An Ontological Approach to the Development of Analytical Platform Language Toolkits

L. Lyadova, N. Suvorov, V. Zayakin, E. Zamyatina
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引用次数: 2

Abstract

The development of complex software systems is impossible without using modern modeling tools. At the design process, various models are developed: when solving each task, the attributes of processes and systems, which are significant for solving this task, are to be presented in the model. Developing analytical systems for data-intensive areas has specifics, which determine new requirements for the system functionality and architecture (interoperability, adaptability, etc.). These requirements can be implemented in the system based on a combination of two approaches: knowledge-driven development and model-driven development. This article presents an approach to creating a knowledge-driven analytical platforms, which integrate language toolkits allowing to create "on the fly" new domain-specific languages (DSLs). DSLs provide "user interfaces" which are customizable to the specifics of the tasks, solved by users with modeling tools, and to the corresponding users' domains. The architecture of the analytical platform, the graph model, and the metalanguage which are the basis of the language toolkits implementation are described in the paper. The multifaceted ontology, which is the core of the analytical platform, is presented too.
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分析平台语言工具箱开发的本体论方法
不使用现代建模工具,复杂软件系统的开发是不可能的。在设计过程中,开发各种模型:在解决每个任务时,将对解决该任务有重要意义的过程和系统的属性呈现在模型中。为数据密集型领域开发分析系统具有特殊性,这决定了系统功能和体系结构(互操作性、适应性等)的新需求。这些需求可以基于两种方法的组合在系统中实现:知识驱动的开发和模型驱动的开发。本文提出了一种创建知识驱动的分析平台的方法,它集成了允许创建“动态”的新领域特定语言(dsl)的语言工具包。dsl提供了“用户界面”,可以根据任务的具体情况定制,由用户使用建模工具解决,并针对相应的用户域。本文描述了分析平台的体系结构、图模型和元语言,它们是语言工具包实现的基础。提出了作为分析平台核心的多面本体。
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