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Article

Monika Lanzenberger, Jennifer J. Sampson, Markus Rester, Yannick Naudet and Thibaud Latour

By providing interoperability users can be supported in sharing and reusing vocabularies and knowledge. Ontology alignment plays an important role in the context of

Abstract

Purpose

By providing interoperability users can be supported in sharing and reusing vocabularies and knowledge. Ontology alignment plays an important role in the context of semantic interoperability. Usually ontology alignment tools generate results that are difficult to understand or assess. In order to enable users to check and improve alignment results and to understand their consequences information visualization techniques are used. The purpose of this paper is to discuss the relevant quality aspects in ontology alignment as well as current activities and available tools.

Design/methodology/approach

Based on a literature study quality measures for ontology alignment identified and requirements for visual ontology alignment are defined. As a proof of concepts a prototype called AlViz was developed.

Findings

Information visualization offers appropriate methods for the assessment of ontology alignment results. Different levels of detail and overview help users to navigate and understand the alignments. The assessment of semi‐structured resources by users involves learning activities. The neighborhood of the entity under investigation bears relevant semantic information. Therefore, assessment may include crisscrossing acquisition of knowledge representations and their semantics.

Originality/value

Along a comprehensive framework alignment assessment tasks are identified and visualization tool is introduced and applied which aims at making ontology alignment results manageable and comprehensible.

Details

Journal of Knowledge Management, vol. 12 no. 6
Type: Research Article
ISSN: 1367-3270

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Article

Ivan Luiz Salvadori, Alexis Huf, Bruno C.N. Oliveira, Ronaldo dos Santos Mello and Frank Siqueira

This paper aims to propose a method based on Linked Data and Semantic Web principles for composing microservices through data integration. Two frameworks that provide…

Abstract

Purpose

This paper aims to propose a method based on Linked Data and Semantic Web principles for composing microservices through data integration. Two frameworks that provide support for the proposed composition method are also described in this paper: Linkedator, which is responsible for connecting entities managed by microservices, and Alignator, which aligns semantic concepts defined by heterogeneous ontologies.

Design/methodology/approach

The proposed method is based on entity linking principles and uses individual matching techniques considering a formal notion of identity. This method imposes two major constraints that must be taken into account by its implementation: architectural constraints and resource design constraints.

Findings

Experiments were performed in a real-world scenario, using public government data. The obtained results show the effectiveness of the proposed method and that, it leverages the independence of development and composability of microservices. Thereby, the data provided by microservices that adopt heterogeneous ontologies can now be linked together.

Research limitations/implications

This work only considers microservices designed as data providers. Microservices designed to execute functionalities in a given application domain are out of the scope of this work.

Originality/value

The proposed composition method exploits the potential data intersection observed in resource-oriented microservice descriptions, providing a navigable view of data provided by a set of interrelated microservices. Furthermore, this study explores the applicability of ontology alignments for composing microservices.

Details

International Journal of Web Information Systems, vol. 13 no. 3
Type: Research Article
ISSN: 1744-0084

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Article

Tayybah Kiren and Muhammad Shoaib

Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many…

Abstract

Purpose

Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many applications like semantic annotation, query answering or ontology integration. Some ontologies may include a large number of entities which make the ontology matching process very complex in terms of the search space and execution time requirements. The purpose of this paper is to present a technique for finding degree of similarity between ontologies that trims down the search space by eliminating the ontology concepts that have less likelihood of being matched.

Design/methodology/approach

Algorithms are written for finding key concepts, concept matching and relationship matching. WordNet is used for solving synonym problems during the matching process. The technique is evaluated using the reference alignments between ontologies from ontology alignment evaluation initiative benchmark in terms of degree of similarity, Pearson’s correlation coefficient and IR measures precision, recall and F-measure.

Findings

Positive correlation between the degree of similarity and degree of similarity (reference alignment) and computed values of precision, recall and F-measure showed that if only key concepts of ontologies are compared, a time and search space efficient ontology matching system can be developed.

Originality/value

On the basis of the present novel approach for ontology matching, it is concluded that using key concepts for ontology matching gives comparable results in reduced time and space.

Details

Aslib Journal of Information Management, vol. 68 no. 1
Type: Research Article
ISSN: 2050-3806

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Article

Biswanath Dutta

Ontology and Linked Data (LD) are the two prominent web technologies that have emerged in the recent past. Both of them are at the center of Semantic Web and its…

Abstract

Purpose

Ontology and Linked Data (LD) are the two prominent web technologies that have emerged in the recent past. Both of them are at the center of Semantic Web and its applications. Researchers and developers from both academia and business are actively working in these areas. The increasing interest in these technologies promoted the growth of LD sets and ontologies on the web. The purpose of this paper is to investigate the possible relationships between them. The effort is to investigate the possible roles that ontologies may play in further empowering the LD. In a similar fashion, the author also studies the possible roles that LD may play to empower ontologies.

Design/methodology/approach

The work is mainly carried out by exploring the ontology- and LD-based real-world systems, and by reviewing the existing literature.

Findings

The current work reveals, in general, that both the technologies are interdependent and have lots to offer to each other for their faster growth and meaningful development. Specifically, anything that we can do with LD, we can do more by adding an ontology to it.

Practical implications

The author envisions that the current work, in the one hand, will help in boosting the successful implementation and the delivery of semantic applications; on the other hand, it will also become a food for the future researchers in further investigating the relationships between the ontologies and LD.

Originality/value

So far, as per the author’s knowledge, there are very little works that have attempted in exploring the relationships between the ontologies and LD. In this work, the author illustrates the real-world systems that are based on ontology and LD, discusses the issues and challenges and finally illustrates their interdependency discussing some of the ongoing research works.

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Article

Bruno C.N. Oliveira, Alexis Huf, Ivan Luiz Salvadori and Frank Siqueira

This paper describes a software architecture that automatically adds semantic capabilities to data services. The proposed architecture, called OntoGenesis, is able to…

Abstract

Purpose

This paper describes a software architecture that automatically adds semantic capabilities to data services. The proposed architecture, called OntoGenesis, is able to semantically enrich data services, so that they can dynamically provide both semantic descriptions and data representations.

Design/methodology/approach

The enrichment approach is designed to intercept the requests from data services. Therefore, a domain ontology is constructed and evolved in accordance with the syntactic representations provided by such services in order to define the data concepts. In addition, a property matching mechanism is proposed to exploit the potential data intersection observed in data service representations and external data sources so as to enhance the domain ontology with new equivalences triples. Finally, the enrichment approach is capable of deriving on demand a semantic description and data representations that link to the domain ontology concepts.

Findings

Experiments were performed using real-world datasets, such as DBpedia, GeoNames as well as open government data. The obtained results show the applicability of the proposed architecture and that it can boost the development of semantic data services. Moreover, the matching approach achieved better performance when compared with other existing approaches found in the literature.

Research limitations/implications

This work only considers services designed as data providers, i.e., services that provide an interface for accessing data sources. In addition, our approach assumes that both data services and external sources – used to enhance the domain ontology – have some potential of data intersection. Such assumption only requires that services and external sources share particular property values.

Originality/value

Unlike most of the approaches found in the literature, the architecture proposed in this paper is meant to semantically enrich data services in such way that human intervention is minimal. Furthermore, an automata-based index is also presented as a novel method that significantly improves the performance of the property matching mechanism.

Details

International Journal of Web Information Systems, vol. 15 no. 1
Type: Research Article
ISSN: 1744-0084

Keywords

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Article

Amed Leiva-Mederos, Jose A. Senso, Yusniel Hidalgo-Delgado and Pedro Hipola

Information from Current Research Information Systems (CRIS) is stored in different formats, in platforms that are not compatible, or even in independent networks. It…

Abstract

Purpose

Information from Current Research Information Systems (CRIS) is stored in different formats, in platforms that are not compatible, or even in independent networks. It would be helpful to have a well-defined methodology to allow for management data processing from a single site, so as to take advantage of the capacity to link disperse data found in different systems, platforms, sources and/or formats. Based on functionalities and materials of the VLIR project, the purpose of this paper is to present a model that provides for interoperability by means of semantic alignment techniques and metadata crosswalks, and facilitates the fusion of information stored in diverse sources.

Design/methodology/approach

After reviewing the state of the art regarding the diverse mechanisms for achieving semantic interoperability, the paper analyzes the following: the specific coverage of the data sets (type of data, thematic coverage and geographic coverage); the technical specifications needed to retrieve and analyze a distribution of the data set (format, protocol, etc.); the conditions of re-utilization (copyright and licenses); and the “dimensions” included in the data set as well as the semantics of these dimensions (the syntax and the taxonomies of reference). The semantic interoperability framework here presented implements semantic alignment and metadata crosswalk to convert information from three different systems (ABCD, Moodle and DSpace) to integrate all the databases in a single RDF file.

Findings

The paper also includes an evaluation based on the comparison – by means of calculations of recall and precision – of the proposed model and identical consultations made on Open Archives Initiative and SQL, in order to estimate its efficiency. The results have been satisfactory enough, due to the fact that the semantic interoperability facilitates the exact retrieval of information.

Originality/value

The proposed model enhances management of the syntactic and semantic interoperability of the CRIS system designed. In a real setting of use it achieves very positive results.

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Article

Rodolfo Stecher, Claudia Niederée, Wolfgang Nejdl and Paolo Bouquet

The discovery of the “right” ontology or ontology part is a central ingredient for effective ontology re‐use. The purpose of this paper is to present an approach for…

Abstract

Purpose

The discovery of the “right” ontology or ontology part is a central ingredient for effective ontology re‐use. The purpose of this paper is to present an approach for supporting a form of adaptive re‐use of sub‐ontologies, where the ontologies are deeply integrated beyond pure referencing.

Design/methodology/approach

Starting from an ontology draft which reflects the intended modeling perspective, the ontology engineer can be supported by suggesting similar already existing sub‐ontologies and ways for integrating them with the existing draft ontology. This paper's approach combines syntactic, linguistic, structural and logical methods into an innovative modeling‐perspective aware solution for detecting matchings between concepts from different ontologies. This paper focuses on the discovery and matching phase of this re‐use process.

Findings

Owing to the combination of techniques presented in this general approach, the work described performs in the general case as well as approaches tailored for a specific usage scenario.

Research limitations/implications

The methods used rely on lexical information obtained from the labels of the concepts and properties in the ontologies, which makes this approach appropriate in cases where this information is available. Also, this approach can handle some missing label information.

Practical implications

Ontology engineering tasks can take advantage from the proposed adaptive re‐use approach in order to re‐use existing ontologies or parts of them without introducing inconsistencies in the resulting ontology.

Originality/value

The adaptive re‐use of ontologies by finding and partially re‐using parts of existing ontological resources for building new ontologies is a new idea in the field, and the inclusion of the modeling perspective in the computation of the matches adds a new perspective that could also be exploited by other matching approaches.

Details

International Journal of Web Information Systems, vol. 4 no. 2
Type: Research Article
ISSN: 1744-0084

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Article

Leila Zemmouchi-Ghomari, Kaouther Mezaache and Mounia Oumessad

The purpose of this paper is to evaluate ontologies with respect to the linked data principles. This paper presents a concrete interpretation of the four linked data…

Abstract

Purpose

The purpose of this paper is to evaluate ontologies with respect to the linked data principles. This paper presents a concrete interpretation of the four linked data principles applied to ontologies, along with an implementation that automatically detects violations of these principles and fixes them (semi-automatically). The implementation is applied to a number of state-of-the-art ontologies.

Design/methodology/approach

Based on a precise and detailed interpretation of the linked data principles in the context of ontologies (to become as reusable as possible), the authors propose a set of algorithms to assess ontologies according to the four linked data principles along with means to implement them using a Java/Jena framework. All ontology elements are extracted and examined taking into account particular cases, such as blank nodes and literals. The authors also provide propositions to fix some of the detected anomalies.

Findings

The experimental results are consistent with the proven quality of popular ontologies of the linked data cloud because these ontologies obtained good scores from the linked data validator tool.

Originality/value

The proposed approach and its implementation takes into account the assessment of the four linked data principles and propose means to correct the detected anomalies in the assessed data sets, whereas most LD validator tools focus on the evaluation of principle 2 (URI dereferenceability) and principle 3 (RDF validation); additionally, they do not tackle the issue of fixing detected errors.

Details

International Journal of Web Information Systems, vol. 14 no. 4
Type: Research Article
ISSN: 1744-0084

Keywords

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Article

Ana Marilza Pernas, Alicia Diaz, Regina Motz and José Palazzo Moreira de Oliveira

The broader adoption of the internet along with web‐based systems has defined a new way of exchanging information. That advance added by the multiplication of mobile…

Abstract

Purpose

The broader adoption of the internet along with web‐based systems has defined a new way of exchanging information. That advance added by the multiplication of mobile devices has required systems to be even more flexible and personalized. Maybe because of that, the traditional teaching‐controlled learning style has given up space to a new way of learning, which is more flexible and adequate to the learners needs. The purpose of this research is to go further into the semantic modeling of adaptive web based learning systems. Particularly, the paper focuses on those learning systems that consider in their definition the awareness of student's context in order to properly react to the student needs.

Design/methodology/approach

In this paper the authors introduce a semantic model of the student context in terms of an ontology network. This semantic model is explored in order to detect the “current situation” of students when they are navigating into e‐learning environments. The final objective is to enrich the adaptation functionality of e‐learning environments, being able to evaluate context data from personal profile, learning domain and technological situation.

Findings

In order to evaluate the semantic model defined, examples of detected situations are shown in accordance to specific e‐learning scenarios.

Originality/value

The paper covers definition of a flexible and modularized model by using ontology networks, which can be easily modified to incorporate new knowledge data, aiding the modeling of concepts from different learning environments.

Details

Interactive Technology and Smart Education, vol. 9 no. 2
Type: Research Article
ISSN: 1741-5659

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Article

M. Priya and Aswani Kumar Ch.

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras…

Abstract

Purpose

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras is noticeably very high. With the availability of these ontologies, the needed information can be smoothly attained, but the presence of comparably varied ontologies nurtures the dispute of rework and merging of data. The assessment of the existing ontologies exposes the existence of the superfluous information; hence, ontology merging is the only solution. The existing ontology merging methods focus only on highly relevant classes and instances, whereas somewhat relevant classes and instances have been simply dropped. Those somewhat relevant classes and instances may also be useful or relevant to the given domain. In this paper, we propose a new method called hybrid semantic similarity measure (HSSM)-based ontology merging using formal concept analysis (FCA) and semantic similarity measure.

Design/methodology/approach

The HSSM categorizes the relevancy into three classes, namely highly relevant, moderate relevant and least relevant classes and instances. To achieve high efficiency in merging, HSSM performs both FCA part and the semantic similarity part.

Findings

The experimental results proved that the HSSM produced better results compared with existing algorithms in terms of similarity distance and time. An inconsistency check can also be done for the dissimilar classes and instances within an ontology. The output ontology will have set of highly relevant and moderate classes and instances as well as few least relevant classes and instances that will eventually lead to exhaustive ontology for the particular domain.

Practical implications

In this paper, a HSSM method is proposed and used to merge the academic social network ontologies; this is observed to be an extremely powerful methodology compared with other former studies. This HSSM approach can be applied for various domain ontologies and it may deliver a novel vision to the researchers.

Originality/value

The HSSM is not applied for merging the ontologies in any former studies up to the knowledge of authors.

Details

Library Hi Tech, vol. 38 no. 2
Type: Research Article
ISSN: 0737-8831

Keywords

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