This article uses text mining techniques to determine the time lag of knowledge transfer between research activity and technology development in bioremediation, complementing these with advanced visualization techniques in order to extract patterns that could be of interest for decision making in this field. The emergence patterns in this field have been identified and a method based on subject-action-object (SAO) semantic structure is proposed for characterizing such patterns, using 2-word tuples. Our results show that technology developments in heavy metal bioremediation swiftly follow scientific advances, as opposed to developments in bioremediation of organic chemical components. The science mapping reveals three distinct areas: 1) heavy metal remediation and phytoremediation; 2) aerobic and anaerobic remediation of chemical elements; and 3) bioremediation techniques for treating specific contamination sources such as oil. The emergence analysis points at activities involving energy recovery by bioremediation, and shows an increasing amount of technologies involving specific strains of microorganisms, which could gain significant traction in this field in an estimated time horizon of ten years. Our SAO approach, tested on the data sample corresponding to these strains, proves to be useful for characterizing the emerging technologies when applied to instrumental concepts.
Author(s): Gaizka Garechana, Rosa Rio-Belver, Enara Zarrabeitia, Izaskun Alvarez-Meaza
Organization(s): University of the Basque Country
Source: IEEE Transactions on Engineering Management
This paper presents findings of a quasi-experimental assessment to gauge the research productivity and degree of interdisciplinarity of research center outputs. Of special interest, we share an enriched visualization of research co-authoring patterns.
We compile publications by 45 researchers in each of 1) the iUTAH project, which we consider here to be analogous to a “research center,” 2) CG1— a comparison group of participants in two other Utah environmental research centers, and 3) CG2—a comparison group of Utah university environmental researchers not associated with a research center. We draw bibliometric data from Web of Science and from Google Scholar. We gather publications for a period before iUTAH had been established (2010–2012) and a period after (2014–2016). We compare these research outputs in terms of publications and citations thereto. We also measure interdisciplinarity using Integration scoring and generate science overlay maps to locate the research publications across disciplines.
We find that participation in the iUTAH project appears to increase research outputs (publications in the After period) and increase research citation rates relative to the comparison group researchers (although CG1 research remains most cited, as it was in the Before period). Most notably, participation in iUTAH markedly increases co-authoring among researchers—in general; and for junior, as well as senior, faculty; for men and women: across organizations; and across disciplines.
The quasi-experimental design necessarily generates suggestive, not definitively causal, findings because of the imperfect controls.
This study demonstrates a viable approach for research assessment of a center or program for which random assignment of control groups is not possible. It illustrates use of bibliometric indicators to inform R&D program management. New visualizations of researcher collaboration provide compelling comparisons of the extent and nature of social networking among target cohort.ings of a
For full-text DOI: https://doi.org/10.2478/jdis-2018-0004
Author(s): Jon Garner, Alan L. Porter, Andreas Leidolf, Michelle Baker
Organization(s): Georgia Institute of Technology, Utah State Universit
Source: Journal of Data and Information Science (JDIS)
The purpose of this study is to modernize previous work on science overlay maps by updating the underlying citation matrix, generating new clusters of scientific disciplines, enhancing visualizations, and providing more accessible means for analysts to generate their own maps.
We use the combined set of 2015 Journal Citation Reports for the Science Citation Index (n of journals = 8,778) and the Social Sciences Citation Index (n = 3,212) for a total of 11,365 journals. The set of Web of Science Categories in the Science Citation Index and the Social Sciences Citation Index increased from 224 in 2010 to 227 in 2015. Using dedicated software, a matrix of 227 × 227 cells is generated on the basis of whole-number citation counting. We normalize this matrix using the cosine function. We first develop the citing-side, cosine-normalized map using 2015 data and VOSviewer visualization with default parameter values. A routine for making overlays on the basis of the map (“wc15.exe”) is available at http://www.leydesdorff.net/wc15/index.htm.
Findings appear in the form of visuals throughout the manuscript. In Figures 1–9 we provide basemaps of science and science overlay maps for a number of companies, universities, and technologies.
As Web of Science Categories change and/or are updated so is the need to update the routine we provide. Also, to apply the routine we provide users need access to the Web of Science.
Visualization of science overlay maps is now more accurate and true to the 2015 Journal Citation Reports than was the case with the previous version of the routine advanced in our paper.
The routine we advance allows users to visualize science overlay maps in VOSviewer using data from more recent Journal Citation Reports.
Author(s): Stephen Carley, Alan L. Porter, Ismael Rafols, Loet Leydesdorff
Organization(s): Georgia Institute of Technology , Universitat Politècnica de València, University of Amsterdam
Source: Journal of Data and Information Science
Synthetic biology is an emerging domain that combines biological and engineering concepts and which has seen rapid growth in research, innovation, and policy interest in recent years. This paper contributes to efforts to delineate this emerging domain by presenting a newly constructed bibliometric definition of synthetic biology. Our approach is dimensioned from a core set of papers in synthetic biology, using procedures to obtain benchmark synthetic biology publication records, extract keywords from these benchmark records, and refine the keywords, supplemented with articles published in dedicated synthetic biology journals. We compare our search strategy with other recent bibliometric approaches to define synthetic biology, using a common source of publication data for the period from 2000 to 2015. The paper details the rapid growth and international spread of research in synthetic biology in recent years, demonstrates that diverse research disciplines are contributing to the multidisciplinary development of synthetic biology research, and visualizes this by profiling synthetic biology research on the map of science. We further show the roles of a relatively concentrated set of research sponsors in funding the growth and trajectories of synthetic biology. In addition to discussing these analyses, the paper notes limitations and suggests lines for further work.
Full-text via Open Access at
Author(s): Philip Shapira, Seokbeom Kwon, Jan Youtie
Organization(s): University of Manchester, Georgia Institute of Technology
Despite the current global trend of reduction in the morbidity and mortality of neglected diseases, dengue’s incidence has increased and occurrence areas have expanded. Dengue also persists as a scientific and technological challenge since there is no effective treatment, vaccine, vector control or public health intervention. Combining bibliometrics and social network analysis methods can support the mapping of dengue research and development (R&D) activities worldwide.
We use scientific publication data from Web of Science Core Collection – articles indexed in Science Citation Index Expanded (SCI-EXPANDED) – and combine bibliometrics and social network analysis techniques to identify the most relevant journals, scientific references, research areas, countries and research organisations in the dengue scientific landscape.
Our results show a significant increase of dengue publications over time; tropical medicine and virology as the most frequent research areas and biochemistry and molecular biology as the most central area in the network; USA and Brazil as the most productive countries; and Mahidol University and Fundação Oswaldo Cruz as the main research organisations and the Centres for Disease Control and Prevention as the most central organisation in the collaboration network.
For full-text, http://www.scielo.br/scielo.php?pid=S0074-02762017005005103&script=sci_arttext&tlng=en
Author(s): Fabio Batista Mota, Bruna de Paula Fonseca e Fonseca, Andréia Cristina Galina, Roseli Monteiro da Silva
Organization(s): Fundação Oswaldo Cruz-Fiocruz
Source: Memórias do Instituto Oswaldo Cruz
One of the most difficult but yet unavoidable tasks for every academic field is to define its own nature and demarcate its area. This article addresses the question of how current computational text-mining approaches can be used as tools for clarifying what aesthetics is when such approaches are combined with philosophical analyses of the field. We suggest that conjoining the two points of view leads to a fuller picture than excluding one or the other, and that such a picture is useful for the self-understanding of the discipline. Our analysis suggests that text-mining tools can find sources, relations, and trends in a new way, but it also reveals that the databases that such tools use are presently seriously limited. However, computational approaches that are still in their infancy in aesthetics will most likely gradually affect our understanding about the ontological status of the discipline and its instantiations.
Open Access article…. for full-text, click http://www.aestheticsandculture.net/index.php/jac/article/view/30072
Author(s): Ossi Naukkarinen and Johanna Bragge
Organization: Aalto University School of Arts, Design and Architecture; Aalto University School of Economics
Source: Journal of Aesthetics and Culture
The delineation of coordinates is fundamental for the cartography of science, and accurate and credible classification of scientific knowledge presents a persistent challenge in this regard. We present a map of Finnish science based on unsupervised-learning classification, and discuss the advantages and disadvantages of this approach vis-à-vis those generated by human reasoning. We conclude that from theoretical and practical perspectives there exist several challenges for human reasoning-based classification frameworks of scientific knowledge, as they typically try to fit new-to-the-world knowledge into historical models of scientific knowledge, and cannot easily be deployed for new large-scale data sets. Automated classification schemes, in contrast, generate classification models only from the available text corpus, thereby identifying credibly novel bodies of knowledge. They also lend themselves to versatile large-scale data analysis, and enable a range of Big Data possibilities. However, we also argue that it is neither possible nor fruitful to declare one or another method a superior approach in terms of realism to classify scientific knowledge, and we believe that the merits of each approach are dependent on the practical objectives of analysis.
Full-text available at http://onlinelibrary.wiley.com/doi/10.1002/asi.23596/full
Author(s): Arho Suominen and Hannes Toivanen
Organization(s): VTT Technical Research Centre of Finland Ltd
Source: Journal of the Association for Information Science and Technology
This study uses the new global patent map developed by Kay et al. (2014) to reflect the patenting activity of Spain together with the activity of the Basque Country, a highly industrialised region in Spain, for the time interval 2000-2006. The global patent map reflects the technology categories where a patent could be categorised according to the international patent classification (IPC) system, in addition to the degree of similarity among different IPCs, determined by using the citing-to-cited relationships as bonds between categories. An overlay method has been developed to compare, on the one hand, the patenting activity in Spain and the Basque Country and a display of the most important technology sectors and; on the other, the selection of a technology sector and an analysis of technology transfer in both regions through different IPCs to compare them and determine the possible technological sources remaining for development.
Author(s): Javier Gavilanes-Trapote, Rosa María Río-Belver, Ernesto Cilleruelo, Gaizka Garechana, Jaso Larruscain
Organization(s): University of the Basque Country
Source: International Journal of Technology Management
The complexity of the problems facing society, such as health care, mobility, or environment, call for solutions cutting across different disciplines. This lies at the heart of interdisciplinary research. Interdisciplinarity has been strongly promoted worldwide over the recent years. For the case of Japan, a prominent example is the WPI (World Premier International Research Center) initiative. The integration of unrelated or distant bodies of knowledge – also regarded as knowledge integration, fusion, confluence, or convergence – is an essential factor for interdisciplinary research. This study aims at quantitatively and visually capturing knowledge integration in a cutting edge WPI research institution in Japan. By combining different existing approaches into one integrated framework, fuller, more holistic, insights into the knowledge integration efforts can be gained. Three levels of analysis are proposed: macro, meso, and micro; each of them targeting knowledge integration at different granularities. For each of these levels, different bibliometric based and visualization approaches are used: global research maps, science overlays, and research landscapes, respectively. The results of these analyses will not only provide key insights into the way knowledge integration efforts can be assessed in cutting edge research institutions, but also they are expected to serve as a spearheading efforts for the conduction of further `technology intelligence’ studies.
Author(s): A. A. Robinson
Organization: Kyoto University
Source: 2015 Portland International Conference on Management of Engineering and Technology (PICMET)
This paper examines the use of scientometric overlay mapping as a tool of ’strategic intelligence’ to aid the governance of emerging technologies. We develop an integrative synthesis of different overlay mapping techniques and associated perspectives on technological emergence across the geographical, social, and cognitive spaces. To do so, we longitudinally analyse (with publication and patent data) three case-studies of emerging technologies in the medical domain. These are: RNA interference (RNAi), Human Papilloma Virus (HPV) testing technologies for cervical cancer, and Thiopurine Methyltransferase (TPMT) genetic testing. Given the flexibility (i.e. adaptability to different sources of data) and granularity (i.e. applicability across multiple levels of data aggregation) of overlay mapping techniques, we argue that these techniques can favour the integration and comparison of results from different contexts and cases, thus potentially functioning as platform for a ’distributed’ strategic intelligence for analysts and decision-makers.
Available from: http://www.researchgate.net/publication/235982047_Strategic_Intelligence_on_Emerging_Technologies_Scientometric_Overlay_Mapping
Author(s): Daniele Rotolo, Ismael Rafols, Michael M. Hopkins, Loet Leydesdorff
Organization(s): University of Sussex, Universitat Politècnica de València
Source: Journal of the Association for Information Science and Technology