The aim of the project is the innovation of two courses of master studies of Geoinformatics and Cartography at Palacký University in Olomouc. The innovated topics are about processing European Union digital data by Data Mining, statistics and spatial analysis methods. There is a freely accessible wide range of collection of European Data, namely Eurostat data and datasets by Copernicus Land Monitoring Service. There is an opportunity to process data about urban structures from European Urban Atlas. Road network data available through INSPIRE policy or Open Street Map service are very often used for spatial evaluation of inhabitant mobility in urban structures, opportunities for walking to uplift health. A combination of datasets makes the opportunity to compare countries and districts from the point of the well-being of European inhabitants expressed by the life quality index. Furthermore, the evaluation of liveable cities arises as a topical issue in European countries and projects based on it can help to increase the quality of life in the EU. The use of the mentioned datasets follows the initiative of Open Access Infrastructure for Research in Europe.
The first proposed course is the course Data Mining (in the winter semester), and the second is Advanced Processing of Geodata (in the summer semester) at the first grade of master study. The innovation of both subjects fosters the introduction of a European Union angle into non-EU related study Geoinformatics and Cartography. The advantage is that students have a good background in geography from bachelor studies of Geoinformatics and Geography. Additionally, students are familiar with statistical software R Studio, data mining software Orange and software ArcGIS for spatial data processing by previous basic courses. There are no barriers to start to analyse data through advanced data mining techniques.
Graduate students of master study are most often employed in the Czech government or international institutions. The ability to process data by advanced computational methods increases their competitiveness, employability and improved career prospects. Graduates became, thank the Jean Monnet Module project, expert in advanced processing of European statistic and spatial data. Subsequently, the European context and expert knowledge of how to process and analyse the spatial data, concerning urban structures, mobility data and wellbeing data are valuable for them.
Both mentioned courses are aimed to acquire the top skills on how to process the statistics and spatial data of the European Union by data mining methods and machine learning.
The main benefit is that students and both young researchers (doctoral student involved in teaching Jan Masopust and postdoctoral student Karel Macků) will be familiar not only with computational methods of data mining but they will become familiar with how to use Copernicus Urban Data, Eurostat data, Open Street Map and other datasets. The final interpretation as the last phase of data mining is the most important output of innovative lectures. It is not only important to know how to use some methods (like associations rule, decision tree, the reduction of data dimensions, and identification of clusters) but process it on real data and make the final interpretation. The topics foster the engagement of young academics in teaching and research on European subjects. It is valuable also for students of Geoinformatics who do not automatically come into contact with European Union studies.
The project has a multidisciplinary character due to the connection of advanced computational methods (data mining and spatial analyses) and European land use and statistic data. The teaching group consists of experienced expert Zdena Dobešová in data mining and spatial analysis and two young specialists – K. Macků and J. Masopust, with experience in processing a wide range of European data sets with experience in how to interpret them. Therefore, students became skilled data analysts in the European context after finishing the courses. The results of the processing data could serve politicians and governments at national and international levels in their decisions. The outcome will be the innovation of two courses by practical lectures on processing data connected with theoretical topics. New practical manuals will describe the practical lectures for the students. Moreover, the output results will be published in scientific articles in conferences and scientific journals. The indicators are two innovated courses, presentations for theoretical lectures, manuals for practical lectures, open workshops, a student diploma thesis and scientific articles. Both innovated courses will be offered also for students from other departments and study branches at Palacky University (like international studies, geography, informatics etc.) during the open credit system and, in addition, for the abroad hosting ERASMUS + students.
