Sleeping beauties cited in patents: is there also a dormitory of inventions?

A ‘Sleeping Beauty in Science’ is a publication that goes unnoticed (‘sleeps’) for a long time and then, almost suddenly, attracts a lot of attention (‘is awakened by a prince’). In our foregoing study we found that roughly half of the Sleeping Beauties are application-oriented and thus are potential Sleeping Innovations. In this paper we investigate a new topic: Sleeping Beauties that are cited in patents. In this way we explore the existence of a dormitory of inventions. To our knowledge this is the first study of this kind. We investigate the time lag between publication of the Sleeping Beauty and the first citation by a patent. We find that patent citation may occur before or after the awakening and that the depth of the sleep, i.e., citation rate during the sleeping period, is no predictor for later scientific or technological impact of the Sleeping Beauty. A surprising finding is that Sleeping Beauties are significantly more cited in patents than ‘normal’ papers. Inventor–author self-citations relations occur only in a small minority of the Sleeping Beauties that are cited in patents, but other types of inventor–author links occur more frequently. We develop an approach in different steps to explore the cognitive environment of Sleeping Beauties cited in patents. First, we analyze whether they deal with new topics by measuring the time-dependent evolution in the entire scientific literature of the number of papers related to both the precisely defined topics as well as the broader research theme of the Sleeping Beauty during and after the sleeping time. Second, we focus on the awakening by analyzing the first group of papers that cites the Sleeping Beauty. Third, we create concept maps of the topic-related and the citing papers for a time period immediately following the awakening and for the most recent period. Finally, we make an extensive assessment of the cited and citing relations of the Sleeping Beauty. We find that tunable co-citation analysis is a powerful tool to discover the prince(s) and other important application-oriented work directly related to the Sleeping Beauty, for instance papers written by authors who cite Sleeping Beauties in both the patents of which they are the inventors, as well as in their scientific papers. Merit, Expertise and Measuremen

Patent Citation Analysis and Its Value in Research Evaluation: A Review and A New Approach to Map Technology-Relevant Research

Purpose: First, to review the state-of-the-art in patent citation analysis, particularly characteristics of patent citations to scientific literature (scientific non-patent references,SNPRs). Second, to present a novel mapping approach to identify technology-relevant research based on the papers cited by and referring to the SNPRs. Design/methodology/approach: In the review part we discuss the context of SNPRs such as the time lags between scientific achievements and inventions. Also patent-to-patent citation is addressed particularly because this type of patent citation analysis is a major element in the assessment of the economic value of patents. We also review the research on the role of universities and researchers in technological development, with important issues such as universities as sources of technological knowledge and inventor-author relations. We conclude the review part of this paper with an overview of recent research on mapping and network analysis of the science and technology interface and of technological progress in interaction with science. In the second part we apply new techniques for the direct visualization of the cited and citing relations of SNPRs, the mapping of the landscape around SNPRs by bibliographic coupling and co-citation analysis, and the mapping of the conceptual environment of SNPRs by keyword co-occurrence analysis. Findings: We discuss several properties of SNPRs. Only a small minority of publications covered by the Web of Science or Scopus are cited by patents, about 3%–4%. However, for publications based on university-industry collaboration the number of SNPRs is considerably higher, around 15%. The proposed mapping methodology based on a “second order SNPR approach” enables a better assessment of the technological relevance of research. Research limitations: The main limitation is that a more advanced merging of patent and publication data, in particular unification of author and inventor names, in still a necessity. Practical implications: The proposed mapping methodology enables the creation of a database of technology-relevant papers (TRPs). In a bibliometric assessment the publications of research groups, research programs or institutes can be matched with the TRPs and thus the extent to which the work of groups, programs or institutes are relevant for technological development can be measured. Originality/value: The review part examines a wide range of findings in the research of patent citation analysis. The mapping approach to identify a broad range of technology relevant papers is novel and offers new opportunities in research evaluation practices. Merit, Expertise and Measuremen

Laudation on the occasion of the presentation of the Derek de Solla Price Award 2021 to Prof. Ludo Waltman at the ISSI conference, Leuven, 2021

Merit, Expertise and Measuremen

Dormitory of Physical and Engineering Sciences: Sleeping Beauties May Be Sleeping Innovations

Merit, Expertise and Measuremen

Do younger Sleeping Beauties prefer a technological prince?

In this paper we investigate recent Sleeping Beauties cited in patents (SB-SNPRs). We find that the increasing trend of the relative number of SBs stopped around 1998. Moreover, we find that the time lag between the publication year of the SB-SNPRs and their first citation in a patent is becoming shorter in recent years. Our observations also suggest that, on average, in the more recent years SBs are awakened increasingly earlier by a ‘technological prince’ rather than by a ‘scientific prince’. These observations suggest that SBs with technological importance are ‘discovered’ earlier in an application-oriented context. Then, because of this earlier recognized technological relevance, papers may be cited also earlier in a scientific context. Thus early recognized technological relevance may ‘prevent’ papers to become an SB. The scientific impact of Sleeping Beauties is generally not necessarily related to the technological importance of the SBs, as far as measured with number and impact of the citing patents. The analysis of the occurrence of inventor-author relations as well as the citation years of inventor-author patents suggest that the scientific awakening of Sleeping Beauties only rarely occurs by inventor-author self-citation. Merit, Expertise and Measuremen

Searching for new breakthroughs in science: How effective are computerised detection algorithms?

In this study we design, develop, implement and test an analytical framework and measurement model to detect scientific discoveries with 'breakthrough' characteristics. To do so we have developed a series of computerized search algorithms  that data mine large quantities of research publications. These algorithms facilitate early-stage detection of 'breakout' papers  that  emerge as highly cited and distinctive and are considered to be potential breakthroughs. Combining computer-aided data  mining with decision heuristics, enabled us to assess structural changes within citation patterns with the international scientific literature. In our case studies we applied a citation  impact  time  window  of 24--36 months after publication of each research paper.  In this paper, we report on our test results, in which five algorithms were applied to the entire Web of Science database. We analysed the citation impact patterns of all research articles from the period 1990--1994. We succeeded in detecting many papers with distinctive impact profiles (breakouts). A small subset of these breakouts is classified as 'breakthroughs': Nobel Prize research papers; papers occurring in Nature's Top-100 Most Cited Papers Ever; papers still (highly) cited by review papers or patents; or those frequently mentioned in today's social media. We also compare the outcomes of our algorithms with the results of a 'baseline' detection algorithm developed by Redner in 2005, which selects the world's most highly cited 'hot papers'.The detection rates of the algorithms vary, but overall, they present a powerful tool for tracing breakout papers in science. The wider applicability of these algorithms, across all science fields, has not yet been ascertained. Whether or not our early-stage breakout papers present a 'breakthrough' remains a matter of opinion, where input from subject experts is needed for verification and confirmation, but our detection approach certain helps to limit the search domain to trace and track important emerging topics in science.Merit, Expertise and Measuremen

Introduction to the special section devoted to the 18th International Conference on Science and Technology Indicators 'Translational Twists and Turns: Science as a Socio-Economic Endeavor'. Berlin, Germany, September 4-6 2013

Merit, Expertise and Measuremen

Urban Scaling of Cities in the Netherlands

Merit, Expertise and Measuremen

Towards a new crown indicator: An empirical analysis

FSW - CWTS - Ou

Citation analysis may severely underestimate the impact of clinical research as compared to basic research

FSW - CWTS - Ou