Abstract JSON

The current json format:

    {
        "correspondence": [
            "sobolev.andrey@gmail.com"
        ], 
        "topic": "Neural encoding and decoding", 
        "doi": "10.12751/test.3", 
        "title": "Web Data Storage for Management and Sharing of Neuroscience Data", 
        "abstract": "Recent advancements in technology and methodology enable scientists to produce growing amounts of increasingly complex data recorded from many species, modalities, and levels of study. Annotation and organization of these data has become a challenging task, which is not only important for the interpretability and reproducibility of results and analyses, but also essential for collaboration and data sharing. In order to address these issues, the German INCF Node (G-Node) is developing software solutions consisting of several services and tools for experimental neuroscientists, focusing on online data access and organization of electrophysiological data. The core of this project is a web service representing a centralized data storage system that provides functions for upload, search, and management of data and metadata [1]. The principal design goal of this service was to improve the experimental workflow and to unify data access from different locations and platforms. Libraries and client programs provide the full functionality while allowing the scientist to use this service either directly through a web page or from his or her preferred working environment. This includes a toolbox for the popular numeric computing environment Matlab and a library for the programming language Python. The software supports various techniques and standards used in the field for data analysis and management, including common data objects for neurophysiology data [2], access to various file formats [3], and data annotation [4]. The service provides powerful search capabilities, implements a versioning system for all stored data objects and allows fine-grained sharing of data from whole datasets down to single signals and files, thus facilitating data management and collaborative research.", 
        "figid": 231, 
        "coi": "The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\n", 
        "frontsubid": "231", 
        "nfigures": 0, 
        "imagefile": "", 
        "affiliations": [
            {
                "index": "1", 
                "address": "Department Biology II, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Germany"
            }
        ], 
        "state": "accepted", 
        "session": "Poster", 
        "caption": "", 
        "authors": [
            {
                "epithet": "1", 
                "name": "Andrey Sobolev"
            }, 
            {
                "epithet": "1", 
                "name": "Adrian Stoewer"
            }, 
            {
                "epithet": "1", 
                "name": "Aljoscha Leonhardt"
            }, 
            {
                "epithet": "1", 
                "name": "Philipp Rautenberg"
            }, 
            {
                "epithet": "1", 
                "name": "Christian Kellner"
            }, 
            {
                "epithet": "1", 
                "name": "Christian Garbers"
            }, 
            {
                "epithet": "1", 
                "name": "Andreas Herz"
            }, 
            {
                "epithet": "1", 
                "name": "Thomas Wachtler"
            }
        ], 
        "submitter": [
            "Andrey Sobolev"
        ], 
        "frontid": "231", 
        "acknowledgements": "Supported by the Federal Ministry of Education and Research (Grant 01GQ0801).", 
        "id": 196710, 
        "refs": "[1] G-Node Repository (http://g-node.github.com)\n[2] NEO I/O (http://neuralensemble.org/neo)\n[3] Neuroshare (https://github.com/G-Node/python-neuroshare)\n[4] Grewe J, Wachtler T, Benda J (2011). A bottom-up approach to data annotation in neurophysiology. Front. Neuroinform. 5:16. doi: 10.3389/fninf.2011.00016", 
    }