PODD - Towards an Extensible, Domain-Agnostic Scientific Data Management System

Yuan-Fang Li, Gavin Kennedy, Faith Davies, J. Hunter
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引用次数: 11

Abstract

Data management has become a critical challenge faced by a wide array of scientific disciplines in which the provision of sound data management is pivotal to the achievements and impact of research projects. Massive and rapidly expanding amounts of data combined with data models that evolve over time contribute to making data management an increasingly challenging task that warrants a rethinking of its design. In this paper we present PODD, an ontology-centric architecture for data management systems that is extensible and domain independent. In this architecture, the behaviors of domain concepts and objects are captured entirely by ontological entities, around which all data management tasks are carried out. The open and semantic nature of ontology languages also makes PODD amenable to greater data reuse and interoperability. To evaluate the PODD architecture, we have applied it to the challenge of managing phenomics data.
面向可扩展的、领域不可知的科学数据管理系统
数据管理已成为众多科学学科面临的关键挑战,其中提供良好的数据管理对研究项目的成就和影响至关重要。随着时间的推移,大量且快速扩展的数据与数据模型相结合,使得数据管理成为一项越来越具有挑战性的任务,需要对其设计进行重新思考。在本文中,我们介绍了PODD,这是一种用于数据管理系统的以本体为中心的体系结构,可扩展且独立于域。在此体系结构中,领域概念和对象的行为完全由本体实体捕获,所有数据管理任务都围绕本体实体执行。本体语言的开放和语义特性还使PODD能够实现更好的数据重用和互操作性。为了评估PODD架构,我们将其应用于管理表型组学数据的挑战。
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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