4D-SETL - A Semantic Data Integration Framework
4D-SETL - A Semantic Data Integration Framework
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DOI：
10.5220/0005822501270134
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发表时间：
2016-04
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影响因子：
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通讯作者：
Sergio de Cesare;George Foy;M. Lycett
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文献类型：
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作者：
Sergio de Cesare;George Foy;M. Lycett
尽管基础本体已成功用作许多大型政府和能源行业项目的基础，但尚未在主流企业系统（ES）数据集成实践中得到广泛采用。然而，随着 ES 的封闭世界向互联网规模的数据源开放，人们越来越需要更好地理解此类数据的语义以及如何集成它们。基础本体可以帮助建立这种理解，因此，有必要研究如何应用此类本体来支持实际的 ES 集成解决方案。本文介绍了通过开发和应用 4D 语义提取转换负载 (4D-SETL) 框架来评估这种方法有效性的研究。 4D-SETL 用于集成大量大规模数据集，并将生成的本体保存在基于图数据库的原型仓库中。该方法的优点包括能够将基础、领域和实例级本体对象组合到单个连贯系统中。此外，该方法提供了一种明确的方法来建立和维护领域对象的身份，因为它们的组成时空部分随着时间的推移而展开，从而使过程和静态数据能够组合在单个模型中。
Although successfully employed as the foundation for a number of large-scale government and energy industry projects, foundational ontologies have not been widely adopted within mainstream Enterprise Systems (ES) data integration practice. However, as the closed-worlds of ES are opened to Internet scale data sources, there is an emerging need to better understand the semantics of such data and how they can be integrated. Foundational ontologies can help establish this understanding and therefore, there is a need to investigate how such ontologies can be applied to underpin practical ES integration solutions. This paper describes research undertaken to assess the effectiveness of such an approach through the development and application of the 4D-Semantic Extract Transform Load (4D-SETL) framework. 4D-SETL was employed to integrate a number of large scale datasets and to persist the resultant ontology within a prototype warehouse based on a graph database. The advantages of the approach included the ability to combine foundational, domain and instance level ontological objects within a single coherent system. Furthermore, the approach provided a clear means of establishing and maintaining the identity of domain objects as their constituent spatiotemporal parts unfolded over time, enabling process and static data to be combined within a single model.