TY - JOUR T1 - The SONATA Data Format for Efficient Description of Large-Scale Network Models JF - bioRxiv DO - 10.1101/625491 SP - 625491 AU - Kael Dai AU - Juan Hernando AU - Yazan N. Billeh AU - Sergey L. Gratiy AU - Judit Planas AU - Andrew P. Davison AU - Salvador Dura-Bernal AU - Padraig Gleeson AU - Adrien Devresse AU - Michael Gevaert AU - James G. King AU - Werner A. H. Van Geit AU - Arseny V. Povolotsky AU - Eilif Muller AU - Jean-Denis Courcol AU - Anton Arkhipov Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/05/02/625491.abstract N2 - Increasing availability of comprehensive experimental datasets in neuroscience and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational network models. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. We provide reference Application Programming Interfaces and model examples to catalyze support and adoption of the format. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility. ER -