The Landscape of Ontology Reuse in Linked Data

Abstract. The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies for describing different domains. Ac-cording to LD principles, developers should reuse as many available terms as possible to describe their data. Importing ontologies or referring to their terms’ URIs are the two main ways to reuse knowledge from available ontologies. In this paper, we have analyzed 18589 terms appearing within 196 ontologies in-cluded in the Linked Open Vocabularies (LOV) registry with the aim of under-standing the current state of ontology reuse in the LD context. In order to char-acterize the landscape of ontology reuse in this context, we have extracted sta-tistics about currently reused elements, calculated ratios for reuse, and drawn graphs about imports and references between ontologies. Keywords: ontology, vocabulary, reuse, linked data, ontology import

Ontology Development by Reuse

This chapter presents methodological guidelines that allow engineers to reuse generic ontologies. This kind of ontologies represents notions generic across many fields, (is part of, temporal interval, etc.). The guidelines helps the developer (a) to identify the type of generic ontology to be reused, (b) to find out the axioms and definitions that should be reused and (c) to adapt and integrate the generic ontology selected in the domain ontology to be developed. For each task of the methodology, a set of heuristics with examples are presented. We hope that after reading this chapter, you would have acquired some basic ideas on how to take advantage of the great deal of well-founded explicit knowledge that formalizes generic notions such as time concepts and the part of relation.

Toward a fuzzy domain ontology extraction method for adaptive e-learning

With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

Ontology learning from user tagging for recommendation making

Recently, user tagging systems have grown in popularity on the web. The tagging process is quite simple for ordinary users, which contributes to its popularity. However, free vocabulary has lack of standardization and semantic ambiguity. It is possible to capture the semantics from user tagging into some form of ontology, but the application of the resulted ontology for recommendation making has not been that flourishing. In this paper we discuss our approach to learn domain ontology from user tagging information and apply the extracted tag ontology in a pilot tag recommendation experiment. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.

A Reuse-based Lightweight Method for Developing Linked Data Ontologies and Vocabularies

The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies for describing different domains. Par-ticular LD development characteristics such as agility and web-based architec-ture necessitate the revision, adaption, and lightening of existing methodologies for ontology development. This thesis proposes a lightweight method for ontol-ogy development in an LD context which will be based in data-driven agile de-velopments, existing resources to be reused, and the evaluation of the obtained products considering both classical ontological engineering principles and LD characteristics.

Ontology-based access to sensor data streams

Sensor networks are increasingly becoming one of the main sources of Big Data on the Web. However, the observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse these data for other purposes than those for which they were originally set up. In this thesis we address these challenges, considering how we can transform streaming raw data to rich ontology-based information that is accessible through continuous queries for streaming data. Our main contribution is an ontology-based approach for providing data access and query capabilities to streaming data sources, allowing users to express their needs at a conceptual level, independent of implementation and language-specific details. We introduce novel query rewriting and data translation techniques that rely on mapping definitions relating streaming data models to ontological concepts. Specific contributions include: • The syntax and semantics of the SPARQLStream query language for ontologybased data access, and a query rewriting approach for transforming SPARQLStream queries into streaming algebra expressions. • The design of an ontology-based streaming data access engine that can internally reuse an existing data stream engine, complex event processor or sensor middleware, using R2RML mappings for defining relationships between streaming data models and ontology concepts. Concerning the sensor metadata of such streaming data sources, we have investigated how we can use raw measurements to characterize streaming data, producing enriched data descriptions in terms of ontological models. Our specific contributions are: • A representation of sensor data time series that captures gradient information that is useful to characterize types of sensor data. • A method for classifying sensor data time series and determining the type of data, using data mining techniques, and a method for extracting semantic sensor metadata features from the time series.

The NeOn Ontology Models

Interoperability on multiple levels, concerning both the ontologies themselves and their engineering activities, is a key requirement for ontology networks to be efficient, with minimal redundancy and high reuse. This requirement has a strict binding for software tools that can support some interoperability levels, yet they can be hindered by a lack of shared models and vocabularies describing the resources to be handled, as well as the ways of handling them. Here, three examples of metalevel vocabularies are proposed, each covering at least one peculiar interoperability aspect: OMV for modeling the artifacts themselves, LIR for managing a multilingual layer on top of them, and C-ODO Light for modeling collaboration-supportive life cycle management tasks and processes. All of these models lend themselves to handling by dedicated software tools and are all being employed within NeOn products.

Introduction: Ontology Engineering in a Networked World

While ontology engineering is rapidly entering the mainstream, expert ontology engineers are a scarce resource. Hence, there is a need for practical methodologies and technologies, which can assist a variety of user types with ontology development tasks. To address this need, this book presents a scenario-based methodology, the NeOn Methodology, which provides guidance for all main activities in ontology engineering. The context in which we consider these activities is that of a networked world, where reuse of existing resources is commonplace, ontologies are developed collaboratively, and managing relationships between ontologies becomes an essential aspect of the ontological engineering process. The description of both the methodology and the ontology engineering activities is grounded in a comprehensive software environment, the NeOn Toolkit and its plugins, which provides integrated support for all the activities described in the book. Here we provide an introduction for the whole book, while the rest of the content is organized into 4 parts: (1) the NeOn Methodology Framework, (2) the set of ontology engineering activities, (3) the NeOn Toolkit and plugins, and (4) three use cases. Primary goals of this book are (a) to disseminate the results from the NeOn project in a structured and comprehensive form, (b) to make it easier for students and practitioners to adopt ontology engineering methods and tools, and (c) to provide a textbook for undergraduate and postgraduate courses on ontology engineering.

Ontology Requirements Specification

The goal of the ontology requirements specification activity is to state why the ontology is being built, what its intended uses are, who the end users are, and which requirements the ontology should fulfill. This chapter presents detailed methodological guidelines for specifying ontology requirements efficiently. These guidelines will help ontology engineers to capture ontology requirements and produce the ontology requirements specification document (ORSD). The ORSD will play a key role during the ontology development process because it facilitates, among other activities, (1) the search and reuse of existing knowledge resources with the aim of reengineering them into ontologies, (2) the search and reuse of ontological resources (ontologies, ontology modules, ontology statements as well as ontology design patterns), and (3) the verification of the ontology along the ontology development.

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.

A formal model of the Semantic Web Service Ontology (WSMO)

Semantic Web Service, one of the most significant research areas within the Semantic Web vision, has attracted increasing attention from both the research community and industry. The Web Service Modelling Ontology (WSMO) has been proposed as an enabling framework for the total/partial automation of the tasks (e.g., discovery, selection, composition, mediation, execution, monitoring, etc.) involved in both intra- and inter-enterprise integration of Web services. To support the standardisation and tool support of WSMO, a formal model of the language is highly desirable. As several variants of WSMO have been proposed by the WSMO community, which are still under development, the syntax and semantics of WSMO should be formally defined to facilitate easy reuse and future development. In this paper, we present a formal Object-Z formal model of WSMO, where different aspects of the language have been precisely defined within one unified framework. This model not only provides a formal unambiguous model which can be used to develop tools and facilitate future development, but as demonstrated in this paper, can be used to identify and eliminate errors present in existing documentation.

Building an Ontology of Product/Service-Systems: Using a Maritime Case Study to Elicit Classifications and Characteristics

Part 4: Transition Towards Product-Service Systems