There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

The PASCAL Visual Object Classes Challenge

being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web—known as the Semantic Web—which has been defined as “the conceptual structuring of the Web in an explicit machine-readable way.”1 This definition does not differ too much from the one used for defining an ontology: “An ontology is an explicit, machinereadable specification of a shared conceptualization.”2 In fact, new ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires—solving the heterogeneous data exchange in this heterogeneous environment. Here, we don’t decide which language is best of the Semantic Web. Rather, our goal is to help developers find the most suitable language for their representation needs.

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Ontology languages for the Semantic Web

As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.

Recommender Systems for Technology Enhanced Learning: Research Trends and Applications

Purpose - Research in the area of technology-enhanced learning (TEL) throughout the last decade has largely focused on sharing and reusing educational resources and data. This effort has led to a fragmented landscape of competing metadata schemas, or interface mechanisms. More recently, semantic technologies were taken into account to improve interoperability. The linked data approach has emerged as the de facto standard for sharing data on the web. To this end, it is obvious that the application of linked data principles offers a large potential to solve interoperability issues in the field of TEL. This paper aims to address this issue. Design/methodology/approach - In this paper, approaches are surveyed that are aimed towards a vision of linked education, i.e. education which exploits educational web data. It particularly considers the exploitation of the wealth of already existing TEL data on the web by allowing its exposure as linked data and by taking into account automated enrichment and interlinking techniques to provide rich and well-interlinked data for the educational domain. Findings - So far web-scale integration of educational resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. However, linked data principles increasingly are recognized by the TEL community. The paper provides a structured assessment and classification of existing challenges and approaches, serving as potential guideline for researchers and practitioners in the field. Originality/value - Being one of the first comprehensive surveys on the topic of linked data for education, the paper has the potential to become a widely recognized reference publication in the area.

Interlinking Educational Resources and the Web of Data: A Survey of Challenges and Approaches

The wide availability of educational resources is a common objective for universities, libraries, archives and other knowledge-intensive institutions. Although generic metadata specifications (such as Dublin Core) seem to fulfill the need for documenting web-distributed objects, educational resources demand a more specialized treatment and characterization. In this article we focus on the use of learning-object specific metadata in digital repositories, as they are primarily incarnated in the LOM (learning object metadata) standard. We review relevant standards and practices, especially noting the importance of application profiling paradigms. A widespread institutional repository platform is offered by DSpace. We discuss our implementation of LOM metadata in this system as well as our interoperability extensions. To this end, we propose a potential LOM to DC mapping that we have put into use in DSpace. Finally, we introduce our implementation of an LOM ontology, as a basis for delivering Semantic Web services over educational resources

The Use of Metadata for Educational Resources in Digital Repositories: practices and Perspectives

Open educational resources are currently becoming increasingly available from a multitude of sources and are consequently annotated in many diverse ways. Interoperability concerns that naturally ar...

A learning object ontology repository to support annotation and discovery of educational resources using semantic thesauri

Information and knowledge retrieval are today some of the main assets of the Semantic Web. However, a notable immaturity still exists, as to what tools, methods and standards may be used to effectively achieve these goals. No matter what approach is actually followed, querying Semantic Web information often requires deep knowledge of the ontological syntax, the querying protocol and the knowledge base structure as well as a careful elaboration of the query itself, in order to extract the desired results. In this paper, we propose a structured semantic query interface that helps to construct and submit entailment-based queries in an intuitive way. It is designed so as to capture the meaning of the intended user query, regardless of the formalism actually being used, and to transparently formulate one in reasoner-compatible format. This interface has been deployed on top of the semantic search prototype of the DSpace digital repository system.

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A structured semantic query interface for reasoning-based search and retrieval

The growing availability of Linked Data and other structured information on the Web does not keep pace with the rich semantic descriptions and conceptual associations that would be necessary for direct deployment of user-tailored services. In contrast, the more complex descriptions become, the harder it is to reason about them. To show the efficacy of a potential compromise between the two, in this paper we propose an intelligent and scalable personalization service, built upon the idea of combining Linked Data with Semantic Web rules. This service is mashing up information from different bookstores, and suggests users with personalized data according to their preferences, which in turn are modeled by a set of Semantic Web rules. This information is made available as Linked Data, thus enabling third-party recipients to consume knowledge-enhanced information.

Dimitrios A. Koutsomitropoulos

Papers

The Use of Metadata for Educational Resources in Digital Repositories: practices and Perspectives

A learning object ontology repository to support annotation and discovery of educational resources using semantic thesauri

A structured semantic query interface for reasoning-based search and retrieval

A Mashup Personalization Service Based on Semantic Web Rules and Linked Data

A standards-based ontology and support for Big Data Analytics in the insurance industry