Evaluating the semantic web: a task-based approach

The increased availability of online knowledge has led to the design of several algorithms that solve a variety of tasks by harvesting the Semantic Web, i.e. by dynamically selecting and exploring a multitude of online ontologies. Our hypothesis is that the performance of such novel algorithms implicity provides an insight into the quality of the used ontologies and thus opens the way to a task-based evaluation of the Semantic Web. We have investigated this hypothesis by studying the lessons learnt about online ontologies when used to solve three tasks: ontology matching, folksonomy enrichment, and word sense disambiguation. Our analysis leads to a suit of conclusions about the status of the Semantic Web, which highlight a number of strengths and weaknesses of the semantic information available online and complement the findings of other analysis of the Semantic Web landscape

Semantic Web Techniques to Support Interoperability in Distributed Networked Environments

We explore two Semantic Web techniques arising from ITA research into semantic alignment and interoperability in distributed networks. The first is POAF (Portable Ontology Aligned Fragments) which addresses issues relating to the portability and usage of ontology alignments. POAF uses an ontology fragmentation strategy to achieve portability, and enables subsequent usage through a form of automated ontology modularization. The second technique, SWEDER (Semantic Wrapping of Existing Data sources with Embedded Rules), is grounded in the creation of lightweight ontologies to semantically wrap existing data sources, to facilitate rapid semantic integration through representational homogeneity. The semantic integration is achieved through the creation of context ontologies which define the integrations and provide a portable definition of the integration rules in the form of embedded SPARQL construct clauses. These two Semantic Web techniques address important practical issues relevant to the potential future adoption of ontologies in distributed network environments

User-system cooperation in document annotation based on information extraction

The process of document annotation for the Semantic Web is complex and time consuming, as it requires a great deal of manual annotation. Information extraction from texts (IE) is a technology used by some very recent systems for reducing the burden of annotation. The integration of IE systems in annotation tools is quite a new development and there is still the necessity of thinking the impact of the IE system on the whole annotation process. In this paper we initially discuss a number of requirements for the use of IE as support for annotation. Then we present and discuss a model of interaction that addresses such issues and Melita, an annotation framework that implements a methodology for active annotation for the Semantic Web based on IE. Finally we present an experiment that quantifies the gain in using IE as support to human annotators.peer-reviewe

Semantic Transformation of Web Services

Web services have become the predominant paradigm for the development of distributed software systems. Web services provide the means to modularize software in a way that functionality can be described, discovered and deployed in a platform independent manner over a network (e.g., intranets, extranets and the Internet). The representation of web services by current industrial practice is predominantly syntactic in nature lacking the fundamental semantic underpinnings required to fulfill the goals of the emerging Semantic Web. This paper proposes a framework aimed at (1) modeling the semantics of syntactically defined web services through a process of interpretation, (2) scop-ing the derived concepts within domain ontologies, and (3) harmonizing the semantic web services with the domain ontologies. The framework was vali-dated through its application to web services developed for a large financial system. The worked example presented in this paper is extracted from the se-mantic modeling of these financial web services

Semantic Network Analysis of Ontologies

A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures currently receive high attention in the Semantic Web community, there are only very few SNA applications, and virtually none for analyzing the structure of ontologies. We illustrate the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size

Issues with Evaluating and Using Publicly Available Ontologies

The proliferation of ontologies in the public domain and the ease of accessing them offers new opportunities for knowledge sharing and interoperability in an open, distributed environment, but it also poses interesting challenges for knowledge and Web engineers alike. In this paper we discuss and analyse those challenges with emphasis on the need to evaluate publicly available ontologies prior to use. We elaborate on a number of issues ranging from technological concerns to strategic and political issues. We drawn our experiences from the field of ontology mapping on the Semantic Web, a necessity that enables many of Semantic Web's proclaimed features

Desirable Ontologies for the Construction of Semantic Applications

The intended goal of semantic web is to provide the search results to the user with at most accuracy and good precision. To make possible, the object of semantic web is to add semantics to the existing information on the Web using semantic web languages. These web languages have been to express detail information of the content present on the web with help of Ontologies. Ontology is expressed in a knowledge representation language, which provides a formal frame of semantics. Therefore we provide a brief explanation of semantic web languages in which some of them uses description logic and frames as basis. These semantic languages used in construction and understanding of ontologies clearly. The goal of this paper is to provide a brief survey of state-of-the-art ontology languages which are used to express ontology over the Web, a basic understanding of ontologies and how the ontologies are constructed

Selection of Ontologies for the Semantic Web

The development of the Semantic Web has encouraged the creation of ontologies in a great variety of domains. Web users currently looking for ontologies in order to incorporate them into their systems, just use their experience and intuition. This makes it difficult for them to justify their choices. Mainly, this is due to the lack of methods that help the user to measure that the most appropriate ontologies for the new system are. To solve this deficiency, this work proposes a method which allows the users to measure the suitability of the existent ontologies, regarding the requirements of their systems