Multidisciplinary Guest Lectures

A series of lectures by experts across the University, talking about the intersection of Web science and their discipline

Semantic web service offer discovery for e-commerce

Semantic Web Services (SWS) are an important part of the Semantic Web, traditionally focused on discovery and composition of e-services. In the area of e-commerce services, it is necessary to go past the granularity of service discovery and also to consider discovering the actual offers provided by a service. Nevertheless, Semantic Web Services research has only recently started to consider offer discovery. In this paper, we present a solution for offer discovery that uses WSMO-Lite, the new lightweight semantic Web service annotation framework

a survey

Building ontologies in a collaborative and increasingly community-driven fashion has become a central paradigm of modern ontology engineering. This understanding of ontologies and ontology engineering processes is the result of intensive theoretical and empirical research within the Semantic Web community, supported by technology developments such as Web 2.0. Over 6 years after the publication of the first methodology for collaborative ontology engineering, it is generally acknowledged that, in order to be useful, but also economically feasible, ontologies should be developed and maintained in a community-driven manner, with the help of fully-fledged environments providing dedicated support for collaboration and user participation. Wikis, and similar communication and collaboration platforms enabling ontology stakeholders to exchange ideas and discuss modeling decisions are probably the most important technological components of such environments. In addition, process-driven methodologies assist the ontology engineering team throughout the ontology life cycle, and provide empirically grounded best practices and guidelines for optimizing ontology development results in real-world projects. The goal of this article is to analyze the state of the art in the field of collaborative ontology engineering. We will survey several of the most outstanding methodologies, methods and techniques that have emerged in the last years, and present the most popular development environments, which can be utilized to carry out, or facilitate specific activities within the methodologies. A discussion of the open issues identified concludes the survey and provides a roadmap for future research and development in this lively and promising field

Collaborative ontology engineering: a survey

Building ontologies in a collaborative and increasingly community-driven fashion has become a central paradigm of modern ontology engineering. This understanding of ontologies and ontology engineering processes is the result of intensive theoretical and empirical research within the Semantic Web community, supported by technology developments such as Web 2.0. Over 6 years after the publication of the first methodology for collaborative ontology engineering, it is generally acknowledged that, in order to be useful, but also economically feasible, ontologies should be developed and maintained in a community-driven manner, with the help of fully-fledged environments providing dedicated support for collaboration and user participation. Wikis, and similar communication and collaboration platforms enabling ontology stakeholders to exchange ideas and discuss modeling decisions are probably the most important technological components of such environments. In addition, process-driven methodologies assist the ontology engineering team throughout the ontology life cycle, and provide empirically grounded best practices and guidelines for optimizing ontology development results in real-world projects. The goal of this article is to analyze the state of the art in the field of collaborative ontology engineering. We will survey several of the most outstanding methodologies, methods and techniques that have emerged in the last years, and present the most popular development environments, which can be utilized to carry out, or facilitate specific activities within the methodologies. A discussion of the open issues identified concludes the survey and provides a roadmap for future research and development in this lively and promising fiel

Designing and Delivering a Curriculum for Data Science Education across Europe

Data is currently being produced at an incredible rate globally, fuelled by the increasing ubiquity of the Web, and stoked by social media, sensors, and mobile devices. However, as the amount of available data continues to increase, so does the demand for professionals who have the necessary skills to manage and manipulate this data. This paper presents the European Data Science Academy (EDSA), an initiative for bridging the data science skills gap across Europe and training a new generation of world-leading data scientists. The EDSA project has established a rigorous process and a set of best practices for the production and delivery of curricula for data science. Additionally, the project’s efforts are dedicated to linking the demand for data science skills with the supply of learning resources that offer these skills

Developing a curriculum of open educational resources for Linked Data

The EUCLID project is developing an educational curriculum about Linked Data, supported by multimodal Open Educational Resources (OERs) tailored to the real needs of data practitioners. The EUCLID OERs facilitate professional training for data practitioners, who aim to use Linked Data in their daily work. The EUCLID OERs are implemented as a combination of living learning materials and activities (eBook, online courses, webinars, face-to-face training), produced via a rigorous process and validated by the user community through continuous feedback