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ExODA: Integrating Description Logics and Database Technologies for Expressive Ontology-Based Data Access

ExODA：集成描述逻辑和数据库技术以实现基于表达本体的数据访问

基本信息

批准号：
EP/H051511/1
负责人：
Ian Horrocks
金额：
$ 89.77万
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2011
资助国家：
英国
起止时间：
2011 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FH051511%2F1
关键词：
ExODA Integrating Description Logics Database

项目摘要

Sources of semi-structured, overlapping, and semantically-related data on the Web are currently proliferating at a phenomenal rate, which has created a demand for more powerful and flexible information systems (ISs). This new generation of ISs will need to integrate incomplete and semi-structured information from heterogeneous sources, employ rich and flexible schemas, and answer queries by taking into account both knowledge and data.Ontology-based data access has recently been proposed as an architectural principle for such systems. The main idea is to develop a unified view of the data by describing the relevant domain in an ontology, which then provides the vocabulary used to ask queries. The IS can use ontological statements, such as the concept hierarchy, to derive new facts and thus enrich query answers with implicit knowledge. This idea has been incorporated into systems such as QuOnto, Owlgres, ROWLKit, and REQUIEM, and ontology reasoners such as RACER, FaCT++, Pellet, and HermiT.Such systems suffer from two main problems. First, the modelling capabilities of ontology languages are often insufficient for practical use cases. In order to achieve favourable computational properties, ontology languages are usually capable of describing only tree-shaped relationships; furthermore, (with some notable exceptions) they usually support only unary and binary predicates. Finally, ontology languages typically employ the open world assumption; however, when answering queries over large amounts of data, the closed world assumption (CWA) is often more appropriate.Second, query answering facilities in existing ontology-based ISs typically do not scale to data sets commonly encountered in practice. Up to now, approaches to addressing this problem have focused on reducing the expressivity of the ontology language even further in order to obtain formal tractability guarantees. This obviously exacerbates the first problem (restricted modelling capabilities), while not necessarily delivering robust scalability in practice.Database theory and practice can provide partial solutions to these problems. In databases, complex domains can be described using dependencies. Dependencies are used in a number of different ways: they are often used as integrity constraints--checks that verify whether a database instance includes all data specified in the domain description; however, dependencies can also be used similarly to ontologies to derive implicit knowledge. Treating dependencies as integrity constraints and answering queries under CWA has allowed practical relational database management systems (RDBMSs) to scale to very large data sets.Database techniques alone do not, however, satisfy all the requirements for an ontology-based IS. In particular, dependencies often cannot model arbitrarily large structures and thus do not cover all practical modelling use cases. Furthermore, generalising the query answering techniques used in practical RDBMSs to the case where information deriving dependencies must be taken into account is still an open problem.We therefore believe that the next generation of ontology-based ISs should be based on a synthesis and an extension of ontology and database systems and techniques, providing data handling capabilities similar to current RDBMSs, but with schemas that are rich, flexible, and tightly integrated with the data. In order to achieve this ambitions goal, however, a number of challenging fundamental problems must be solved. First, ontology and dependency languages need to be unified in a coherent theoretical framework. Second, it will be necessary to identify fragments of the framework that are likely to exhibit robust scalability but can still support realistic use cases. Third, it will be necessary to devise effective algorithmic techniques that can form the basis of practical ISs.

目前，Web 上半结构化、重叠和语义相关的数据源正在以惊人的速度激增，这就产生了对更强大、更灵活的信息系统 (IS) 的需求。新一代信息系统将需要集成来自异构源的不完整和半结构化信息，采用丰富而灵活的模式，并通过考虑知识和数据来回答查询。最近提出了基于本体的数据访问作为此类系统的架构原则。主要思想是通过描述本体中的相关领域来开发数据的统一视图，然后提供用于提出查询的词汇。 IS 可以使用本体论陈述（例如概念层次结构）来导出新事实，从而用隐含知识丰富查询答案。这一思想已被纳入 QuOnto、Owlgres、ROWLKit 和 REQUIEM 等系统以及 RACER、FaCT++、Pellet 和 HermiT 等本体推理器中。此类系统存在两个主要问题。首先，本体语言的建模能力通常不足以满足实际用例。为了获得良好的计算特性，本体语言通常只能描述树形关系；此外，（有一些值得注意的例外）它们通常仅支持一元和二元谓词。最后，本体语言通常采用开放世界假设；然而，当回答大量数据的查询时，封闭世界假设（CWA）通常更合适。其次，现有基于本体的信息系统中的查询回答设施通常无法扩展到实践中常见的数据集。到目前为止，解决这个问题的方法主要集中在进一步降低本体语言的表达能力，以获得正式的易处理性保证。这显然加剧了第一个问题（建模能力受限），同时在实践中不一定提供强大的可扩展性。数据库理论和实践可以为这些问题提供部分解决方案。在数据库中，可以使用依赖关系来描述复杂的域。依赖关系有多种不同的使用方式：它们通常用作完整性约束——检查数据库实例是否包含域描述中指定的所有数据；然而，依赖关系也可以与本体类似地使用来导出隐式知识。将依赖关系视为完整性约束并在 CWA 下回答查询，使得实用的关系数据库管理系统 (RDBMS) 能够扩展到非常大的数据集。然而，仅靠数据库技术并不能满足基于本体的 IS 的所有要求。特别是，依赖关系通常无法对任意大的结构进行建模，因此无法涵盖所有实际的建模用例。此外，将实际RDBMS中使用的查询应答技术推广到必须考虑信息派生依赖关系的情况仍然是一个悬而未决的问题。因此，我们认为下一代基于本体的IS应该基于本体和数据库系统和技术的综合和扩展，提供与当前RDBMS类似的数据处理能力，但具有丰富、灵活和紧密集成的模式与数据。然而，为了实现这一宏伟目标，必须解决一些具有挑战性的基本问题。首先，本体和依赖语言需要统一在一个连贯的理论框架中。其次，有必要确定框架的片段，这些片段可能表现出强大的可扩展性，但仍然可以支持实际的用例。第三，有必要设计出有效的算法技术，为实用信息系统奠定基础。