Arkheia: Data Management and Communication for Open Computational Neuroscience - Antolík, Ján; Davison, Andrew P. (Frontiers in Neuroinformatics, 2018)
Two trends have been unfolding in computational neuroscience during the last decade. First, a shift of focus to increasingly complex and heterogeneous neural network models, with a concomitant increase in the level of collaboration within the field (whether direct or in the form of building on top of existing tools and results). Second, a general trend in science towards more open communication, both internally, with other potential scientific collaborators, and externally, with the wider public. This multi-faceted development towards more integrative approaches and more intense communication within and outside of the field poses major new challenges for modellers, as currently there is a severe lack of tools to help with automatic communication and sharing of all aspects of a simulation workflow to the rest of the community. To address this important gap in the current computational modeling software infrastructure, here we introduce Arkheia. Arkheia is a web-based open science platform for computational models in systems neuroscience. It provides an automatic, interactive, graphical presentation of simulation results, experimental protocols, and interactive exploration of parameter searches, in a web browser-based application. Arkheia is focused on automatic presentation of these resources with minimal manual input from users. Arkheia is written in a modular fashion with a focus on future development of the platform. The platform is designed in an open manner, with a clearly defined and separated API for database access, so that any project can write its own backend translating its data into the Arkheia database format. Arkheia is not a centralized platform, but allows any user (or group of users) to set up their own repository, either for public access by the general population, or locally for internal use. Overall, Arkheia provides users with an automatic means to communicate information about not only their models but also individual simulation results and the entire experimental context in an approachable graphical manner, thus facilitating the user’s ability to collaborate in the field and outreach to a wider audience.