R&D globalization processes and university-industry research cooperation: measurement and indicators

FSW - CWTS - Ou

Van wetenschap naar innovatie: Over wensdromen en kennisstromen

Merit, Expertise and Measuremen

Discarding the ‘basic science/applied science’ dichotomy: A Knowledge Utilization Triangle classification system of research journals

FSW - CWTS - Ou

Пам'яті Івана Григоровича Гуракова

20 вересня 2004 року, не доживши 4 дні до свого 70-річчя, пішов у вічність колишній головний гідрогеолог, начальник Трускавецької гідрогеологічно режимно-експлуатаційної станції Іван Григорович Гураков. Пішов тихо і раптово в далекій землі Ізраїлю

Twenty-first century macro-trends in the institutional fabric of science: Bibliometric monitoring and analysis

Merit, Expertise and Measuremen

Capturing ‘R&D excellence’: Indicators, international statistics, and innovative universities

Excellent research may contributeto successful science-based technological innovation. We define ‘R&D excellence’in terms of scientific research that has contributed to the development ofinfluential technologies, where ‘excellence’ refers to the top segment of astatistical distribution based  oninternationally comparative performance scores. Our measurements are derivedfrom frequency counts of literature references (‘citations’) from patents toresearch publications during the last 15 years. The ‘D’ part in R&D isrepresented by the top10% most highly cited ‘excellent’ patents worldwide. The ‘R’part is captured by research articles in international scholarly journals thatare cited by these patented technologies.After analyzing millions of citingpatents and cited research publications, we find very large differences betweencountries worldwide in terms of the volume of domestic science contributing to thosepatented technologies. Where the USA produces the largest numbers of cited researchpublications (partly because of database biases), Switzerland and Israel outperformthe US after correcting for the size of their national science systems.To tease out possible explanatoryfactors, which may significantly affect or determine these performancedifferentials, we first studied high-income nations and advanced economies. Herewe find that the size of R&D expenditure correlates with the sheer size ofcited publications, as does the degree of university research cooperation withdomestic firms. When broadening our comparative framework to 70 countries(including many medium-income nations) while correcting for size of national sciencesystems, the important explanatory factors become the availability of humanresources and quality of science systems. Focusing on the latter factor, ourin-depth analysis of 716 research-intensive universities worldwide reveals severaluniversities with very high scores on our two R&D excellence indicators.Confirming the above macro-level findings, an in-depth study of 27 leading USuniversities identifies research expenditure size as a prime determinant.Our analytical model andquantitative indicators provides a supplementary perspective to input-oriented statisticsbased on R&D expenditures. The country-level findings are indicative of significantdisparities between national R&D systems. Comparing the performance ofindividual universities, we observe large differences within national sciencesystems. The top ranking ‘innovative’ research universities contribute significantlyto the development of advanced science-based technologies. Merit, Expertise and Measuremen

University-driven inclusive innovations in the Western Cape of South Africa: Towards a research framework of innovation regimes

Merit, Expertise and Measuremen

University–industry R&D linkage metrics: Validity and applicability in world university rankings

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