A framework for interoperability between models with hybrid tools.

IF 2.3 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Germán Braun, Pablo Rubén Fillottrani, C Maria Keet
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引用次数: 1

Abstract

Complex system development and maintenance face the challenge of dealing with different types of models due to language affordances, preferences, sizes, and so forth that involve interaction between users with different levels of proficiency. Current conceptual data modelling tools do not fully support these modes of working. It requires that the interaction between multiple models in multiple languages is clearly specified to ensure they keep their intended semantics, which is lacking in extant tools. The key objective is to devise a mechanism to support semantic interoperability in hybrid tools for multi-modal modelling in a plurality of paradigms, all within one system. We propose FaCIL, a framework for such hybrid modelling tools. We design and realise the framework FaCIL, which maps UML, ER and ORM2 into a common metamodel with rules that provide the central point for management among the models and that links to the formalisation and logic-based automated reasoning. FaCIL supports the ability to represent models in different formats while preserving their semantics, and several editing workflows are supported within the framework. It has a clear separation of concerns for typical conceptual modelling activities in an interoperable and extensible way. FaCIL structures and facilitates the interaction between visual and textual conceptual models, their formal specifications, and abstractions as well as tracking and propagating updates across all the representations. FaCIL is compared against the requirements, implemented in crowd 2.0, and assessed with a use case. The proof-of-concept implementation in the web-based modelling tool crowd 2.0 demonstrates its viability. The framework also meets the requirements and fully supports the use case.

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Abstract Image

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一个用于使用混合工具的模型之间互操作性的框架。
复杂的系统开发和维护面临着处理不同类型模型的挑战,这是由于语言的支持、偏好、大小等等,涉及到不同熟练程度的用户之间的交互。目前的概念性数据建模工具并不完全支持这些工作模式。它要求明确指定使用多种语言的多个模型之间的交互,以确保它们保持预期的语义,这是现有工具所缺乏的。关键目标是设计一种机制来支持混合工具中的语义互操作性,以便在多个范例中进行多模态建模,所有这些都在一个系统中。我们提出FaCIL,这种混合建模工具的框架。我们设计并实现了FaCIL框架,它将UML、ER和ORM2映射到一个具有规则的公共元模型中,该规则为模型之间的管理提供中心点,并链接到形式化和基于逻辑的自动推理。FaCIL支持在保留其语义的同时以不同格式表示模型的能力,并且在框架内支持几个编辑工作流。它以可互操作和可扩展的方式对典型的概念建模活动进行了清晰的关注点分离。FaCIL结构并促进了可视化和文本概念模型、它们的正式规范和抽象之间的交互,以及在所有表示中跟踪和传播更新。FaCIL与需求进行比较,在crowd 2.0中实现,并使用用例进行评估。基于web的建模工具crowd 2.0中的概念验证实现证明了它的可行性。该框架还满足需求并完全支持用例。
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来源期刊
Journal of Intelligent Information Systems
Journal of Intelligent Information Systems 工程技术-计算机:人工智能
CiteScore
7.20
自引率
11.80%
发文量
72
审稿时长
6-12 weeks
期刊介绍: The mission of the Journal of Intelligent Information Systems: Integrating Artifical Intelligence and Database Technologies is to foster and present research and development results focused on the integration of artificial intelligence and database technologies to create next generation information systems - Intelligent Information Systems. These new information systems embody knowledge that allows them to exhibit intelligent behavior, cooperate with users and other systems in problem solving, discovery, access, retrieval and manipulation of a wide variety of multimedia data and knowledge, and reason under uncertainty. Increasingly, knowledge-directed inference processes are being used to: discover knowledge from large data collections, provide cooperative support to users in complex query formulation and refinement, access, retrieve, store and manage large collections of multimedia data and knowledge, integrate information from multiple heterogeneous data and knowledge sources, and reason about information under uncertain conditions. Multimedia and hypermedia information systems now operate on a global scale over the Internet, and new tools and techniques are needed to manage these dynamic and evolving information spaces. The Journal of Intelligent Information Systems provides a forum wherein academics, researchers and practitioners may publish high-quality, original and state-of-the-art papers describing theoretical aspects, systems architectures, analysis and design tools and techniques, and implementation experiences in intelligent information systems. The categories of papers published by JIIS include: research papers, invited papters, meetings, workshop and conference annoucements and reports, survey and tutorial articles, and book reviews. Short articles describing open problems or their solutions are also welcome.
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