Customisable Data Science Educational Environment: From Competences Management and Curriculum Design to Virtual Labs On-Demand

Abstract

Data Science is an emerging field of science, which requires a multidisciplinary approach and is based on the Big Data and data intensive technologies that both provide a basis for effective use of the data driven research and economy models. Modern data driven research and industry require new types of specialists that are capable to support all stages of the data lifecycle from data production and input to data processing and actionable results delivery, visualisation and reporting, which can be jointly defined as the Data Science professions family. The education and training of Data Scientists currently lacks a commonly accepted, harmonized instructional model that reflects all multidisciplinary knowledge and competences that are required from the Data Science practitioners in modern, data driven research and the digital economy. The educational model and approach should also solve different aspects of the future professionals that includes both theoretical knowledge and practical skills that must be supported by corresponding education infrastructure and educational labs environment. In modern conditions with the fast technology change and strong skills demand, the Data Science education and training should be customizable and delivered in multiple form, also providing sufficient data labs facilities for practical training. This paper discussed both aspects: building customizable Data Science curriculum for different types of learners and proposing a hybrid model for virtual labs that can combine local university facility and use cloud based Big Data and Data analytics facilities and services on demand. The proposed approach is based on using the EDISON Data Science Framework (EDSF) developed in the EU funded Project EDISON and CYCLONE cloud automation systems being developed in another EU funded project CYCLONE.

Big and open linked data analytics: a study on changing roles and skills in the higher educational process

“…making the collection of educational data, its processes of calculation and its consequences into an automated, real-time and recursive process (Williamson, 2016). On the other hand, new skills are required to gain valuable information and a deeper insight into the processes taking place around educational data analytics Demchenko et al, 2017;Máchová et al, 2016).…”

“…Although the learners and educators are still the key roles in the educational process, the pressure is on their skills. The research on this topic is mostly dealing with existing stakeholders and how they can profit from these new approaches and technologies (Aghabozorgi et al, 2014;Cen et al, 2015;Chatti et al, 2017;Demchenko et al, 2017;Klašnja-Milićević et al, 2017;Macfadyen et al, 2014;Sedkaoui, 2018), but the question remains on what should they do or learn to make this happen. For this reason, new stakeholders with respective roles have to be involved in this process to ensure that it meets technical and societal needs for working with BOLED analytics and enables to share knowledge and skills among them.…”

“…According to Mikroyannidis et al (2016), organizations "need their employees to understand the legal and economic aspects of datadriven business development, as a prerequisite for the creation of product and services that turn open and corporate data assets into decision-making insight and commercial value." As reported by Demchenko et al (2017) and Gupta et al (2015), a commonly accepted and harmonized instructional model that reflects all multidisciplinary knowledge and competencies is required. The educational model and approach have to solve different aspects and overlaps between topics that include both theoretical knowledge and practical skills.…”

“…At the same time, many of learning materials as well as courses and lectures are open and available anywhere as Open Educational Resources (OER), mostly in the form of interactive (tutorial) courseware and Massive Open Online Courses (MOOC), which combine different OER, e-learning methods and social networks culminating in an online learning experience. Such evolution influences today's educational systems and requires to build data-centred skills (Aikat et al, 2017;Colpaert, 2018;Demchenko et al, 2017;Khriyenko & Khriyenko, 2013;Klašnja-Milićević et al, 2017;Li & Ni, 2015;Mikroyannidis, Domingue, Maleshkova, Norton, & Simperl, 2016). It changes learning needs and requires a reorientation toward the development of novel approaches and advancements in higher educational institutions (Gupta, Goul, & Dinter, 2015;Sedkaoui, 2018).…”

“…It changes learning needs and requires a reorientation toward the development of novel approaches and advancements in higher educational institutions (Gupta, Goul, & Dinter, 2015;Sedkaoui, 2018). These demands then create the need for systemic change in education focusing on preparing new specialists (data-related roles) and training for new skills (Coccoli, Maresca, & Stanganelli, 2017;Demchenko et al, 2014;Demchenko et al, 2017). According to the findings of the recent study of Mikalef, Giannakos, Pappas, and Krogstie (2018), there is a gap between the skills needed and the ones taught in academic curricula.…”