Nia Alexandrov

Using Ontology Engineering Methods to Improve Computer Science and Data Science Skills.

Abstract This paper focuses on issues of ontology construction process, Computing Classification System and Data Science domain ontology all used to help not only IT-students but any IT-specialists from industry and academia also to tackle the problems addressing the Big Data and Data Science skills gap. We discuss some methodological aspects of ontology design process and enriching of existing free accessible ontologies and show how suggested methods and software tools help IT-specialists including master students to implement their research work and participate in real world projects. The role of visual data exploration tools for certain issues under discussion and some use cases are discussed.

Computational Science Research Methods for Science Education at PG Level

Abstract The role of Computational Science research methods teaching to science students at PG level is to enhance their research profile developing their abilities to investigate complex problems, analyze the resulting data and use adequately HPC environments and tools for computation and visualization. The paper analyses the current state and proposes a program that encompasses mathematical modelling, data science, advanced algorithms development, parallel programming and visualization tools. It also gives examples of specific scientific domains with explicitly taught and embedded Computational Science subjects.

The Role of Computational Science and Emerging Technologies in the Natural Sciences Education at University Level

Abstract This paper is focused on the role of Computational Science and emerging technologies in the natural sciences education at university level. We outline our Integrated Metacognitive Process Model (IMPM) and our Collaborative Learning approach based on Collaborative Creative Cross-Pollination activity model at postgraduate level. We present our multidisciplinary approach based on the following three components: the existence of multidisciplinary research environment (non-silos departmental culture), computational science research methods as core part of the curricula and collaborative teaching activities facilitated by novel collaborative tools using Collaborative Creative Cross-Pollination. Some results showing the advantages of such an environment and approach are presented. The initial results have shown overall average improvement of the average marks with around 5% plus clear satisfaction of the students as evident from their responses to the course evaluation.

Collaborative Computing and E-learning

In this paper we present the Collaborative Computing Frameworks (CCF) as an integration platform for e-learning. The capabilities of the CCF facilitate mixed modes of delivery and the possibility to integrate already existing e-learning platforms. The CCF features allow to form different groups during the learning process. This coupled with peer-to-peer communication facilities, promotes the efficient implementation of collaborative technologies as an important component of the Dialogue phase of the learning process. The new Collaborative Computing Transport Layer (CCTL) will allow wireless devices to be experimented with for the purposes of e-learning. It is envisaged that this direction will dramatically widen the possibilities for content delivery.

Bridging the HPC Talent Gap with Computational Science Research Methods BRIDGE Workshop at ICCS 2016

Abstract Computational Science, an interdisciplinary field that melds basic sciences, mathematical modelling, quantitative analysis techniques and High-performance Computing (HPC) techniques, is proving integral in addressing the big problems in industries ranging from manufacturing and aerospace, to drug design and risk management. With the advances in HPC and with the advent of Data Science there is a clear and recognized need of researchers and scientists to further develop their skills and in particular: mathematical skills, problem solving and analytical skills.

The E-Learning Grid: Peer-To-Peer Approach

In this paper we present some of the approaches taken by the European E-Learning Grid consortium in building learning Grids. Some of the initial research has been done within the EC GENIUS project, which is a partnership between industry and academia. In this particular paper we focus on how in combining the collaborative and peer-to-peer approach with the relevant pedagogical paradigms we can arrive at the E-Learning Grid.