204 research outputs found

    Patent data as a tool to monitor S & T portfolio's.

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    This article deals with the use of patent data to monitor science and technology (S&T) portfolios. S&T portfolios have become central tools to examine and to monitor the vitality of both institutions and regions in the innovation game that underpins their economic growth and development. Those portfolios have to be monitored not only at the intra-organizational level, but also at the inter-organizational level and at the levels of specific systems of innovation. Therefore, the development of appropriate, easy-to-use and transparent, benchmark indicators to assess the strengths and weaknesses of organizational S&T portfolios is tantamount. In this paper, we report the construction of such a benchmark indicator and we assess its usefulness by applying it to the European Patent Database.Data; Science; Regions; Systems;

    Linking science to technology: using bibliographic references in patents to build linkage schemes.

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    In this paper, we develop and discuss a method to design a linkage scheme that links the systems of science and technology through the use of patent citation data. After conceptually embedding the linkage scheme in the current literature on science-technology interactions and associations, the methodology and algorithms used to decelop the linkage scheme are discussed in detail. The method is subsequently tested on and applied to subsets of USPTO patents. The results point to highly skewed citation distributions, enabling us to discern between those fields of technology that are highly science-interactive and those fields where technology develoment is highly independent from the scientific literature base.Science; Patents; Systems; Data; Algorithms; Distribution;

    Origin and emergence of entrepreneurship as a research field

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    This paper seeks to map out the emergence and evolution of entrepreneurship as an independent field in the social science literature from the early 1990s to 2009. Our analysis indicates that entrepreneurship has grown steadily during the 1990s but has truly emerged as a legitimate academic discipline in the latter part of the 2000s. The field has been dominated by researchers from Anglo-Saxon countries over the past 20 years, with particularly strong representations from the US, UK, and Canada. The results from our structural analysis, which is based on a core document approach, point to five large knowledge clusters and further 16 sub-clusters. We characterize the clusters from their cognitive structure and assess the strength of the relationships between these clusters. In addition, a list of most cited articles is presented and discussed

    Learning in university technology transfer offices: transactions-focused and relations-focused approaches to commercialization of academic research

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    University Technology Transfer Offices (TTOs) need a wide range of abilities to facilitate commercial exploitation of research outputs; however, we know relatively little about how these important abilities are developed and refined over time. We draw on practice-based studies of learning to create a novel conceptualization of learning processes and their outcomes in TTOs and show that this conceptualization of learning provides new empirical insights into how learning in TTOs shapes their commercialization practice. We investigate learning-in-practice in case studies of six UK TTOs and find two approaches to commercialization, namely transactions-focused practice and relations-focused practice. We find that both practices co-exist and co-evolve in some TTOs while other TTOs are predominantly transactions-focused. For the latter the development of a relations-focused approach is difficult, but possible if there is strategic direction and if sources of inertia are removed by TTO directors. Given that evolving practice cannot be fully explained by informal learning processes, we suggest that so far separate streams of practice-based literature on learning and strategizing should be brought together. The implications for further investigations of TTO abilities and some recommendations for policy and practice are discussed

    Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network

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    The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (i) identifies actual clusters of patents: i.e. technological branches, and (ii) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the {citation vector}, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action

    Technology transfer model for Austrian higher education institutions

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    The aim of this paper is to present the findings of a PhD research (Heinzl 2007, Unpublished PhD Thesis) conducted on the Universities of Applied Sciences in Austria. Four of the models that emerge from this research are: Generic Technology Transfer Model (Sect. 5.1); Idiosyncrasies Model for the Austrian Universities of Applied Sciences (Sect. 5.2); Idiosyncrasies-Technology Transfer Effects Model (Sect. 5.3); Idiosyncrasies-Technology Transfer Cumulated Effects Model (Sect. 5.3). The primary and secondary research methods employed for this study are: literature survey, focus groups, participant observation, and interviews. The findings of the research contribute to a conceptual design of a technology transfer system which aims to enhance the higher education institutions' technology transfer performance. © 2012 Springer Science+Business Media, LLC

    A census of baryons in the Universe from localized fast radio bursts

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    More than three quarters of the baryonic content of the Universe resides in a highly diffuse state that is difficult to observe, with only a small fraction directly observed in galaxies and galaxy clusters. Censuses of the nearby Universe have used absorption line spectroscopy to observe these invisible baryons, but these measurements rely on large and uncertain corrections and are insensitive to the majority of the volume, and likely mass. Specifically, quasar spectroscopy is sensitive either to only the very trace amounts of Hydrogen that exists in the atomic state, or highly ionized and enriched gas in denser regions near galaxies. Sunyaev-Zel'dovich analyses provide evidence of some of the gas in filamentary structures and studies of X-ray emission are most sensitive to gas near galaxy clusters. Here we report the direct measurement of the baryon content of the Universe using the dispersion of a sample of localized fast radio bursts (FRBs), thus utilizing an effect that measures the electron column density along each sight line and accounts for every ionised baryon. We augment the sample of published arcsecond-localized FRBs with a further four new localizations to host galaxies which have measured redshifts of 0.291, 0.118, 0.378 and 0.522, completing a sample sufficiently large to account for dispersion variations along the line of sight and in the host galaxy environment to derive a cosmic baryon density of Ωb=0.0510.025+0.021h701\Omega_{b} = 0.051_{-0.025}^{+0.021} \, h_{70}^{-1} (95% confidence). This independent measurement is consistent with Cosmic Microwave Background and Big Bang Nucleosynthesis values.Comment: Published online in Nature 27 May, 202

    The rise and fall of the king : the correlation between FO Aquarii's low states and the White Dwarf's Spindown

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    The intermediate polar FO Aquarii experienced its first-reported low-accretion states in 2016, 2017, and 2018. We establish that these low states occurred shortly after the system's white dwarf (WD) began spinning down, after having spent a quarter-century spinning up. FO Aquarii is the only intermediate polar whose period derivative has undergone a sign change, and it has now done so twice. By combining our spin-pulse timings with previous data, we determine that the WD's spin period has varied quasi-sinusoidally since the system's discovery, and an extrapolation predicts that the white dwarf was spinning down during newly discovered low states in photographic plates from 1964, 1965, and 1974. Thus, FO Aquarii's low states appear to occur exclusively during epochs of spindown. Additionally, our time-series photometry of the 2016-18 low states reveals that the mode of accretion is extremely sensitive to the accretion rate; when the system is fainter than V~14.0, the accretion onto the WD is largely stream-fed, but when it is brighter, it is almost exclusively disk-fed. The system's grazing eclipse remained detectable throughout all observations, confirming the uninterrupted presence of a disk-like structure, regardless of the accretion state. Our observations are consistent with theoretical predictions that during the low states, the accretion disk dissipates into a ring of diamagnetic blobs. Finally, a new XMM-Newton observation from 2017 indicates that the system's anomalously soft X-ray spectrum and diminished X-ray luminosity in the wake of the 2016 low state appear to be long-lasting changes compared to pre-2016 observations.peer-reviewe
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