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

Цифровые технологии вовлечения школьников в учебный процесс: геймификация и сторителлинг

Цель исследования заключается в том, чтобы на полученном эмпирическом материале проанализировать возможности применения цифровых технологий с целью вовлечения школьников в учебный процесс. В процессе исследования рассмотрен уровень познавательной мотивации учения школьников и их отношение к учению в условиях применения цифровых и дистанционных технологий на основе сетевых ресурсов Интернет

The European Data Science Academy: Bridging the Data Science Skills Gap with Open Courseware

As a global society, we are producing data at an incredible rate, fuelled by the increasing ubiquity of the Web, and stoked by social media, sensors, and mobile devices. However, as the amount of produced data continues to increase, so does the demand for practitioners who have the necessary skills to manage and manipulate this data. The European Data Science Academy (EDSA) is looking to bridge the data science skills gap by developing multimodal open courseware tailored to the real needs of data practitioners. The EDSA courseware is 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 data science community through continuous feedback

Open Data Sectors and Communities: Education

Open data can help researchers and policy-makers understand the education landscape, provide information for parents and children about education facilities and their performance, and serve as a key element in the creation of open educational resources (OER). Attention must move beyond the simple availability of data on education to also question how the data is contextualised, presented, and used to ensure it does not result in the reinforcement of pre-existing biases and social divides. There has been relatively limited intersection to date between the open education and open data communities. There are opportunities for future strengthening of these links, increasing the use of open data as a key educational resource, and supporting more applied civic education

Education

Key Points * Open data can help researchers and policy makers understand the education landscape, can provide information for parents and children about education facilities and their performance, and can be used as an input into education: making a connection between open data and Open Educational Resources (OER). * Attention must focus beyond the simple availability of education data to also question how the data is shaped, presented, and used. This should address the ways in which, without wider policy interventions, making data available about education performance may ultimately reinforce stigma and social divides. * There has been relatively limited overlap between OER and Open Data communities, although since 2013, the Open Knowledge Education Working Group has sought to build connections between them. There are opportunities for future strengthening of these links, increasing the use of open data as a key educational resource, and supporting more applied civic education

A PRACTICE OF OPEN DATA ADOPTION TO «PROGRAMMING» COURSE OF «SOFTWARE ENGINEERING» BACHELOR PROGRAM

Abstract. The aim of the publication is to show the possibilities of use of open data in teaching courses of programming. Methods. The results of adoption of the technique presented in the publication to the process of training in programming at the first year of the course «Program Engineering» are received by a comparative research and analysed by methods of descriptive statistics.Results and scientific novelty. The technique of the use of open data sets when developing training and control tasks on programming for students of a bachelor degree of information and technological educational program specialization is offered; standard tasks templates are presented. The application of open data in the educational purposes is a rather new direction in education that considerably enables to improve the quality of training of an expert in the field of computer sciences: to bring closer educational tasks to real; to increase variability of control tasks; to increase motivation of students. However, along with positive characteristics of the presented method, there are some difficulties of the method introduction in educational process. The authors have formulated the problems arising when using open data; possible ways of their decision are shown.Practical significance. The results received during the research show the possibilities of further expansion of application of open data in education. The described practical experience of training in programming can be partially or completely used by teachers of other training courses.Цель работы – показать возможности использования открытых данных в преподавании курсов программирования. Методы и методики. Результаты внедрения представленной в публикации методики в процесс обучения программированию на первом курсе специальности «Программная инженерия» получены путем сравнительного исследования и проанализированы методами описательной статистики. Результаты и научная новизна. Предложена методика использования открытых наборов данных при разработке тренировочных и контрольных заданий по программированию для студентов бакалавриата информационно-технологического профиля; приведены шаблоны типовых заданий. Применение открытых данных в учебных целях – достаточно новое направление в образовании, позволяющее значительно улучшить качество подготовки специалиста в области компьютерных наук: приблизить учебные задачи к реальным; увеличить вариативность контрольных заданий; повысить мотивацию студентов. Однако наряду с позитивными характеристиками метода имеется ряд трудностей его внедрения в учебный процесс. Авторами сформулированы проблемы, возникающие при использовании открытых данных, и показаны возможные пути их решения. Практическая значимость. Полученные в ходе исследования результаты демонстрируют возможности дальнейшего расширения применения открытых данных в образовании. Описанный практический опыт обучения программированию может быть частично или полностью использован преподавателями других учебных курсов.

Towards Semantic APIs for Research Data Services

Die schnelle Entwicklung der Internet- und Web-Technologie verändert den Stand der Technik in der Kommunikation von Wissen oder  Forschungsergebnissen. Insbesondere werden semantische Technologien, verknüpfte und offene Daten zu entscheidenden Faktoren für einen  erfolgreichen und effizienten Forschungsfortschritt. Zuerst definiere ich den Research Data Service (RDS) und diskutiere typische aktuelle  und mögliche zukünftige Nutzungsszenarien mit RDS. Darüber hinaus bespreche ich den Stand der Technik in den Bereichen semantische Dienstleistung und Datenanmerkung und API-Konstruktion sowie infrastrukturelle Lösungen, die für die RDS-Realisierung anwendbar sind. Zum Schluss werden noch innovative Methoden der Online-Verbreitung, Förderung und effizienten Kommunikation der Forschung diskutiert.Rapid development of Internet and Web technology is changing the state of the art in communication of knowledge, or results of research activities. Particularly, Semantic technology, linked and open data become key enablers for successful and efficient progress in research. At first, I define the research data service (RDS) and discuss typical current and possible future usage scenarios involving RDS. Further, I discuss the state of the art in the areas of semantic service and data annotation and API construction, as well as infrastructural solutions, applicable for RDS realisation. At last, innovative methods of online dissemination, promotion and efficient communication of research are discussed

Designing Heterotopic Transversal Equitable Foundations for Open Knowledge: Access, Freedom & e/Quality

Following on the publications based on Smit’s 2017 International Open Access lecture (cf. Smit & Chetty 2018a; and 2018b), we capture some aspects from his 2018 presentation, in this article. It further develops his exploration of the significance of Michel Foucault’s triad, subject – communication – knowledge-power production in the digital paradigm, or e-episteme, in terms of knowledge-power networks (KPNs). For this, the article has two main parts. Firstly, it provides a theoretical framework for the empirical interpretation of the 2018 international topic for the Open Access week, seminally, incorporating the no-tions of the ‘heterotopic’ and ‘transversal’. Secondly, in South Africa’s ascendant history into openness, as a free country, it provides a sample of three significant events in our affirmative genealogy, or genealogies, of freedom. These are, access to the full participation in, or ‘contribution’ to, world civilization, or world information-, data-, or knowledge-power, or science-power productions, á la Anton Lembede; freedom as founded in the Universal Declaration of Hu-man Rights (UDHR); and equity/ equality/ e/Quality, as founded in ‘The Free-dom Charter’. As such, the advocacy for access, freedom, and equality in South Africa’s affirmative genealogy of freedom, are three of the seminal elements, and historical empirical events, for South Africa’s entry into its free democratic dispensation, in 1994. The presentation was dedicated to the international celebration of the seventieth year of the founding of the UDHR, in 1948

COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package

OntoSIDES: Ontology-based student progress monitoring on the national evaluation system of French Medical Schools

International audienceWe introduce OntoSIDES, the core of an ontology-based learning management system in Medicine, in which theeducational content, the traces of students’ activities and the correction of exams are linked and related to itemsof an official reference program in a unified RDF data model. OntoSIDES is an RDF knowledge base comprised ofa lightweight domain ontology that serves as a pivot high-level vocabulary of the query interface with users, andof a dataset made of factual statements relating individual entities to classes and properties of the ontology.Thanks to an automatic mapping-based data materialization and rule-based data saturation, OntoSIDES containsaround 8 millions triples to date, and provides an integrated access to useful information for student progressmonitoring, using a powerful query language (namely SPARQL) allowing users to express their specific needs ofdata exploration and analysis. Since we do not expect end-users to master the raw syntax of SPARQL and toexpress directly complex queries in SPARQL, we have designed a set of parametrized queries that users caninstantiate through a user-friendly interface