摘要翻译：
需求波动性通常是软件工程中的一个问题，特别是在基于Web的临床应用中，它通常源于对感兴趣领域的不完全知识。随着健康科学的进步，许多特性和功能需要添加到生物医学领域的现有软件应用程序中，或从现有软件应用程序中删除。同时，生物医学系统日益复杂，使其更加难以理解，从而更难定义其需求，这在很大程度上加剧了其波动性。本文提出了一个基于本体驱动的实验室信息管理系统(LIMS)中的一种新的基于Agent的方法来分析和管理易变和动态的需求，该系统是为医学真菌学中基于Web的病例报告而设计的。该框架采用本体赋权，并使用范畴理论进行形式化，以提供对功能和非功能需求层次及其相互关系的深入和共同理解，并跟踪变化对概念框架的影响。
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英文标题：
《Managing Requirement Volatility in an Ontology-Driven Clinical LIMS
  Using Category Theory. International Journal of Telemedicine and Applications》
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作者：
Arash Shaban-Nejad, Olga Ormandjieva, Mohamad Kassab, Volker Haarslev
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最新提交年份：
2009
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Multiagent Systems        多智能体系统
分类描述：Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
涵盖多Agent系统、分布式人工智能、智能Agent、协调交互。和实际应用。大致涵盖ACM科目I.2.11类。
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英文摘要：
  Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.
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PDF链接：
https://arxiv.org/pdf/0906.1842