International Journal of Metadata, Semantics and Ontologies
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International Journal of Metadata, Semantics and Ontologies (4 papers in press)
Abstract: Semantic annotation, the process of identifying key phrases in texts and linking them to concepts in a knowledge base, is an important basis for semantic information retrieval and the Semantic Web uptake. Despite the emergence of semantic annotation systems, very few comparative studies have been published on their performance. In this paper, we provide an evaluation of the performance of existing systems over three tasks: full semantic annotation, named entity recognition, and keyword detection. More specifically, the spotting capability (recognition of relevant surface forms in text) is evaluated for all three tasks, whereas the disambiguation (correctly associating an entity from Wikipedia or DBpedia to the spotted surface forms) is evaluated only for the first two tasks. We use logistic regression to identify significant performance differences. Although some of the annotators are specifically targeted at some task (NE, SA, KW), our results show that they do not necessarily obtain the best performance on those tasks. In fact, systems identified as full semantic annotators beat all other systems on all datasets. We also show that there is still much room for improvement for the identification of the most relevant entities described in a text.
Keywords: semantic annotation; linked data cloud; performance evaluation.
Ontology-based modleling of extended web service secure conversation Pattern
by Ashish Kumar Dwivedi
Abstract: Securing an application based on service oriented architecture provides defence against a number of security threats arising from exposing applications and data to the internet. Various security guidelines are available to apply security in web applications. But these guidelines are sometimes difficult to understand and generate inconsistencies. In this study, an extended web service secure conversation pattern is presented in the presence of a man-in-the-middle attack. An ontology-based modelling and refinement framework is presented for semantically analysing an extended web service secure conversation pattern. A metamodel is introduced to provide rigorous modelling of security services in terms of concepts, properties, and relationships. At the end of this study, an evaluation of the proposed approach has been made by performing experiments for security requirements against security policies in the presence of proposed description logic rules.
Keywords: extended web service; secure conversation pattern; security patterns; semantic web service security; UML; OWL.
Collections revisited from the perspective of historical testimonies
by Annamaria Goy, Diego Magro
Abstract: This paper presents the results of an ontological analysis of collective entities, as an essential step towards the definition of a rich semantic model underlying ontology-driven applications in the historical and cultural heritage domains. The major contributions of our proposal are the following: (a) an explicit distinction of contingent and necessary features, that led us to formalise our ontology by means of modal logics; (b) a description of collective entities from a diachronic perspective (thus including singletons and empty collections); (c) an analysis of the inferences enabled by the characterisation of collective entities and by the inclusion relationships; (d) a representation of the inclusion relationships that does not imply existential dependence; (e) a distinction between emerging and created collective entities. In the paper, we present an indepth ontological analysis of these aspects and provide a sound formalisation for it.
Keywords: collections; collective entities; sets; ontology; ontologies; semantic model; ontological analysis; ontology-driven applications; semantic metadata; inference; modal logics; historical archives; historical testimonies; cultural heritage.
A data model-independent approach to big research data integration
by Valentina Bartalesi, Carlo Meghini, Costantino Thanos
Abstract: The paper discusses the data integration problem in the context of the scientific domain. The main characteristics of the big research data, that make the traditional approach of data integration unfeasible are presented. Two new emerging practices, i.e., an exploratory approach to data seeking and an empiricist epistemological approach to knowledge creation, that also contribute to making this approach not suited for this domain are discussed. Based on these considerations a new paradigm of data integration is proposed and discussed. An application ontology, i.e., the BDI ontology that supports this new paradigm is presented. The ontology is based on five types of event, concerning the creation of new databases or views, the update of the schema of a database or of the query defining a view, or the update of the data content of a database. Every event is extensionally modelled as an input/output operation on the involved data entity. The strong point of the ontology and of the whole approach to data integration, is that no assumption is made on the data models in which the databases or the views are expressed. This provides a level of generality that successfully deals with the heterogeneity of the domain, making our approach applicable in principle to every data integration context. Different approaches for implementing data integration based on the proposed ontology are also discussed, and an approach guaranteeing consistency while preserving efficiency is proposed. Some implementation issues are discussed and, as a proof of feasibility, the main algorithms for realising the approach are also given in the Appendix.
Keywords: data integration; big research data; ontology; semantic web.