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         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/2645c97554bcfc72bac8aacda74218dd3/diglezakis",         
         "tags" : [
            "framework","forschungsdaten","engineering","largeData"
         ],
         
         "intraHash" : "645c97554bcfc72bac8aacda74218dd3",
         "interHash" : "6a797a7ed8f41a24ca0dfcffa047aa53",
         "label" : "signac - A Simple Data Management Framework",
         "user" : "diglezakis",
         "description" : "[1611.03543] signac - A Simple Data Management Framework",
         "date" : "2017-09-05 11:25:43",
         "changeDate" : "2017-09-05 09:25:43",
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         "pub-type": "misc",
         
         "year": "2016", 
         "url": "http://arxiv.org/abs/1611.03543", 
         
         "author": [ 
            "Carl S. Adorf","Paul M. Dodd","Sharon C. Glotzer"
         ],
         "authors": [
         	
            	{"first" : "Carl S.",	"last" : "Adorf"},
            	{"first" : "Paul M.",	"last" : "Dodd"},
            	{"first" : "Sharon C.",	"last" : "Glotzer"}
         ],
         "note": "cite arxiv:1611.03543Comment: 14 pages, 6 figures","abstract": "Researchers in the field of computational physics, chemistry, and materials\r\nscience are regularly posed with the challenge of managing large and\r\nheterogeneous data spaces. The amount of data increases in lockstep with\r\ncomputational efficiency multiplied by the amount of available computational\r\nresources, which shifts the bottleneck within the scientific process from data\r\nacquisition to data post-processing and analysis. We present a framework\r\ndesigned to aid in the integration of various specialized data formats, tools\r\nand workflows. The signac framework provides all basic components required to\r\ncreate a well-defined and thus collectively accessible data space, simplifying\r\ndata access and modification through a homogeneous data interface, largely\r\nagnostic of the data source, i.e., computation or experiment. The framework's\r\ndata model is designed not to require absolute commitment to the presented\r\nimplementation, simplifying adaption into existing data sets and workflows.\r\nThis approach not only increases the efficiency with which scientific results\r\ncan be produced, but also significantly lowers barriers for collaborations\r\nrequiring shared data access.",
         "bibtexKey": "adorf2016signac"

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