Motivation

“If data had mass, the earth would be a black hole“ - Stephen Marsland

We live in the age of information, or, as many refer to, the age of data. Every day, 2.5 quintillion bytes of data are created - 90% of it in the last two years. This information comes from a wide range of different fields and in a wide range of shapes. One of the biggest challenges in the forthcoming years will consist of successfully leveraging it. People, companies, countries, and even international organizations have started to realize it. The European Union, for example, with the funding of the EURITO project has already started to tackle this challenge. The project wishes to help countries and organizations make better informed R&I policies, create new innovation opportunities and enhance the understanding of these systems, all by leveraging vast amounts of information, bringing benefits to both policymakers, researchers, and businesses.

As the scope tightens, the Technical University of Denmark is one of the organizations that wants to help advance this initiative by taking part in the EURITO project. In partnership with companies and institutions, AMICa, seeks to help solve a number of challenges related to the positive impact that industry can have on climate change. Such impact includes leveraging data to support management of complex value chains, identification of new research opportunities, and development of a new system layout design. As a general rule, this master thesis project wants to provide stakeholders with better tools to make data-driven decisions in what regards their business or operational logic. These stakeholders, just like in the project EURITO, include technology developers, organizations, and policymakers.

To prove the concept, researchers at DTU started by creating a database of technological assets (patents, scientific publications and projects) which will be further described in chapter 3. These are all related to biofuel research. After cleaning, preparing and analyzing the data, some results have already started to surface. Data exploration dashboards, which help understanding how technological assets are distributed, and sankey diagram implementations that help to understand in what country or organization focuses on in terms of biofuels research.

However, another need soon surfaced, what more insights lie in this vast amount of data? How can this information help decision makers and other stakeholders understand the technological landscape and make better R&I decisions by further exploiting this knowledge data? The possibilities of the analysis of this knowledge data are almost endless, but the problems that need solving can easily be quantifiable (see chapter 2). With the goal of not losing the focus, this project benefits participants in three different levels.

The macro level, wishes to help policy makers, as the first stakeholder, in assessing and understanding the “big picture” biofuel research landscape at a global level, and how this system might evolve over time. One problem, for example, can be the need for understanding the differences and similarities between two periods in time: How has biofuel research changed from 2000 to 2010? Another important problem, which is addressed in this work, might be the need for comprehending how external factors might impact research. For example, does the price of oil affect the research in any important way?

After the macro level, countries become the object of focus. The meso level of the analysis serves as a tool that assists in understanding the technological landscape by taking countries as units of research. This is particularly interesting for policy makers trying to make sense of, for example, what characterises countries in the research landscape. Here, questions such as: “How can a country be characterized in terms of its scientific capability?” or, “Are any countries related from a research perspective?” will be addressed. Other questions related to collaboration and similarity between countries might be critical in policy making, and will be addressed in this project.

The micro level, seeks to assist organizations. Between countries and organizations, even if the scope is different, the types of questions are highly connected. For example, as a president of a university one might want to understand what are the best options in business terms, the university should collaborate with.Moreover, one might want to comprehend the clusters of universities and organizations that exist throughout the world. This can help organizations and universities understand the underlying landscape of innovation and research strategies, and accurately design their own strategy.

In the system level, the understanding of the particularities of the system can benefit stakeholders at the national, organizational or even research level. These problems, although being more general, are highly relevant. For example, is sugarcane more researched or more patented? Is wood more patented or researched? Moreover, what are the external factors that affect research and do the price of goods influence it in any way?

Helping stakeholders make decisions at different levels and understand the research landscape is the primary goal of this work. It is believed that data, in its most pure form, has advantages not only in terms of the quality of the decisions but most importantly in the transparency of those same decisions.