Summer School – Challenges for the XXI century: 2nd edition

Summer School – Challenges for the XXI century: 2nd edition

Summer school Valencia 2019The University of Valencia will be hosting its 2st Summer SchoolChallenges for the XXI century: data, information and communication”. This Summer School faces the present data driven revolution with a view to understanding its scope.

Target group: Master’s degree and PhD students in Economics, Engineering, Journalism, Sciences, Computing and Telecommunications, Marketing and Communication.
Where? University of Valencia, Spain
When? 1st – 5th July 2019
Credits: 3.0 ECTS credits + Certificate of Attendance
Fees600 €
Coordinator: Universitat de València
Organising committee: Xaro Benavent, David Conesa, Dolors Palau, Juan Sanchis, Amparo Villén
Application, deadline and links: 15th June 2019.
Website: All the information is available here and at 


Contents and course planning

The summer school is devoted to modern developments in managing data from different disciplines: engineering, economics, social sciences, journalism, science, mathematics, medicine, etc.. These new approaches related to data managing are going to change production of goods, interaction between individuals and firms, the way we work, communications, arts, etc..

We are facing a data driven revolution, and this summer school aims to aid students and other participants to understand its scope.

Every day during the course the students will attend to theoretical (2 hour sessions) and practical classes (3 hour sessions). The school will provide coffee during breaks and lunch every day. Further, a number of social activities will be offered every afternoon.


1. Introduction to the course. Data: a new paradigm

This introduction discusses the current scenario of data-related technologies/applications. Next, we will explain, in a very descriptive way, the mathematical models on which these applications are based. Finally, we will discuss the free distribution tools that can be used to develop data-based applications.

2. Analytics (Matlab R, Stata, others)

In this session, we will describe some methods of predictive analytics as well as their applications in different areas. We will also discuss current trends in this topic.

3. Data and the firms: EVERIS, GMV, Capgemini, and others

In this session, some relevant companies working in the data-managing sector will explain their experience in the development of products based on data. They will describe the different phases of project development and how they foresee the future of these technologies and their applications.

4. Big data databases

In this session, big data databases will be analysed from different points of view: storage and data management for Big Data will be analysed, frameworks for distributed storage and processing, NoSQL databases, and operational vs. analytical capabilities.

5. Cloud computing and cloud hands on

The cloud enables the crystallization of the XaaS (Everything as a Service) paradigm in the current digital society and the democratization of the access to computational resources. In this session an introduction to the main concepts and technologies behind cloud computing and beyond will be presented.

6. Digital Privacy: Experimental and Big-data methodologies understanding human behaviour

Privacy and security (Cyber security) are central for all network tools and data. Protection of Data of a Personal Nature: Intimacy, privacy, right to honour, and personal image. Management of data: confidentiality and security.

7. The art of text mining: getting the essence from texts. How journalists use Big Data

WordSmith Tools and LIWC: programs to analyse frequencies and keywords (first) and to offer percentages of appearance based on 72 possible categories (second). Allow the analysis of great amount of data (news, comments or debates in digital environments) ensuring reliability and replicability.

Visual mining: the role infographics and data visualization play in our world. Basic principles of data and critical thinking. Step-by-step processes that will help you evaluate any data visualization. How to create and use effective charts, graphs, and data maps to explain data to any audience.

Social networks: Given the volume of information generated by users, reliable tools are required to evaluate the relevance of this huge volume of data. The seminar will explain some techniques of text mining applied to the evaluation of feeling and content of messages posted on Twitter. Twitter; machine learning; social networks; sentiment analysis; political communication.

8. Games: how data transformed the industry

Gamification is the application of game-design elements and game principles in non-game contexts.

Gamification commonly employs game design elements, which are used in non-game contexts to improve user engagement, organizational productivity, flow, learning, crowdsourcing, employee recruitment and evaluation, ease of use, usefulness of systems, physical exercise, traffic violations, voter apathy, and more.

A collection of research on gamification shows that a majority of studies on gamification find it has positive effects on individuals. However, individual and contextual differences exist. Gamification can also improve an individual’s ability to comprehend digital content and understand a certain area of study such as music.

9. Statistical learning with visual neuroscience
10. Artificial intelligence and the right to privacy. Data protection by design under European GDPR
11. Data and the fight against money laundering and tax evasion
12. Big data visualisation (graphic mining)
13. How do we validate software quality in big data projects (telecommunications)