Scalable Enterprise Systems Phase II:Exploratory Research on Flexible Production Networks: SEEK - Scalable Extraction of Enterprise Knowledge

可扩展的企业系统第二阶段：柔性生产网络的探索性研究：SEEK - 可扩展的企业知识提取

• 批准号: 0122193
• 负责人: Joachim Hammer
• 金额: --
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0122193&HistoricalAwards=false
• 关键词: Scalable; Enterprise; Systems; Phase; II

ABSTRACTProposal: CMS-0122193PI: Joachim Hammer Institution: University of FloridaDate: July 21, 2001ABSTRACT CMS0122193 - "Flexible Production Networks Phase II: SEEK - Scalable Extraction of Enterprise Knowledge"This grant provides funding to support development of new theory and technologies to allow the seamless, rapid interconnection of diverse legacy systems with enterprise decision support tools to allow extraction of data and knowledge across those legacy systems. Such a capability is critically important to allow rapid configuration of computing systems that support extended enterprise collaboration. The application domain is the flexible production network. Flexible production networks (FPNs) consist of firms that operate in a project oriented, customized production environment. Most construction (totaling approximately 8% of GNP) and growing parts of manufacturing industry operate in this form. Characterized by rapid assembly and disassembly of business networks based on project needs, FPNs are particularly well-suited users for the proposed research.We call our technology SEEK - Scalable Extraction of Enterprise Knowledge. Knowledge extraction is difficult because data resident in the firm does not map directly to the input needed by a decision support system. Existing approaches do not support SEEK's fundamental capabilities: (1) rapid connection to legacy data and applications with little programmatic setup; and (2) linking source knowledge with decision support tools not natively available to the source. Our novel approach to provide these capabilities is to use encoded domain knowledge about the types of information that would be stored in applications to enable semiautomatic connection to those applications. Our approach is application independent, supporting extraction of legacy data from both structured and unstructured sources. This approach is inherently more scalable and robust than building application specific tools. Successful conclusion of our research will significantly increase the speed and reduce the amount of human input necessary to instantiate an extended enterprise computing platform with heterogeneous sources.

摘要提案：CMS-0122193PI：Joachim Hammer 机构：佛罗里达大学日期：2001 年 7 月 21 日摘要 CMS0122193 - “灵活生产网络第二阶段：SEEK - 可扩展的企业知识提取”这项拨款提供资金支持新理论和技术的开发，以允许各种遗留系统与企业决策支持工具无缝、快速互连，从而允许提取数据 以及跨这些遗留系统的知识。这种能力对于快速配置支持扩展企业协作的计算系统至关重要。应用领域是柔性生产网络。灵活生产网络 (FPN) 由在面向项目的定制生产环境中运营的公司组成。大多数建筑业（总计约占国民生产总值的 8%）和制造业的增长部分都以这种形式运营。 FPN 的特点是根据项目需求快速组装和拆卸业务网络，特别适合拟议研究的用户。我们将我们的技术称为 SEEK - 可扩展的企业知识提取。知识提取很困难，因为公司中的数据不能直接映射到决策支持系统所需的输入。现有方法不支持 SEEK 的基本功能：(1) 快速连接到遗留数据和应用程序，几乎不需要编程设置； (2) 将源知识与源本身不可用的决策支持工具联系起来。我们提供这些功能的新颖方法是使用有关存储在应用程序中的信息类型的编码领域知识，以实现与这些应用程序的半自动连接。我们的方法独立于应用程序，支持从结构化和非结构化源中提取遗留数据。这种方法本质上比构建特定于应用程序的工具更具可扩展性和鲁棒性。我们研究的成功结论将显着提高实例化具有异构源的扩展企业计算平台所需的速度并减少所需的人力输入量。