How can you conceptualize and then detect patterns and trends in environmental data? In this module students practise transferable data science skills using a typical applied ecology case study: the study of people's and animal's movement behaviours in natural and built environments. This module examines typical data analysis work-flow, starting with data capture, followed by pre-processing (cleaning, filtering, aggregating, reshaping data), analytical modeling, and finally visualisation of outcomes, uing the R statistics and visualization environment.
Schwerpunkte
Modelling matters
- Introduction into data science
- Conceptual spatial models
- Structuring data
Defining and detecting patterns
- Preprocessing and data issues
- Similarity and segmentation
- Pattern detection algorithms
Contextualizing patterns
- Relating Data with Joins
- Overlay operations
- Integrating multi-source data
Presenting patterns
- Visualization and visual analytics
- Exploratory data analysis
Studieninformation
Dieses Modul wird auf Englisch durchgeführt.