Metadata and annotations for multi-scale electrophysiological data.
Metadata and annotations for multi-scale electrophysiological data.
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DOI：
10.1109/iembs.2009.5333570
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
Worrell GA
中科院分区：
文献类型：
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作者：
Bower MR;Stead M;Brinkmann BH;Dufendach K;Worrell GA
在癫痫术前评估期间，越来越多地使用多个电极进行高频（kHz）、长持续时间（天）颅内监测，产生了大量难以存储和维护的数据。这些大型数据集的描述性元数据和临床注释也对简单的（通常是手动的）数据分析方法提出了挑战。元数据和注释在程序之间的可靠通信、在长时间段内维护信息中的含义以及重新排序数据以进行分析的灵活性等问题对数据结构和算法提出了不同的要求。可以配置这些单独问题域（通信、存储和分析）的解决方案，以提供跨域的轻松转换和清晰度。多尺度注释格式（MAF）提供了一个集成的元数据和注释环境，最大限度地提高代码重用，最大限度地减少错误概率，并通过减少过度适应当前问题的信息技术解决方案的趋势来鼓励未来的更改。一个例子的图形实用程序生成和评估元数据和注释的“大数据”文件。
The increasing use of high-frequency (kHz), long-duration (days) intracranial monitoring from multiple electrodes during pre-surgical evaluation for epilepsy produces large amounts of data that are challenging to store and maintain. Descriptive metadata and clinical annotations of these large data sets also pose challenges to simple, often manual, methods of data analysis. The problems of reliable communication of metadata and annotations between programs, the maintenance of the meanings within that information over long time periods, and the flexibility to re-sort data for analysis place differing demands on data structures and algorithms. Solutions to these individual problem domains (communication, storage and analysis) can be configured to provide easy translation and clarity across the domains. The Multi-scale Annotation Format (MAF) provides an integrated metadata and annotation environment that maximizes code reuse, minimizes error probability and encourages future changes by reducing the tendency to over-fit information technology solutions to current problems. An example of a graphical utility for generating and evaluating metadata and annotations for “big data” files is presented.