Studies on Human Behaviour: procuring the data
Welcome to the homepage of the Computer Science edition of Studies on Human Behaviour, course of the Data Science degree at the University of Trento.

News

Website online!

September 20th, 2023 14:50

 

 

This Course will start on Monday, September 11th.

September 1st, 2023 18:00

 

 

Last modification: September 1st, 2023 18:00

Instructions

The Fall 2023 Edition of the course Studies on Human Behaviour is delivered in the classrooms. We will also provide some complementary asynchonous material

 

The idea behind this course is that the students do most of the work during the course duration (up to November) because we believe this should yield considerably better results.

 

 

 

Studying human behaviour involves the analysis of real data about people. Data collection is then a crucial part of the whole process. For this reason, the students of the course will be taught and asked to collect data from their own smartphones via an application developed by the Knowdive group, ideally over a period of 2 weeks. In the calendar you can find the dates of the data collection and when the data will be made avilable (dates can still change). More details will be provided by the professors during the first lessons.

 

Calendar and Material

The course runs from September 11, 2023 till December 28, 2023 with the following schedule:

  • Monday, time 10:30 - 12:30 (Classroom A216 - Povo)

  • Tuesday, time 14:30 - 16:30 (Classroom A216 - Povo)

 

Always check the official University calendar on Moodle.

 

You might want to read the Instructions to understand how to take the course.

 

Notice also the titles and structure of the lessons yet to be delivered might change slightly . The rule of the thumb is: if there are links with materials, things won’t change; if there are no links to the materials, titles and content are just suggestions.

 

Date Id Modality Starts at Material Content of Lesson Professor(s)
11 Sep, 2023 L1 10:30 Course Introduction. Representing and Collecting Behavioral data in Context. F. Giunchiglia, M. Rodas
18 Sep, 2023 L3 10:30 Representing behavioral data in context: behavioral data as KGs. F. Giunchiglia
26 Sep, 2023 L6 14:30 iLog video Representing behavioral data in context: passive data in KG F. Giunchiglia, M. Rodas
02 Oct, 2023 L7 10:30 Representing behavioral data in context: active data in KG. F. Giunchiglia, M. Rodas
03 Oct, 2023 L8 14:30 - Groups: project plan discussion. I. Bison, F. Giunchiglia, M. Tonin, M. Rodas
03 Oct, 2023 - - - - iLog data collection starts. -
09 Oct, 2023 L9 10:30 Collecting behavioral data in the context: data collection. F. Giunchiglia, M. Rodas
10 Oct, 2023 L10 14:30 Collecting behavioral data in the context: data preparation, metadata. F. Giunchiglia, M. Rodas
16 Oct, 2023 L11 10:30 Collecting behavioral data in the context: data integration. F. Giunchiglia
30 Oct, 2023 L15 10:30 Collecting behavioral data in the context: GDPR and Ethics. F. Giunchiglia
31 Oct, 2023 L16 14:30 Groups: Status of work progress F. Giunchiglia, M. Rodas
31 Oct, 2023 - - - - iLog data collection ends. -
27 Nov, 2023 L23 10:30 - Final groups presentations I. Bison, F. Giunchiglia, M. Tonin, M. Rodas
28 Nov, 2023 L24 14:30 - Final groups presentations I. Bison, F. Giunchiglia, M. Tonin, M. Rodas

Syllabus

Course Objectives and Outcomes

The aim of this course is to study the behaviour of people. The course is data intensive and hands on. It covers all the phases from experiment design, data collection, data preparation and data analysis. After a brief theoretical introduction, the course will consist of running real world experiments, on large amounts of data. The exam will consist of presenting the results of the experiment in a public presentation. This inter-disciplinary course bridges competences in sociology, ethics and computer science.

 

 

Suggested Readings

People interested in knowing more details about what we do in this course can refer to these books:

Mainly about Data Science:

  • Bishop, Christopher M. Pattern recognition and machine learning. springer, 2006.

  • Grus, Joel. Data science from scratch: first principles with python. O'Reilly Media, 2019.

  • VanderPlas, Jake. Python data science handbook: Essential tools for working with data. O'Reilly Media, 2016.

 

Mainly about systems and frameworks for Big Data:

  • Carpenter, Jeff, and Eben Hewitt. Cassandra: the definitive guide: distributed data at web scale. O'Reilly Media, 2022.

  • Chambers, Bill, and Matei Zaharia. Spark: The definitive guide: Big data processing made simple. O'Reilly Media, 2018.

 

Teachers

Prof. Ivano Bison

Prof. Fausto Giunchiglia

Dr. Marcelo Rodas Britez

Marco Tonin

Examination and Grading

The examination consists in the preparation of a written paper that will be presented at the end of the course in December.

 

The slots when the paper has to be presented are highlithed in the calendar.

 

IMPORTANT: You must register to ESSE3 in order to take part to the written exam. The registration (mandatory) concludes the exam.

 

Collaboration Opportunities

Multiple positions are available as 150h and internships. They should be considered as the first part of a research project and thesis with the Knowdive group. The general activities of the group are listed on the website (http://knowdive.disi.unitn.it/), while activities already scheduled and available now can be found at http://knowdive.disi.unitn.it/work-with-us/. The 150h activities have variable length and are strictly related to software development: for this reason, knowledge of software development with at least onr programming language is a must. All the activities can also be carried on in a remote fashion.

 

Anyone interested in these opportunities can send an email to knowdive-positions@disi.unitn.it, providing already information about preferences in terms of topics or activities (if known). For 150h activities it is important to provide information about known programming languages with the corresponding level, a value in the range [1 - 5] where 1= basic knowledge, 5= advanced knowledge.

The applications to the “150 ore” program can be done at the link: https://www.unitn.it/servizi/224/collaborazioni-studenti-150-ore