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Data mining and analyzing of urban structures as contribution to European Union studies

Funder: European CommissionProject code: 620791-EPP-1-2020-1-CZ-EPPJMO-MODULE
Funded under: ERASMUS+ | Jean Monnet Activities | Jean Monnet Modules Funder Contribution: 29,660.4 EUR

Data mining and analyzing of urban structures as contribution to European Union studies

Description

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 the health. A combination of dataset makes the opportunity to compare countries and districts from the point of the wellbeing 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 course Data Mining, and the second is Advanced Processing of Geodata (at 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. The main benefit is that students and both young researchers (doctoral students involved in teaching J. Masopust and K. Macků) will be familiar not only with computational methods of data mining but they will become familiar with how to use Europen Data. The ability to process data by advanced computational methods increases their competitiveness, employability and improved career prospects.

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