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One of the most interesting challenges in terms of Cartography in XXI century is big data visualization. Yes, we now have access to many courses, YouTube videos, books and articles on big data, but what about telling a story with it? Or showing a trend, a process with 100000 rows of data?
Actually having to visualize statistical data could be mission impossible, if you don't have some soft skills, understanding of colors and emotions they drive into people and many other non-geographic and non-cartographic topics. SO,
here comes your aesthetics
If you want to succeed in data viz field, you have to know a little bit of:
- colors - what feelings they spark in people
- psychology - what are the limits of people's perceptions
- presentation methods
- graphical representation of real world objects
I've put a little bit of all listed above
into my online course Introduction to Geospatial Data Visualization. It's a complex topic so you need to have broad understanding of many other stuff BEFORE learning how to deal with Big Data. And remember that learning how to work with a specific software IS NOT what's important. The important thing is to understand the basic ideas standing in the field of spatial data visualization, and after that to be able to work with any type of software you want. Don't be a slave to one or other software.
About the course
The Introduction to geospatial data visualization course contains topics that cover a broad understanding of spatial data visualization. The students will understand what data visualization is and why it is important for geospatial professionals in the XXI century. The difference between data and information is discussed and the four main steps of creating a good data visualization. Attributes are widely discussed as they are the most important factor in data classification techniques. Mapping methods and basic rules for designing maps are covered as part of the traditional cartography lessons.
For taking this course the students must have a basic understanding of GIS, vector and raster data, geometry and attributes.