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Week - 1 |
Basic concepts; information hierarchy, spatial data and why information is important. |
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Week - 2 |
Relationship between spatial data and decision making; examples of decision making with spatial data in public and private sectors (disaster management, logistics, marketing) |
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Week - 3 |
Data-driven strategy development |
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Week - 4 |
Data sources and quality assessment; open data portals, data quality and data selection considerations |
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Week - 5 |
EN: Practice 1 - Open source data application (OSM data upload etc.) |
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Week - 6 |
Data collection and pre-processing; integration of survey IOT, social media data into spatial analysis |
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Week - 7 |
Data visualization and effective presentation; designing understandable maps for decision makers |
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Week - 8 |
Data visualization and effective presentation; dashboard and storymapping |
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Week - 9 |
EN: Practice 2- Data visualization competition |
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Week - 10 |
Basic statistics and spatial pattern analysis; density (population, traffic), clustering (hotspot) and correlation analysis maps |
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Week - 11 |
Data-driven policy development; use of spatial data in public policies, impact analysis |
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Week - 12 |
Correct evaluation of data analysis |
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Week - 13 |
Practice 3 - Evaluating selected real-life scenarios according to the criteria learned in the course |
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Week - 14 |
Practice 4 - Designing a business model based on spatial data and convincing the class of the model |
Eskisehir Technical University Info Package