Building an ontology catalogue for smart cities

Apart from providing semantics and reasoning power to data, ontologies enable and facilitate interoperability across heterogeneous systems or environments. A good practice when developing ontologies is to reuse as much knowledge as possible in order to increase interoperability by reducing heterogeneity across models and to reduce development effort. Ontology registries, indexes and catalogues facilitate the task of finding, exploring and reusing ontologies by collecting them from different sources. This paper presents an ontology catalogue for the smart cities and related domains. This catalogue is based on curated metadata and incorporates ontology evaluation features. Such catalogue represents the first approach within this community and it would be highly useful for new ontology developments or for describing and annotating existing ontologies

Linked USDL: a vocabulary for web-scale service trading

Real-world services ranging from cloud solutions to consulting currently dominate economic activity. Yet, despite the increasing number of service marketplaces online, service trading on the Web remains highly restricted. Services are at best traded within closed silos that offer mainly manual search and comparison capabilities through a Web storefront. Thus, it is seldom possible to automate the customisation, bundling, and trading of services, which would foster a more efficient and effective service sector. In this paper we present Linked USDL, a comprehensive vocabulary for capturing and sharing rich service descriptions, which aims to support the trading of services over the Web in an open, scalable, and highly automated manner. The vocabulary adopts and exploits Linked Data as a means to efficiently support communication over the Web, to promote and simplify its adoption by reusing vocabularies and datasets, and to enable the opportunistic engagement of multiple cross-domain providers

Leveraging Indexical Pragmatics (OFIP) for Search Engine: An Ontology- based Approach

The relevance of search results is an important indicator of information retrieval performance. A domain-specific Search Engine (SE), distinct from a general web SE, focuses on a specific segment of online content and may increase search results relevance. Traditional methods to improve domain-specific SE precision heavily depend on query expansion, lexical analysis of texts, and large amounts of training data. These methods suffer from limited effectiveness and efficiency because expanded query terms and coarse language features bring in uncontrollable complexity and increase dimensionality. Our design, leveraging the integrated power of computational syntax, semantics, and indexical pragmatics, proposes an ontology-driven framework that is tailored to work in a dynamic Internet environment without large amounts of manually annotated training data. This article presents our design, that is essential for building a domain-specific SE, and its instantiation in the terrorism domain

A More Decentralized Vision for Linked Data

In this deliberately provocative position paper, we claim that ten years into Linked Data there are still (too?) many unresolved challenges towards arriving at a truly machine-readable and decentralized Web of data. We take a deeper look at the biomedical domain - currently, one of the most promising "adopters" of Linked Data - if we believe the ever-present "LOD cloud" diagram. Herein, we try to highlight and exemplify key technical and non-technical challenges to the success of LOD, and we outline potential solution strategies. We hope that this paper will serve as a discussion basis for a fresh start towards more actionable, truly decentralized Linked Data, and as a call to the community to join forces.Series: Working Papers on Information Systems, Information Business and Operation

Ontology evaluation approach for semantic web documents

Ontology is a conceptual tool used for managing and capturing information related to domain knowledge, such as the travel, education and medical domains. Publicly available ontology repositories like Falcons and SWOOGLE enhance the growth of ontology on the Web by providing a medium for ontology developers to publish their ontologies. In order to promote ontology reuse, a suitable approach for ontology evaluation is required that deals with ontology coverage for domain representation which includes an approach for validating the ontology with a corpus of information containing terms related to domain knowledge. Since contributions in ontology evaluation were introduced in different aspects, it is important to conceptualise related information to build an evaluation approach that can help users to select ontology. This work proposed OntoUji, an ontology that conceptualises information related to ontology evaluation. From OntoUji conceptualisation, these works proceed with the development of evaluation steps that are then converted into ontology evaluation algorithms to evaluate ontology documents retrieved from selected repositories according to data-driven evaluation approach. The data-driven approach focuses on evaluating the coverage of ontology using a set of keywords provided, yet similarly involves a comparison of ontological vocabulary with a pre-defined corpus, WordNet, gained from the information retrieval approach. The evaluation is then processed using Letters Pair Similarity algorithm as the selected similarity measures technique to process the ontology coverage result. The findings showed that the OntoUji ontology conceptualization helps to define ontology evaluation steps to gain similarity result for ontology selection

Context-based ontology matching and data interlinking

euzenat2015cContext-based matching finds correspondences between entities from two ontologies by relating them to other resources. A general view of context-based matching is designed by analysing existing such matchers. This view is instantiated in a path-driven approach that (a) anchors the ontologies to external ontologies, (b) finds sequences of entities (path) that relate entities to match within and across these resources, and (c) uses algebras of relations for combining the relations obtained along these paths. Parameters governing such a system are identified and made explicit. We discuss the extension of this approach to data interlinking and its benefit to cross-lingual data interlinking. First, this extension would require an hybrid algebra of relation that combines relations between individual and classes. However, such an algebra may not be particularly useful in practice as only in a few restricted case it could conclude that two individuals are the same. But it can be used for finding mistakes in link sets

Watson, more than a Semantic Web search engine

In this tool report, we present an overview of the Watson system, a Semantic Web search engine providing various functionalities not only to find and locate ontologies and semantic data online, but also to explore the content of these semantic documents. Beyond the simple facade of a search engine for the Semantic Web, we show that the availability of such a component brings new possibilities in terms of developing semantic applications that exploit the content of the Semantic Web. Indeed, Watson provides a set of APIs containing high level functions for finding, exploring and querying semantic data and ontologies that have been published online. Thanks to these APIs, new applications have emerged that connect activities such as ontology construction, matching, sense disambiguation and question answering to the Semantic Web, developed by our group and others. In addition, we also describe Watson as a unprecedented research platform for the study the Semantic Web, and of formalised knowledge in general