首页> 外文期刊>Wirtschaftsinformatik >Enriching Linked Data with Semantics from Domain-Specific Diagrammatic Models
【24h】

Enriching Linked Data with Semantics from Domain-Specific Diagrammatic Models

机译:从领域特定的图表模型中利用语义丰富链接数据

获取原文
获取原文并翻译 | 示例
       

摘要

One key driver of the Linked Data paradigm is the ability to lift data graphs from legacy systems by employing various adapters and RDFizers (e.g., D2RQ for relational databases, XLWrap for spreadsheets). Such approaches aim towards removing boundaries of enterprise data silos by opening them to cross-organizational linking within a "Web of Data". An insufficiently tapped source of machine-readable semantics is the underlying graph nature of diagrammatic conceptual models - a kind of information that is richer compared to what is typically lifted from table schemata, especially when a domain-specific modeling language is employed. The paper advocates an approach to Linked Data enrichment based on a diagrammatic model RDFizer originally developed in the context of the ComVantage FP7 research project. A minimal but illustrative example is provided from which arguments will be generalized, leading to a proposed vision of "conceptual model "-aware information systems.
机译:链接数据范式的一个主要推动力是能够通过使用各种适配器和RDFizer(例如,用于关系数据库的D2RQ,用于电子表格的XLWrap)从旧系统中提取数据图的能力。此类方法旨在通过开放企业数据孤岛的边界以在“数据网络”内进行跨组织链接来消除它们。未被充分利用的机器可读语义资源是图解概念模型的基础图形性质-与通常从表纲要中提炼的信息相比,这种信息要丰富得多,尤其是在使用领域特定的建模语言时。本文提出了一种基于最初在ComVantage FP7研究项目的背景下开发的图解模型RDFizer的链接数据丰富方法。提供了一个最小但说明性的示例,通过该示例可以概括各种论点,从而实现对“概念模型”的感知信息系统的拟议构想。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号