[WARNING]: This course substitutes “Big Data Analytics” from the academic year 2022/23 on.

• Luca Pappalardo
  • luca [dot] pappalardo [at] isti [dot] cnr [dot] it
  • KDD Laboratory, ISTI-CNR, Pisa
  • http://www-kdd.isti.cnr.it

• Mirco Nanni
  • mirco [dot] nanni [at] isti [dot] cnr [dot] it
  • KDD Laboratory, ISTI-CNR, Pisa
  • http://www-kdd.isti.cnr.it

• Giuliano Cornacchia, PhD student, University of Pisa
• Giovanni Mauro, PhD student, University of Pisa
• Daniele Gambetta, PhD student, University of Pisa

• Beginning of lectures: 15 September 2022
• End of lectures: 2 December 2022
• Possible lessons recovered: 5–16 December 2022

The lectures will be only in presence and will NOT be live-streamed

A Telegram channel will be used to post news and other stuff related to the course:

• Master theses available on Geospatial Analytics. Contact the professors for further information.
• Exam dates: January 27th, 2023 and February 24th, 2023, in aula Faedo at ISTI-CNR , Pisa.
• Exam instructions:
  • each student will present the project, i.e., submitted notebook(s) (in max. 15 minutes)
  • during/after the presentation, we'll ask some questions about the project
  • and some questions about the course in general (mainly about the topic related to the project)
  • (for the computationally expensive code blocks, please pre-run them and show the outputs only).
• List of projects
• Projects assignment
• Evaluation of homeworks 1.x and 2.x
• Evaluation of homeworks 3.x
• Evaluation of homeworks 4.x, 6.x, and 8.x
• Evaluation of homeworks 5.x and 7.x
• Evaluation of homeworks 9.x and 10.x

The analysis of geographic information, such as those describing human movements, is crucial due to its impact on several aspects of our society, such as disease spreading (e.g., the COVID-19 pandemic), urban planning, well-being, pollution, and more. This course will teach the fundamental concepts and techniques underlying the analysis of geographic and mobility data, presenting data sources (e.g., mobile phone records, GPS traces, geotagged social media posts), data preprocessing techniques, statistical patterns, predicting and generative algorithms, and real-world applications (e.g., diffusion of epidemics, socio-demographics, link prediction in social networks). The course will also provide a practical perspective through the use of advanced geoanalytics Python libraries.

The assessment of the course consists of: (1) an oral exam, aimed to test the knowledge acquired by the student during the course; (2) exercises to be done during the course; (3) the development of a project to test the practical ability acquired during the course.

Topics:

• Spatial Reference Systems
• Data formats
• Trajectory and Flows
• Spatial Tessellations
• Open-source tools for geospatial analysis
• Digital spatial and mobility data
• Preprocessing mobility data
• Privacy issues in mobility data
• individual and collective mobility laws
• Next-location and flow prediction
• Trajectory and flow generation
• Applications

• Fundamentals of Geographical Information Systems
  • Geographic coordinates systems
  • Vector data model
  • Trajectories
  • Spatial Tessellations
  • Flows
  • Practice: Python packages for geospatial analysis (Shapely, GeoPandas, folium, scikit-mobility)
• Digital spatial and mobility data
  • Mobile Phone Data
  • GPS data
  • Social media data
  • Other data (POIs, Road Networks, etc.)
  • Practice: reading and exploring spatial and mobility datasets in Python
• Preprocessing mobility data
  • filtering compression
  • stop detection
  • trajectory segmentation
  • trajectory similarity and clustering
  • Practice: data preprocessing with scikit-mobility

• individual mobility laws/patterns
• collective mobility laws/patterns
• Practice: analyze mobility data with Python

• Prediction
  • Next-location prediction
  • Crowd flow prediction
  • Spatial interpolation
• Generation
  • Trajectory generation
  • Flow generation
• Practice: mobility prediction and generation in Python

• Epidemic spreading (COVID-19)
• Urban segregation models
• Routing and navigation apps
• Traffic simulation with SUMO

The exam can be done on one of the following dates:

• January 27th, 2023
• February 24th, 2023

The exam will start at 9:30 am and will be in Aula Faedo (C-29) at ISTI-CNR, Pisa. Remember to bring an identity document (mandatory) and your “libretto” (if any).

Choose one of the two dates and remember that the project material must be submitted 10 days before the chosen date (i.e., January 17th and February 14th) through this google form.

The exam will consist of a discussion of the project and some questions about the course topics related to the project. The discussion of the project consists of a presentation by the student of the submitted notebook(s).