Using Metaneva for Structuring, Managing and Retrieving Animal Data in the Cognitive Neurosciences

Abstract

Contemporary cognitive neuroscience data sets are characterized by a lack of a standardized ontology, leading to shortcomings in data reports and data sharing along with possibly outdated modular models of functional brain mechanisms. Neuroinformatics is actively addressing these hiatuses, developing detailed and more powerful workbenches. However, the structuring of data is largely neglected due to the intrinsically different data sets in the neurosciences. Here we present a workbench called Metaneva addressing the need of data structures for the improvement of both data storage and data retrieval. We hereby present both our data structuring approach and the system developed specifically for the storage and retrieval of this Metaneva specific data structures.