponding metadata are ingested to keep OntoSearch updated. The hierarchies are also shared publicly to facilitate extensions and reuse in other projects.
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