PurposeSince the early 1980s, a paradigm shift, caused by the work undertaken in the field of cognitive psychology, has occurred. This shift is known as the move from teacher-centered instruction to learner-centered or learning-centered instruction, and emphasizes the importance of building new knowledge on previous ones, interacting with peers, making meaningful and reflective learning and being engaged in his own path to foster learning. This new vision of teaching has created a need for new learning and assessment instruments that are better adapted to these pedagogical realities. In this context, the electronic portfolio or e-portfolio is one of the most versatile and effective tools that have been proposed for this purpose. More specifically, the interest in e-portfolios has grown considerably with the emergence of the competency-based approach and portfolio-based competency assessments. The purpose of this paper is to describe a semantic-based representation of e-portfolios, defined on the basis of official e-portfolio standards and specifications. Moreover, a comparative study of several well-known e-portfolio solutions has been carried out based on different facets, such as functional features, technical and organizational features. The objective is to identify those features that are mostly supported by e-portfolio solution providers and accordingly to gain a fairly accurate idea of the common structure of e-portfolios. In addition, the authors take advantage of an already implemented ontological model describing competency-related characteristics of learners and learning objects and combine it with the e-portfolio ontology, with a view to support a more reliable and authentic competency assessment.Design/methodology/approachThe proposed e-portfolio ontology was built following the ontology development methodology Methontology (Fernandez et al., 1997). In addition, it was constructed using the Protégé ontology environment (Protégé, 2007) and was implemented in OWL (Web Ontology Language) (Antoniou and Harmelen, 2004).FindingsThe proposed e-portfolio ontology provides humans with a shared vocabulary that enables capturing the most important elements in e-portfolios and serves as the basis for the semantic interoperability for machines.Originality/valueThe main advantage of the e-portfolio ontology lies in its ability to provide a common and semantically enriched representation of e-portfolio artifacts, thus facilitating the interoperability and exchange of competency evidences between different learning systems and platforms. In addition, capturing the semantics of e-portfolios helps to make them utilizable by intelligent applications.

PurposeThe purpose of this paper is to focus on the quality of the connections (linkset) among thesauri published as Linked Data on the Web. It extends the cross-walking measures with two new measures able to evaluate the enrichment brought by the information reached through the linkset (lexical enrichment, browsing space enrichment). It fosters the adoption of cross-walking linkset quality measures besides the well-known and deployed cardinality-based measures (linkset cardinality and linkset coverage).Design/methodology/approachThe paper applies the linkset measures to the Linked Thesaurus fRamework for Environment (LusTRE). LusTRE is selected as testbed as it is encoded using a Simple Knowledge Organisation System (SKOS) published as Linked Data, and it explicitly exploits the cross-walking measures on its validated linksets.FindingsThe application on LusTRE offers an insight of the complementarities among the considered linkset measures. In particular, it shows that the cross-walking measures deepen the cardinality-based measures analysing quality facets that were not previously considered. The actual value of LusTRE’s linksets regarding the improvement of multilingualism and concept spaces is assessed.Research limitations/implicationsThe paper considers skos:exactMatch linksets, which belong to a rather specific but a quite common kind of linkset. The cross-walking measures explicitly assume correctness and completeness of linksets. Third party approaches and tools can help to meet the above assumptions.Originality/valueThis paper fulfils an identified need to study the quality of linksets. Several approaches formalise and evaluate Linked Data quality focusing on data set quality but disregarding the other essential component: the connection among data.

PurposeProducing meeting documents requires an instantaneous recorder during meetings, which costs extra human resources and takes time to amend the file. However, a high-quality meeting document can enable users to recall the meeting content efficiently. The paper aims to discuss these issues.Design/methodology/approachAn application based on this framework is developed to help the users find topics and obtain summarizations of meeting contents without extra effort. This app uses the Bluemix speech recognizer to obtain speech transcripts. It then combines latent Dirichlet allocation and a TextTiling algorithm with the speech script of meetings to detect boundaries between different topics and evaluate the topics in each segment. TextTeaser, an open API based on a feature-based approach, is then used to summarize the speech transcripts.FindingsThe results indicate that the summaries generated by the machine are 85 percent similar to the records written by humankind.Originality/valueTo reduce the human effort in generating meeting reports, this paper presents a framework to record and analyze meeting contents automatically by voice recognition, topic detection, and extractive summarization.