Neuronal data storage using document oriented databases

Abstract

Event Abstract Back to Event Neuronal data storage using document oriented databases Christian Garbers1, 2*, Christian Kellner1, 2, Lukasz Mokrzycki3 and Thomas Wachtler1, 2 1 Ludwig-Maximilians-Universität München, Department Biology II, Germany 2 German INCF Node, Germany 3 Jagiellonian University, Faculty of Mathematics and Computer Science, Poland The modern neurosciences produce increasingly large amounts of data - both from experiments and large scale simulations. While sharing of scientific data is common in other areas of biological sciences, the neurosciences are faced with barriers in data sharing. Furthermore, the information about how the data was acquired (the so called “metadata”) has the tendency to vanish with time. Often, it is the difficulty of finding and accessing the necessary information about the data, i.e., the metadata, that limits data sharing. Only well annotated data can be easily reused later. We present the NEuRonal Database (NERD), a project aiming to provide a database solution to the challenges of storing, retrieving, annotating and sharing of neuronal data. It smoothly integrates with the the data management framework of the German Neuroinformatics Node (G-Node, www.g-node.org) and is designed as an optional server side backend for the G-Node Data API. Instead of a standard relational database approach, NERD uses a document oriented data model and is intended to facilitate storage of large amounts of time series data, integrating and indexing corresponding meta information in the odML format [1]. In order to achieve quick searching on all levels of data annotation, NERD uses a bimodal approach towards data storage. The actual data are separated from the description of data structure and metadata, and both are stored differentially while keeping them tightly interlinked. By exploiting the main features of document oriented databases and combining them with the power of the HDF5 file format and distributed file systems, we provide a neat and scalable solution to the challenges of data management. Furthermore, the system accounts for the important requirement of versioning. NERD’s “give me my figures back” functionality keeps track of the history of changes to the data and enables going back to any previous version. Here we present a detailed sketch of the NERD architecture and give usage examples on how to store data with NERD using the G-Node-API. Furthermore, we present benchmark results demonstrating NERDs performance under various conditions. Acknowledgements Supported by the Federal Ministry of Education and Research (Grant 01GQ0801) References [1] Grewe J, Wachtler T, Benda J (2011) A bottom-up approach to data annotation in neurophysiology. Frontiers in Neuroinformatics 5:16. Keywords: database, Meta-Data Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012. Presentation Type: Poster Topic: Data analysis, machine learning, neuroinformatics Citation: Garbers C, Kellner C, Mokrzycki L and Wachtler T (2012). Neuronal data storage using document oriented databases. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00264 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 11 May 2012; Published Online: 12 Sep 2012. * Correspondence: Mr. Christian Garbers, Ludwig-Maximilians-Universität München, Department Biology II, Planegg-Martinsried, D-82152, Germany, garbers@biologie.uni-muenchen.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Christian Garbers Christian Kellner Lukasz Mokrzycki Thomas Wachtler Google Christian Garbers Christian Kellner Lukasz Mokrzycki Thomas Wachtler Google Scholar Christian Garbers Christian Kellner Lukasz Mokrzycki Thomas Wachtler PubMed Christian Garbers Christian Kellner Lukasz Mokrzycki Thomas Wachtler Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.