Performance Evaluation of the Metadata-Driven MASi Research Data Management Repository Service

2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP) Pub Date : 2018-03-21 DOI:10.1109/PDP2018.2018.00059

Richard Grunzke, Volker Hartmann, T. Jejkal, H. Kollai, C. Dressler, Julia Dolhoff, Julia Stanek, H. Herold, A. Hoffmann, R. Müller-Pfefferkorn, Torsten Schrade, S. Herres‐Pawlis, G. Meinel, W. Nagel

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Abstract

Research data is increasingly important in order to gain insights from scientific data. To optimally foster this, the management of research data is required to be usable, customizable and fast. We enable this by building up the MASi research data management repository service, based on the KIT DM framework. The aim is on utilizing a single repository instance to serve multiple arbitrary community use cases. Due to their diverse data characteristics the performance of the MASi service has to be fitting across the different cases. We evaluate the performance along three initial heterogeneous use cases. Various aspects are investigated; First, the object insertion and query performance of the database along the object fill level. Second and third, the ingest and download performance of digital objects using real-life data sets. Highly favorable performance characteristics are shown.

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元数据驱动的MASi研究数据管理存储库服务的性能评价

为了从科学数据中获得见解，研究数据变得越来越重要。为了最佳地促进这一点，研究数据的管理需要是可用的、可定制的和快速的。我们通过构建基于KIT DM框架的MASi研究数据管理存储库服务来实现这一点。其目的是利用单个存储库实例来服务多个任意社区用例。由于不同的数据特征，MASi服务的性能必须适应不同的情况。我们根据三个初始异构用例评估性能。调查了各个方面;首先，沿着对象填充级别的数据库的对象插入和查询性能。第二和第三，使用真实数据集的数字对象的摄取和下载性能。显示出非常有利的性能特征。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)

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