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News | 17 June 2021

Publication of the book: Data Science for Economics and Finance - Methodologies and Applications

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance

Composite Indicators

The use of data science and artificial intelligence for economics and finance is providing benefits for scientists, professionals and policy-makers by improving the available data analysis methodologies for economic forecasting and therefore making our societies better prepared for the challenges of tomorrow.

This book is a good example of how combining expertise from the European Commission, universities in the U.S. and Europe, financial and economic institutions, and multilateral organizations, can bring forward a shared vision on the benefits of data science applied to economics and finance; from the research point of view to the evaluation of policies on the other hand.

It showcases how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the economic and financial sectors.

At the same time, the book is making an appeal for further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies.

About the authors

Sergio Consoli is a Scientific Project Officer at the European Commission, Joint Research Centre, Italy, working at the Competence Centre on Composite Indicators and Scoreboards (COIN), and, formerly, within the Centre for Advanced Studies on the project: Big Data and Forecasting of Economic Developments. Formerly Sergio was a Senior Scientist within the Data Science department at Philips Research, a Computer Engineering Officer at the Italian Presidency of the Council of Ministers, and a Junior Researcher at the National Research Council of Italy. Sergio's education and scientific experience fall in the areas of data science, operations research, artificial intelligence, knowledge engineering, and machine learning. He is author of several research publications in peer-reviewed international journals, granted patents, edited books, and leading conferences in these fields.


Diego Reforgiato Recupero is an Associate Professor at the Department of Mathematics and Computer Science of the University of Cagliari, Italy, where he is also a member of the Technical Commission for Patents and Spin-offs. His interests span from Semantic Web, graph theory, and smart grid optimization to sentiment analysis, data mining, big data, natural language processing, and human-robot interaction. He is the author of several research publications in peer-reviewed international journals, edited books, and leading conferences in these fields. He is Director of the Laboratory of Human Robot Interaction and Co-Director of the Laboratory of Artificial Intelligence and Big Data. He is also affiliated with the National Research Council of Italy (CNR) where he is a member of the Semantic Technology Laboratory and passionate  about bringing the research output to the market. 


Michaela Saisana is Head of the Monitoring, Indicators and Impact Evaluation Unit and she also leads the European Commission's Competence Centre on Composite Indicators and Scoreboards (COIN) at the Joint Research Centre in Italy. She has been working in the JRC since 1998, where she obtained a prize as “Best Young Scientist of the Year” in 2004 and together with her team the “JRC Policy Impact Award” for the Social Scoreboard of the European Pillar of Social Rights in 2018. Specializing on process optimization and spatial statistics, she is actively involved in promoting a sound development and responsible use of performance monitoring tools which feed into EU policy formulation and legislation in a wide range of fields.
 

Links to the book:

https://www.springer.com/gp/book/9783030668907

https://link.springer.com/book/10.1007%2F978-3-030-66891-4

The book is entirely published as Gold Open Access to reach a large audience. Feel free to grab a copy at your pleasure!