Search (4 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Informetrie"
  • × theme_ss:"Visualisierung"
  • × year_i:[2010 TO 2020}
  1. Braun, S.: Manifold: a custom analytics platform to visualize research impact (2015) 0.00 
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    Abstract
    The use of research impact metrics and analytics has become an integral component to many aspects of institutional assessment. Many platforms currently exist to provide such analytics, both proprietary and open source; however, the functionality of these systems may not always overlap to serve uniquely specific needs. In this paper, I describe a novel web-based platform, named Manifold, that I built to serve custom research impact assessment needs in the University of Minnesota Medical School. Built on a standard LAMP architecture, Manifold automatically pulls publication data for faculty from Scopus through APIs, calculates impact metrics through automated analytics, and dynamically generates report-like profiles that visualize those metrics. Work on this project has resulted in many lessons learned about challenges to sustainability and scalability in developing a system of such magnitude.
  2. Cobo, M.J.; López-Herrera, A.G.; Herrera-Viedma, E.; Herrera, F.: Science mapping software tools : review, analysis, and cooperative study among tools (2011) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.7, S.1382-1402
  3. Zhang, Y.; Zhang, G.; Zhu, D.; Lu, J.: Scientific evolutionary pathways : identifying and visualizing relationships for scientific topics (2017) 0.00 
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    Abstract
    Whereas traditional science maps emphasize citation statistics and static relationships, this paper presents a term-based method to identify and visualize the evolutionary pathways of scientific topics in a series of time slices. First, we create a data preprocessing model for accurate term cleaning, consolidating, and clustering. Then we construct a simulated data streaming function and introduce a learning process to train a relationship identification function to adapt to changing environments in real time, where relationships of topic evolution, fusion, death, and novelty are identified. The main result of the method is a map of scientific evolutionary pathways. The visual routines provide a way to indicate the interactions among scientific subjects and a version in a series of time slices helps further illustrate such evolutionary pathways in detail. The detailed outline offers sufficient statistical information to delve into scientific topics and routines and then helps address meaningful insights with the assistance of expert knowledge. This empirical study focuses on scientific proposals granted by the United States National Science Foundation, and demonstrates the feasibility and reliability. Our method could be widely applied to a range of science, technology, and innovation policy research, and offer insight into the evolutionary pathways of scientific activities.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.8, S.1925-1939
  4. Chen, R.H.-G.; Chen, C.-M.: Visualizing the world's scientific publications (2016) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.10, S.2477-2488

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