The Semantic Web: the roles of XML and RDF

XML and RDF are the current standards for establishing semantic interoperability on the Web, but XML addresses only document structure. RDF better facilitates interoperation because it provides a data model that can be extended to address sophisticated ontology representation techniques. We explain the role of ontologies in the architecture of the Semantic Web. We then briefly summarize key elements of XML and RDF, showing why using XML as a tool for semantic interoperability will be ineffective in the long run. We argue that a further representation and inference layer is needed on top of the Web's current layers, and to establish such a layer, we propose a general method for encoding ontology representation languages into RDF/RDF schema. We illustrate the extension method by applying it to Ontology Interchange Language, an ontology representation and inference language     

Constructing ontologies by mining deep semantics from XML Schemas and XML instance documents

With the development of the Semantic Web and Artificial Intelligence techniques, ontology has become a very powerful way of representing not only knowledge but also their semantics. Therefore, how to construct ontologies from existing data sources has become an important research topic. In this paper, an approach for constructing ontologies by mining deep semantics from eXtensible Markup Language (XML) Schemas (including XML Schema 1.0 and XML Schema 1.1) and XML instance documents is proposed. Given an XML Schema and its corresponding XML instance document, 34 rules are first defined to mine deep semantics from the XML Schema. The mined semantics is formally stored in an intermediate conceptual model and then is used to generate an ontology at the conceptual level. Further, an ontology population approach at the instance level based on the XML instance document is proposed. Now, a complete ontology is formed. Also, some corresponding core algorithms are provided. Finally, a prototype system is implemented, which can automatically generate ontologies from XML Schemas and populate ontologies from XML instance documents. The paper also classifies and summarizes the existing work and makes a detailed comparison. Case studies on real XML data sets verify the effectiveness of the approach.     

Representing and Reasoning About XML with Ontologies

The eXtensible Markup Language (XML) has reached a wide acceptance as the relevant standardization for representing and exchanging data on the Web. Unfortunately, XML covers the syntactic level but lacks semantics, and thus cannot be directly used for the Semantic Web. Currently, finding a way to utilize XML data for the Semantic Web is challenging research. As we have known that ontology can formally represent shared domain knowledge and enable semantics interoperability. Therefore, in this paper, we investigate how to represent and reason about XML with ontologies. Firstly, we give formalized representations of XML data sources, including Document Type Definitions (DTDs), XML Schemas, and XML documents. On this basis, we propose formal approaches for transforming the XML data sources into ontologies, and we also discuss the correctness of the transformations and provide several transformation examples. Furthermore, following the proposed approaches, we implement a prototype tool that can automatically transform XML into ontologies. Finally, we apply the transformed ontologies for reasoning about XML, so that some reasoning problems of XML may be checked by the existing ontology reasoners.     

基于关系数据库的模糊本体的存储方法

模糊本体被广泛用来描述语义Web上的模糊信息。如何对模糊本体进行有效的存储,逐渐成为语义Web领域一个重要的研究课题。鉴于关系数据库在数据组织与管理方面的优势,提出基于关系数据库的模糊本体的存储方法。首先,通过对RDF数据类型进行模糊扩展,给出模糊本体中模糊数据类型的表示方法;然后,提出了基于关系数据库的模糊本体的存储模式以及模糊本体的结构和实例在关系数据库中的存储方法;最后,证明了该存储方法的正确性。基于关系数据库的模糊本体的存储方法为语义Web中模糊数据的存储和管理提供了一个有效的解决方案。     

Growing triples on trees: an XML-RDF hybrid model for annotated documents

Since the beginning of the Semantic Web initiative, significant efforts have been invested in finding efficient ways to publish, store, and query metadata on the Web. RDF and SPARQL have become the standard data model and query language, respectively, to describe resources on the Web. Large amounts of RDF data are now available either as stand-alone datasets or as metadata over semi-structured (typically XML) documents. The ability to apply RDF annotations over XML data emphasizes the need to represent and query data and metadata simultaneously. We propose XR, a novel hybrid data model capturing the structural aspects of XML data and the semantics of RDF, also enabling us to reason about XML data. Our model is general enough to describe pure XML or RDF datasets, as well as RDF-annotated XML data, where any XML node can act as a resource. This data model comes with the XRQ query language that combines features of both XQuery and SPARQL. To demonstrate the feasibility of this hybrid XML-RDF data management setting, and to validate its interest, we have developed an XR platform on top of well-known data management systems for XML and RDF. In particular, the platform features several XRQ query processing algorithms, whose performance is experimentally compared.     

ActiveRDF: Embedding Semantic Web data into object-oriented languages

Semantic Web applications share a large portion of development effort with database-driven Web applications. Existing approaches for development of these database-driven applications cannot be directly applied to Semantic Web data due to differences in the underlying data model. We develop a mapping approach that embeds Semantic Web data into object-oriented languages and thereby enables reuse of existing Web application frameworks.We analyse the relation between the Semantic Web and the Web, and survey the typical data access patterns in Semantic Web applications. We discuss the mismatch between object-oriented programming languages and Semantic Web data, for example in the semantics of class membership, inheritance relations, and object conformance to schemas.We present ActiveRDF, an object-oriented API for managing RDF data that offers full manipulation and querying of RDF data, does not rely on a schema and fully conforms to RDF(S) semantics. ActiveRDF can be used with different RDF data stores: adapters have been implemented to generic SPARQL endpoints, Sesame, Jena, Redland and YARS and new adapters can be added easily. We demonstrate the usage of ActiveRDF and its integration with the popular Ruby on Rails framework which enables rapid development of Semantic Web applications.     

Semi-automatic construction of domain ontology for agent reasoning

One of the key elements of the Semantic Web technologies is domain ontologies and those ontologies are important constructs for multi-agent system. The Semantic Web relies on domain ontologies that structure underlying data enabling comprehensive and transportable machine understanding. It takes so much time and efforts to construct domain ontologies because these ontologies can be manually made by domain experts and knowledge engineers. To solve these problems, there have been many researches to semi-automatically construct ontologies. Most of the researches focused on relation extraction part but manually selected terms for ontologies. These researches have some problems. In this paper, we propose a hybrid method to extract relations from domain documents which combines a named relation approach and an unnamed relation approach. Our named relation approach is based on the Hearst’s pattern and the Snowball system. We merge a generalized pattern scheme into their methods. In our unnamed relation approach, we extract unnamed relations using association rules and clustering method. Moreover, we recommend candidate relation names of unnamed relations. We evaluate our proposed method by using Ziff document set offered by TREC.     

基于本体的语义Web研究

语义Web与本体的关系极为特殊,本体在语义Web本身的体系结构中扮演着极为重要的角色,同时,位于语义Web体系结构的其它层的XML、RDF(S)等与本体也有着千丝万缕的联系。为阐述两者的关系,探讨基于本体的语义Web的特点及应用,介绍了本体和语义Web的产生和发展,在此基础上对基于本体的语义Web进行研究,重点分析了本体在描述语义方面弥补了XML、RDF(S)等的不足,并结合Web服务检索的实例介绍了本体在Web服务上的应用。     

一种利用模糊关系数据库构建模糊OWL本体的方法

经典OWL本体不能直接表示和处理语义Web应用中广泛存在的模糊知识,鉴于模糊关系数据库在模糊数据表示与处理方面的优势,提出利用模糊关系数据库来构建模糊OWL本体.通过对RDF数据类型进行模糊扩展,并从模糊数据类型角度扩展OWL,解决了模糊OWL本体的表示问题;在此基础上,研究了以模糊关系数据库为数据源的模糊OWL本体的构建方法,该方法为语义Web中模糊本体的构建提供了一个有效的解决方案.     

一种基于语义的协同工作模型

针对产品制造领域,提出一种基于语义的协同工作模型。该模型分别以XML和RDF(S)作为协同信息的语法描述模式和语义描述模型,为协同信息提供机器呵处理和可理解能力;通过建立由个体Ontology和顶层Ontology构成的两层Ontology体系,以个体Ontology描述协同过程中个人或团体的领域背景知识,以顶层Ontology为概念和语义参照模型,建立协同信息之间的语义约束,为协同过程提供多领域知识共享和互操作环境。     

Ease of interaction plus ease of integration: Combining Web2.0 and the Semantic Web in a reviewing site

Web2.0 has enabled contributions to the Web on an unprecedented scale, through simple interfaces that provide engaging interactions. This wealth of data has spawned countless mashups that integrate heterogenous information, but using techniques that will not scale beyond a handful of sources. In contrast, the Semantic Web provides the key to large-scale data integration, yet still lacks approachable interfaces allowing contributions from non-specialists. In this paper we present Revyu, a reviewing and rating site in the Web2.0 mould that is built on Semantic Web infrastructure and both publishes and consumes linked RDF data. This combination of approaches affords ease of interaction for regular users and ease of integration with external data sources.     

Revyu: Linking reviews and ratings into the Web of Data

Revyu is a live, publicly accessible reviewing and rating Web site, designed to be usable by humans whilst transparently generating machine-readable RDF metadata for the Semantic Web, based on user input. The site uses Semantic Web specifications such as RDF and SPARQL, and the latest Linked Data best practices to create a major node in a potentially Web-wide ecosystem of reviews and related data. Throughout the implementation of Revyu design decisions have been made that aim to minimize the burden on users, by maximizing the reuse of external data sources, and allowing less structured human input (in the form of Web 2.0-style tagging) from which stronger semantics can later be derived. Links to external sources such as DBpedia are exploited to create human-oriented mashups at the HTML level, whilst links are also made in RDF to ensure Revyu plays a first class role in the blossoming Web of Data. In this paper we document design decisions made during the implementation of Revyu, discuss the techniques used for linking Revyu data with external sources, and outline how data from the site is being used to infer the trustworthiness of reviewers as sources of information and recommendations.     

RDB中基于RDFS的语义本体存储技术研究

资源描述框架(RDF)/资源描述框架模式(RDFS)是语义互联网架构中的技术。尽管XML/RDF数据库正迅速的发展,关系型数据库仍是目前企业级应用的首选。针对如何有效地把RDFS数据存储在关系数据库中,充分利用现有的数据库资源来管理RDFS数据,提出了一种RDB中基于RDFS的语义本体存储技术,实现了RDFS本体抽取,提出了RDFS本体的存储优化方案,提高了数据存储访问效率。     

Bridging the semantic Web and Web 2.0 with Representational State Transfer (REST)

Semantic Web technologies must integrate with Web 2.0 services for both to leverage each others strengths. We argue that the REST-based design methodologies [R.T. Fielding, R.N. Taylor, Principled design of the modern web architecture, ACM Trans. Internet Technol. (TOIT) 2 (2) (2002) 115–150] of the web present the ideal mechanism through which to align the publication of semantic data with the existing web architecture. We present the design and implementation of two solutions that combine REST-based design and RDF [D. Beckett (Ed.), RDF/XML Syntax Specification (Revised), W3C Recommendation, February 10, 2004] data access: one solution for integrating existing web services and one server-side solution for creating RDF REST services. Both of these solutions enable SPARQL [E. Prud’hommeaux, A. Seaborne (Eds.), SPARQL Query Language for RDF, W3C Working Draft, March 26, 2007] to be a unifying data access layer for aligning the Semantic Web and Web 2.0.