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The common understanding of generalization/specialization relations assumes the relation to be equally strong between a classifier and any of its related classifiers and also at every level of the hierarchy. Assigning a grade of relative distance to represent the level of similarity between the related pairs of classifiers could correct this situation, which has been considered as an oversimplification of the psychological account of the real-world relations. The paper aims to discuss these issues.

The evaluation followed an end-user perspective. In order to obtain a consistent data set of specialization distances, a group of 21 persons was asked to assign values to a set of relations from a selection of terms from the AGROVOC thesaurus. Then two sets of representations of the relations between the terms were built, one according to the calculated concept of specialization weights and the other one following the original order of the thesaurus. In total, 40 persons were asked to choose between the two sets following an A/B test-like experiment. Finally, short interviews were carried out after the test to inquiry about their decisions.

The results show that the use of this information could be a valuable tool for search and information retrieval purposes and for the visual representation of knowledge organization systems (KOS). Furthermore, the methodology followed in the study turned out to be useful for detecting inconsistencies in the thesaurus and could thus be used for quality control and optimization of the hierarchical relations.

The use of this relative distance information, namely, “concept specialization distance,” has been proposed mainly at a theoretical level. In the current experiment, the authors evaluate the potential use of this information from an end-user perspective, not only for text-based interfaces but also its application for the visual representation of KOS. Finally, the methodology followed for the elaboration of the concept specialization distance data set showed potential for detecting possible inconsistencies in KOS.

The purpose of this paper is to review the current status of research on Wikidata and, in particular, of articles that either describe applications of Wikidata or provide empirical evidence, in order to uncover the topics of interest, the fields that are benefiting from its applications and which researchers and institutions are leading the work.

A systematic literature review is conducted to identify and review how Wikidata is being dealt with in academic research articles and the applications that are proposed. A rigorous and systematic process is implemented, aiming not only to summarize existing studies and research on the topic, but also to include an element of analytical criticism and a perspective on gaps and future research.

Despite Wikidata’s potential and the notable rise in research activity, the field is still in the early stages of study. Most research is published in conferences, highlighting such immaturity, and provides little empirical evidence of real use cases. Only a few disciplines currently benefit from Wikidata’s applications and do so with a significant gap between research and practice. Studies are dominated by European researchers, mirroring Wikidata’s content distribution and limiting its Worldwide applications.

The results collect and summarize existing Wikidata research articles published in the major international journals and conferences, delivering a meticulous summary of all the available empirical research on the topic which is representative of the state of the art at this time, complemented by a discussion of identified gaps and future work.

This paper reports on a quantitative study of data gathered from the Linked Open Vocabularies (LOV) catalogue, including the use of network analysis and metrics. The purpose of this paper is to gain insights into the structure of LOV and the use of vocabularies in the Web of Data. It is important to note that not all the vocabularies in it are registered in LOV. Given the de-centralised and collaborative nature of the use and adoption of these vocabularies, the results of the study can be used to identify emergent important vocabularies that are shaping the Web of Data.

The methodology is based on an analytical approach to a data set that captures a complete snapshot of the LOV catalogue dated April 2014. An initial analysis of the data is presented in order to obtain insights into the characteristics of the vocabularies found in LOV. This is followed by an analysis of the use of Vocabulary of a Friend properties that describe relations among vocabularies. Finally, the study is complemented with an analysis of the usage of the different vocabularies, and concludes by proposing a number of metrics.

The most relevant insight is that unsurprisingly the vocabularies with more presence are those used to model Semantic Web data, such as Resource Description Framework, RDF Schema and OWL, as well as broadly used standards as Simple Knowledge Organization System, DCTERMS and DCE. It was also discovered that the most used language is English and the vocabularies are not considered to be highly specialised in a field. Also, there is not a dominant scope of the vocabularies. Regarding the structural analysis, it is concluded that LOV is a heterogeneous network.

The paper provides an empirical analysis of the structure of LOV and the relations between its vocabularies, together with some metrics that may be of help to determine the important vocabularies from a practical perspective. The results are of interest for a better understanding of the evolution and dynamics of the Web of Data, and for applications that attempt to retrieve data in the Linked Data Cloud. These applications can benefit from the insights into the important vocabularies to be supported and the value added when mapping between and using the vocabularies.

The purpose of this paper is to describe an attempt to provide a model for the description of the major aspects of historical interpersonal relationships between celebrities, with a focus on modelling different kinds of evidence about them, from documented and contrasted data to mere rumours.

The approach takes the form of analysis of cases and ontology engineering. A formal schema is provided for the model. The way information can be organized according to this is illustrated with examples about life facts and rumours regarding a popular Hollywood actress.

Some web systems that exploit the representation of personal relationships for purposes such as finding jobs or business opportunities have gained popularity recently. These systems enable users to take advantage of their personal information when combined with information provided by others who are willing to attain similar objectives. However, the importance of that kind of social information can also be applied to other fields in which the information is not directly provided by users, but comes from historical evidence or indirect sources. This is especially relevant to creating knowledge representations that attempt to reconstruct the social networks of celebrities or historical characters.

The model described in this paper can be used to gain insight regarding the historical course of their lives, and of their work relationships, as affected by personal ties. Further, the model could also be used to understand other culture‐bound issues or phenomena in the social sphere.

Large terminologies usually contain a mix of terms that are either generic or domain specific, which makes the use of the terminology itself a difficult task that may limit the positive effects of these systems. The purpose of this paper is to systematically evaluate the degree of domain specificity of the AGROVOC controlled vocabulary terms as a representative of a large terminology in the agricultural domain and discuss the generic/specific boundaries across its hierarchy.

A user-oriented study with domain-experts in conjunction with quantitative and systematic analysis. First an in-depth analysis of AGROVOC was carried out to make a proper selection of terms for the experiment. Then domain-experts were asked to classify the terms according to their domain specificity. An evaluation was conducted to analyse the domain-experts’ results. Finally, the resulting data set was automatically compared with the terms in SUMO, an upper ontology and MILO, a mid-level ontology; to analyse the coincidences.

Results show the existence of a high number of generic terms. The motivation for several of the unclear cases is also depicted. The automatic evaluation showed that there is not a direct way to assess the specificity degree of a term by using SUMO and MILO ontologies, however, it provided additional validation of the results gathered from the domain-experts.

The “domain-analysis” concept has long been discussed and it could be addressed from different perspectives. A resume of these perspectives and an explanation of the approach followed in this experiment is included in the background section.

The authors propose an approach to identify the domain specificity of terms in large domain-specific terminologies and a criterion to measure the overall domain specificity of a knowledge organisation system, based on domain-experts analysis. The authors also provide a first insight about using automated measures to determine the degree to which a given term can be considered domain specific. The resulting data set from the domain-experts’ evaluation can be reused as a gold standard for further research about these automatic measures.

The paper seeks to provide personalized learning objects to adults' educators of special groups (AESG) in a technology‐enhanced learning environment.

The paper presents a definition of specific criteria by which personalization of learning objects is effected. An analysis under the scope of adult education and multicultural education is performed, resulting in the development of tools and a clear path leading to more efficient personalization of learning objects of AESG within an e‐learning environment.

Personalization of learning objects for AESG can be achieved to a much greater extent when the element of compatibility between educator and learner defines content, preceding and mapping with presentation factors.

As the research is focused on AESG, the key notion of compatibility may not be applicable to adult educators of the general public.

The paper offers a path through which learning management systems can provide improved personalization of learning objects addressed to AESG.

The introduction of compatibility between educator and learner as the key element of the educator's profile in order to provide personalized learning objects addressed to AESG opens up new territory. The paper is also useful to the developers of learning management systems addressed to any group with special attributes which strongly affect the learner's profile.

The purpose of this research is to introduce a mapping of the Simple Knowledge Organization Systems (SKOS) Core metadata to an ontology‐based model, whose main aim is to foster the semantic interoperability of different concept schemes.

Research objectives have been achieved through the introduction of a common ground for the definition of concepts, based on shared definitions included in widely used upper ontologies. This effort makes use of a particular upper ontology: OpenCyc, the open source version of Cyc, which is currently one of the most complete general knowledge bases.

An in‐depth study of the SKOS vocabulary has suggested its extension, with the aim of correcting the shortcomings related with SKOS schemes semantic interoperability. However, although such an extension would help avoid ambiguities and enable inter‐thesaurus interoperability, the paper is focused on using a non‐invasive contribution. Non‐invasive in that the SKOS Core should not be modified as a result of this activity, but also, non‐invasive in that current SKOS schemes would not require modifications.

The use of formal representations to provide the SKOS terms with computational semantics, as well as the introduction of an intermediate ontology‐based model built on the SKOS information. Although both proposals stand on one upper ontology (OpenCyc), they could be easily adapted to others, which provides an added value to this research work.

The purpose of this Guest Editorial is to introduce the papers in this special issue.

A brief summary of the main contributions of the papers included in this issue is provided.

The idea of this special issue was an outcome of the organization of activities of the First Online Conference on Metadata and Semantics Research (MTSR'05).

The emphasis on “semantics” addresses the importance of the languages in which metadata records are created, their adequacy for the functions to be enabled and their modular design to adapt to present and future requirements.