What is Spatial Data Science?

Data Science

science of extracting meaningful information from data

Data Science is about

data collection

data cleaning and preprocessing

exploratory data analysis

data visualization

data modeling

descriptive analytics

predictive analytics

prescriptive analytics

machine learning

deep learning

Different

data

New data revolution

Raw data

Large data

Exotic data

Strange data

tools

Computational revolution

Python

R

SQL

JavaScript

methods

Methodological evolution

The old in the new world

The new derived from the old

The new

culture

Open science

Open data

Open tools

Open methods

Open mind

Spatial Data Science

data science that treats location, distance, and spatial interaction as core aspects of the data and employs specialised methods and software to store, retrieve, explore, analyse, visualise and learn from such data.

Spatial Data Science vs GIS

advanced statistical and computational techniques to analyse and derive insights from spatial data

deeper in computation

complex data pipelines (unlimited power of coding)

Spatial data science often draws from GIS but extends its capabilities by incorporating more extensive data analysis and modelling techniques

different toolkit

though some overlaps in the Esri world do exist

This course

compass

not a satnav

What the course IS about?

An overview of the ecosystem

A way to build an intuition

A kickstart of your journey

What the course IS NOT about?

Comprehensive guide

Definitive guide

Deep dive into math and stats

Idea behind the course design

A wide variety of methods and tools

Focus on application and use

Real-world data

Each class is divided into 3 parts

Concepts

Hands-on

Exercise

A lot of options to continue

on your own

Contents

Python

Second best tool for everything

Standard in GIS and Data Science

Easy-to-read language

12 lessons in 12 weeks

Structure

3 lessons on basics

3 lessons on exploratory data analysis

6 lessons on data science techniques

Structure

Introduction

Open Data Science

Spatial data

Spatial weights

ESDA

Point patterns

Clustering

Raster data

Interpolation

Linear regression

Non-linear regression

Classification

Organisation

Website

martinfleischmann.net/sds

Discord

Evaluation

Exercises

Computational essay

An essay whose narrative is supported by code and its results, which are part of the essay.

2,500-5,000 words

equivalent

1,500 words

5 maps

2 tables

code

Topic

Define your task

A Barcelona case

English or Czech language

Use of generative AI

It can be helpful but be cautious.

Helps more advanced users than beginners.

Can produce erroneous code.

Often results in too verbose and inefficient code.

Does not pick up the latest changes.

Acknowledge if used for the final assignment.

Contact

martin.fleischmann@natur.cuni.cz

Discord!