Search (10 results, page 1 of 1)

  • × theme_ss:"Informetrie"
  • × theme_ss:"Visualisierung"
  1. Tscherteu, G.; Langreiter, C.: Explorative Netzwerkanalyse im Living Web (2009) 0.02
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    Object
    Web 2.0
    Source
    Social Semantic Web: Web 2.0, was nun? Hrsg.: A. Blumauer u. T. Pellegrini
  2. Petersen, A.; Münch, V.: STN® AnaVist(TM) holt verborgenes Wissen aus Recherche-Ergebnissen : Neue Software analysiert und visualisiert Marktaufteilung, Forschung und Patentaktivitäten (2005) 0.01
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    Abstract
    "Im 21. Jahrhundert ist die entscheidende Herausforderung an Informationsdienstleister nicht, Informationen zugänglich, sondern sie optimal nutzbar zu machen", sagt Sabine Brünger-Weilandt, Geschäftsführerin von FIZ Karlsruhe, das den Online-Dienst STN International in internationaler Kooperation betreibt. Informationsprofis, so Brünger-Weilandt weiter, bräuchten hockentwickelte Software für strategisches Informationsmanagement. Als "Antwort auf diesen Bedarf" hat STN International eine neue Software zur Analyse und Visualisierung (A&V) von Rechercheergebnissen aus STN-Datenbanken entwickelt. STN® AnaVistT(TM) wurde auf der DGI Online-Tagung Ende Mai in Frankfurt am Main und auf Benutzertreffen in Frankfurt am Main, München und Essen vorgestellt. Seit 18. Juli 2005 ist das neue A&V-Werkzeug für die öffentliche Nutzung freigegeben (www.stn-international.de).
    Die wichtigsten Funktionen von STN AnaVist sind: - Inhalte aus mehreren Datenbanken sind gleichzeitig auswertbar - Nutzer können Daten aus unterschiedlichen Ouellen suchen, analysieren und visualisieren, u.a. aus der Chemiedatenbank CAplusSM, der Patentdatenbank PCTFULL, und US-amerikanischen Volltextdatenbanken. - Einzigartige Beziehungen zwischen Datenelementen-nur STN AnaVist bietet die Möglichkeit, Beziehungen zwischen sieben unterschiedlichen Feldern aus Datenbankdokumenten - z.B., Firmen, Erfindern, Veröffentlichungsjahren und Konzepten-darzustellen. - Gruppierung und Bereinigung von Daten - vor der Analyse werden Firmen und ihre unterschiedlichen Namensvarianten von einem "Company Name Thesaurus" zusammengefasst. - Konzept-Standardisierung - Durch das CAS-Vokabular werden Fachbegriffe datenbankübergreifend standardisiert, so dass weniger Streuung auftritt. - Interaktive Präsentation der Beziehungen zwischen Daten und Diagrammenwährend der Auswertung können Daten zum besseren Erkennen der Beziehungen farblich hervorgehoben werden. - Flexible Erstellung der auszuwertenden Rechercheergebnisse - Rechercheergebnisse, die als Ausgangsdatensatz für die Analyse verwendet werden sollen, können auf zwei Arten gewonnen werden: zum einen über die in STN® AnaVist(TM) integrierte Konzept-Suchfunktion, zum anderen durch problemlose Übernahme von Suchergebnissen aus der bewährten Software STN Express® with Discover! TM Analysis Edition, Version 8.0
    Source
    Information - Wissenschaft und Praxis. 56(2005) H.5/6, S.319-322
  3. Cobo, M.J.; López-Herrera, A.G.; Herrera-Viedma, E.; Herrera, F.: Science mapping software tools : review, analysis, and cooperative study among tools (2011) 0.01
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    Abstract
    Science mapping aims to build bibliometric maps that describe how specific disciplines, scientific domains, or research fields are conceptually, intellectually, and socially structured. Different techniques and software tools have been proposed to carry out science mapping analysis. The aim of this article is to review, analyze, and compare some of these software tools, taking into account aspects such as the bibliometric techniques available and the different kinds of analysis.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.7, S.1382-1402
  4. Leydesdorff, L.: Visualization of the citation impact environments of scientific journals : an online mapping exercise (2007) 0.00
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    Abstract
    Aggregated journal-journal citation networks based on the Journal Citation Reports 2004 of the Science Citation Index (5,968 journals) and the Social Science Citation Index (1,712 journals) are made accessible from the perspective of any of these journals. A vector-space model Is used for normalization, and the results are brought online at http://www.leydesdorff.net/jcr04 as input files for the visualization program Pajek. The user is thus able to analyze the citation environment in terms of links and graphs. Furthermore, the local impact of a journal is defined as its share of the total citations in the specific journal's citation environments; the vertical size of the nodes is varied proportionally to this citation impact. The horizontal size of each node can be used to provide the same information after correction for within-journal (self-)citations. In the "citing" environment, the equivalents of this measure can be considered as a citation activity index which maps how the relevant journal environment is perceived by the collective of authors of a given journal. As a policy application, the mechanism of Interdisciplinary developments among the sciences is elaborated for the case of nanotechnology journals.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.1, S.25-38
  5. Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006) 0.00
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    Abstract
    This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.
    Date
    22. 7.2006 16:11:05
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.359-377
  6. 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.
  7. 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
  8. Samoylenko, I.; Chao, T.-C.; Liu, W.-C.; Chen, C.-M.: Visualizing the scientific world and its evolution (2006) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.11, S.1461-1469
  9. Aris, A.; Shneiderman, B.; Qazvinian, V.; Radev, D.: Visual overviews for discovering key papers and influences across research fronts (2009) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.11, S.2219-2228
  10. 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