Part III: Usage and Exploitation of Big Data
José María Cavanillas
José María Cavanillas is currently R&D&I Director in Atos since 2000. He is Master Engineer in Telecommunications in Madrid Technical University (UPM) and has completed post-graduate studies in Business Administration and International Trade from CEPADE. In the last 20 years his team has been involved in more than 200 R&D&I projects.
Edward Curry is a Research Scientist at the Insight Centre for Data Analytics. His research interests include smart cities, energy intelligence, semantic information management, event based systems, and collaborative data management. He has worked extensively with industry and government advising on the adoption patterns, practicalities, and benefits of new technologies.
Wolfgang Wahlster is the Director and CEO of the German Research Center for Artificial Intelligence and a Professor of Computer Science at Saarland University (Saarbrücken, Germany). He has published more than 170 technical papers and 8 books on language technology and intelligent user interfaces.
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy.
The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe.
This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.
Contributing AuthorsTilman Becker, José María Cavanillas, Edward Curry, Jörg Daubert, Nuria De Lama, John Domingue, Anna Fensel, André Freitas, Kazim Hussain, Anja Jentzsch, Nelia Lasierra, Helen Lippell, Mario Lischka, Klaus Lyko, Ricard Munné, Sabrina Neururer, Marcus Nitzschke, Axel-Cyrille Ngonga Ngomo, Adegboyega Ojo, Walter Palmetshofer, Elsa Prieto, Herman Ravkin, Sebnem Rusitschka, Martin Strohbach, Andreas Thalhammer, Tim van Kasteren, Wolfgang Wahlster, Sonja Zillner.
This book reports on preparatory work toward an important policy objective of the European Commission: turning Europe into a safe and privacy-respecting society that thrives by extracting maximum value from the data it produces and reuses, be it in support of important societal goals or as fuel for innovation in productive activities.
Our plans for Europe are described in our July 2014 Communication on a datadriven economy, where we spell out a three-pronged approach addressing regulatory issues (such as personal data protection and data ownership), framework conditions (such as data standards and infrastructures), and community building.
The first visible step of our community building efforts is a massive commitment (534 million Euros by 2020), which we signed in October 2014, to enter in a Public Private Partnership with the Big Data Value Association (BDVA): with the help from industrial parties and groups that represent relevant societal concerns (such as privacy), we intend to identify and solve technical problems and framework conditions (such as skill development) that stand in the way of European companies increasing their productivity and innovativeness by making efficient use of data technologies. By shouldering some of the financial risk of these activities, we plan to leverage even more massive European investment: for every public Euro invested by the Commission, our industry partners have committed to investing four private Euros.
Naturally, this requires some well-informed and clear thinking on which domains of data-related activities hold the greatest promise for a safe and prosperous Europe and on how we can avoid wasteful duplication in the development of data infrastructures, formats, and technologies. The book you are holding in your hands gives you a first lay of the land: it results from more than two years of work(also funded by the European Union) aimed at identifying issues and opportunities that are specifically European in character.
We fully expect that many of these results will be included and further elaborated over the years in the strategic planning of the BDVA, and we are happy to share them in this book with the broader public.
We hope that you will find them informative and that they will help you shape your own thinking on what your expectations and active role might be in a better Europe that has taught itself to run on data.
Data has become a factor just as important to production as labor, capital, and land. For the new value creators in today’s technology start-ups, little capital and office space is required. Both can be almost free when a firm is growing 1 % per day, on any metric. But without talent, and without the right kind of data, such a takeoff is highly improbable.
We see the same forces at play in SAP’s Innovation Center Network. Attracting the right talent was critical to establish the first Innovation Center in Potsdam. And having large, real-world datasets from customers and co-innovation partners is critical to many of our innovations. To make a difference in cancer treatment and research with our Medical Research Insights app, we critically depended on datadriven collaboration with the National Center for Tumor Diseases. The same holds for incubating SAP’s new sports line of business by co-innovating with the German national soccer team based on real-time sensor feeds from their players. And it holds true for SAP’s many initiatives in the Internet of Things, like the predictive maintenance apps with John Deere and Kaeser.
The Big Data Value Association (BDVA) is poised to make a difference both for data availability and for talent. By bringing together businesses with leading researchers, software and hardware partners, and enabling co-innovation around large, real-world datasets, BDVA can help lower the data barrier. And helping educate the next generation of thought leaders, especially in data science, computer science, and related fields, BDVA can help increase the supply of talent. Both are critical so Europe can begin to lead, not follow, in creating value from big data.
By clearly defining the opportunity in big data, by examining the big data value chain, and by deep-diving into industry sector applications, this book charts a way forward to new value creation and new opportunities from big data. Decision makers, policy advisors, researchers, and practitioners on all levels can benefit from this.