Politiques scientifiques, technologiques et d'innovation
This page provides information on OECD work on scientometrics and bibliometrics. Scientometrics has been defined as the “quantitative study of science, communication in science, and science policy” (Hess, 1997). This field has evolved over time from the study of indices for improving information retrieval from peer-reviewed scientific publications (commonly described as the “bibliometric” analysis of science) to cover other types of documents and information sources relating to science and technology. These sources can include data sets, web pages and social media. Scientometric indicators complement and contribute to OECD efforts to standardise, collect, report and analyse a wide range of science, technology and innovation activities by providing evidence on a selected set of science and technology (S&T) outcomes.
This paper identifies and measures developments in science, algorithms and technologies related to artificial intelligence (AI). Using information from scientific publications, open source software (OSS) and patents, it finds a marked increase in AI-related developments over recent years. Since 2015, AI-related publications have increased by 23% per year; from 2014 to 2018, AI-related OSS contributions grew at a rate three times greater than other OSS contributions; and AI-related inventions comprised, on average, more than 2.3% of IP5 patent families in 2017. China’s growing role in the AI space also emerges.
The analysis relies on a three-pronged approach based on established bibliometric and patent-based methods, and machine learning (ML) implemented on purposely collected OSS data.
This report sheds light on the innovative strategies of the top 2000 corporate R&D investors worldwide, and the way they contribute to scientific advances, the development of new technologies, and to bringing new products and processes onto the market. In addition to providing evidence about some key structural features of these top corporate R&D investors worldwide and their innovative activities and specialisation, the report offers first time evidence about the artificial intelligence (AI)-related activities of these companies. The analysis in the report relies on a three-pronged approach exploiting intellectual property-related data, such as patent and registered trademark data, to proxy technological development and branding strategies, respectively; and scientific publication data to assess the contribution to scientific developments of these top 2000 corporate R&D investors worldwide and their affiliates.
The report is the result of long-term collaboration between the Joint Research Centre of the European Commission (EC-JRC) and the Directorate for Science, Technology and Innovation (STI) of the Organisation for Economic Cooperation and Development (OECD). The original data on which the report relies are available upon request.