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The purpose of this paper is to assess whether Europeana can be really seen as the new “Library of Alexandria” for digital resources from the perspective of teachers, academics and researchers that might want to retrieve and reuse those resources for learning purposes.

The authors define a systematic method for studying Europeana digital resources and their potential for reuse in e-learning environments. To achieve this, the authors explore the coverage of digital resources when searching information about a specific area. The paper studies the relevance of the results (thematic coverage) provided by queries targeting the resources’ metadata elements defined by the EDM Europeana model. All the data collected for this study from Europeana digital resources are the result of four explorations since 2012-2016.

The autors found that Europeana as a digital library has good levels of coverage of digital resources for those terms in the AAT thesaurus explored (terms from the “Styles and Periods” subset). This subset was selected as an example of faceted search given that it is a common search topic in the academic environment. However, it is important to remark the use of common vocabulary words provided by participants in order to obtain relevant results of search based on specific knowledge areas defined by AAT terms.

This research used a relatively small sample size of resources which may not be representative of the general size of Europeana digital resources. However, the results are illustrative as they are based on a specific knowledge area of AAT (118 terms) which contains very common topics used in high school courses by students and teachers in the field of art and cultural heritage. The study also aspires to provide a systematic method for conducting future studies in other knowledge areas.

The coverage study aims to analyze if Europeana is a digital library that teachers could use for the development of learning objects in specific knowledge areas, through the reuse of free/open access digital resources.

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 aims to address the issue of poor quality of metadata records describing educational content in Learning Object Repositories (LORs). Through this, it aims to improve the discoverability of learning objects in such LORs through a structured process that supports metadata creation.

This paper presents a proposed metadata quality assessment certification process for LORs. The process was designed as a generic approach that may be customized to fit various application domains.

Initial results from the application of the process in the context of a specific LOR report an improvement of the quality of about 11,000 metadata records. More specifically, metadata completeness for all metadata elements used in the repository under examination was significantly improved from 30 percent to 85 percent.

The main limitation of the findings is that they come from the application of the proposed process on a relatively small repository, which does not allow safe generalizations without further experimental study in bigger ones where resources and requirements scale up.

This paper addresses implications for the development of a repository in the educational domain, identifying issues related to the metadata application profile, the support to domain experts and the mechanisms that may be put in place to support metadata creation.

The value and also the originality of the approach presented lies within the fact the proposed approach quantifies issues related to metadata creation and management by studying actions and perceptions of stakeholders who are involved in the repository lifecycle.

The aim of this paper is discussing about the similarities between the life cycle of knowledge management and the processes in which learning objects are created, evaluated and used.

The paper describes LO and learning designs and depicts their integration into the knowledge life cycle (KLC) of the KMCI, showing the main ontological definitions required to represent the proposed integration, putting them into relation with previous research in the topic.

The main points in that the “learning object” concept can be connected to existing KLC models in order to provide a more comprehensive framework for reuse‐oriented e‐learning and knowledge management.

The paper describes how to integrate learning‐oriented artefacts as part of the organizational context, in particular, as part of the knowledge life cycle (KLC). It also depicts the integration of a reuse‐oriented e‐learning framework into the KLC of the KMCI in the form of ontological definitions.

The purpose of this paper is to describe the provision of existing learning object repositories with enhanced forms of describing digital resources on organic agriculture and agroecology.

The approach followed was to investigate non‐invasive techniques for semantic annotation of learning objects, for which use was made of two tools. The first tool was a software application for the automated classification of learning resources stored in public learning object repositories. The second tool was an ontology in OWL derived from the knowledge in the Agrovoc thesaurus.

Current digital repositories for educational resources and open access archives provide scholars with a number of features, such as the ability to search for materials according to given criteria, or to retrieve the full content of those materials from the repository. Many provide advanced features as well, such as browsing, assessing and collaboratively peer reviewing learning resources, but at the cost of using the specific tools and interfaces provided by each repository.

This research is part of the EU‐funded project Organic.Edunet, aimed at facilitating access, usage and exploitation of digital educational content related to organic agriculture and agroecology (OA&AE). Consequently, knowledge representation, thesauri and the educational resources reported herein are deliberately focused on the OA&AE domain, even though the concepts and techniques utilized may be easily applied in other contexts.

The paper describes two new approaches aimed at enhancing availability of learning resources: the potential use of ontologies for the description of learning resources, and the full use of the classification category in the IEEE LOM metadata standard.

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.

This paper aims to analyse user interfaces for search and collection visualisation and navigation from a usability perspective. The final aim is to offer repository owners a scientific basis to support their decisions when they have to choose an interface that can really help users to effectively locate and visualise resources over large digital collections.

This HCI study is divided into two parts: perception and usability. The first one analysed three perceptual abilities required to use interfaces: attention, retention of information and understanding. The second one was run on an ad hoc generated collection including more than 40,000 European digital resources collected and classified according to a given branch of knowledge in the Art & Architecture Thesaurus.

Although visual interfaces proved useful for certain tasks related to resource discovery and search, and despite the overall good general user opinion, the authors found it necessary to conduct another thorough study to know more about the target users and the amplitude of the collection, as well as to determine the ideal type of interface to implement. All these factors are important for increasing user acceptance and avoiding unnecessary implementation costs.

This research was run on a relatively small sample size of users from Spain and Latin America, which may not be representative of the general population. In similar studies previous knowledge about usability has been reported to introduce bias in the results, so the authors tried to avoid this when selecting the participants.

There are no previous usability studies for the development and implementation of interfaces in digital learning or cultural repositories. The authors' experience highlights the importance of addressing usability aspects a priori, to prevent users from ceasing to use visual interfaces over time, because they do not perceive any benefit from using them.

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.

In the last few years, information and communication technologies (ICTs) and social media have become increasingly relevant to politicians and political parties alike, often used to issue statements or campaigning, among others. At the same time, many citizens have become more involved in politics, partly due to the highly interactive and social environments that the social networking services (SNS) provide. Political events flow through these networks, influencing their users; such events, however, often start offline (outside the online platform) and are, therefore, hard to track. Event studies, a methodology often used in financial and economic studies, can be translated to social networks to help modeling the effect of external events in the network. In the present case, the event study methodology is applied to two sample cases: the tariff war between the United States and China, with multiple responses and retaliations from both sides, and the Brexit referendum. In both cases, the Twitter social networks that arise from users who discuss the respective subjects are analyzed to examine how political events shape and modify the network. Results show how event studies, combined with the possibilities offered by the ICTs both in data retrieval and analysis, can be applied to understand the effect of external political events, allowing researchers to quantitatively track, observe, and analyze the spread of political information over social network platforms. This is a first step toward obtaining a better understanding on how political messages are diffused over social networks and their effects in the network structures and behaviors.

The purpose of this paper is to provide a literature review of the principal formats and frameworks that have been used in the last 20 years to exchange linguistic resources. It aims to give special attention to the most recent approaches to publishing linguistic linked open data on the Web.

Research papers published since 1990 on the use of various formats, standards, frameworks and methods to exchange linguistic information were divided into two main categories: those proposing specific schemas and syntaxes to suit the requirements of a given type of linguistic data (these are referred to as offline approaches), and those adopting the linked data (LD) initiative and the semantic web technologies to support the interoperability of heterogeneous linguistic resources. For each paper, the type of linguistic resource exchanged, the framework/format used, the interoperability approach taken and the related projects were identified.

The information gathered in the survey reflects an increase in recent years in approaches adopting the LD initiative. This is due to the fact that the structural and syntactic issues which arise when addressing the interoperability of linguistic resources can be solved by applying semantic web technologies. What remains an open issue in the field of computational linguistics is the development of knowledge artefacts and mechanisms to support the alignment of the different aspects of linguistic resources in order to guarantee semantic and conceptual interoperability in the linked open data (LOD) cloud. Ontologies have proved to be of great use in achieving this goal.

The research presented here is by no means a comprehensive or all‐inclusive survey of all existing approaches to the exchange of linguistic resources. Rather, the aim was to highlight, analyze and categorize the most significant advances in the field.

This survey has practical implications for computational linguists and for every application requiring new developments in natural language processing. In addition, multilingual issues can be better addressed when semantic interoperability of heterogeneous linguistic resources is achieved.

The paper provides a survey of past and present research and developments addressing the interoperability of linguistic resources, including those where the linked data initiative has been adopted.