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  • × author_ss:"Boyack, K.W."
  • × theme_ss:"Visualisierung"
  1. Boyack, K.W.; Wylie, B.N.; Davidson, G.S.: Domain visualization using VxInsight®) [register mark] for science and technology management (2002) 0.00 
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    Abstract
    Boyack, Wylie, and Davidson developed VxInsight which transforms information from documents into a landscape representation which conveys information on the implicit structure of the data as context for queries and exploration. From a list of pre-computed similarities it creates on a plane an x,y location for each item, or can compute its own similarities based on direct and co-citation linkages. Three-dimensional overlays are then generated on the plane to show the extent of clustering at particular points. Metadata associated with clustered objects provides a label for each peak from common words. Clicking on an object will provide citation information and answer sets for queries run will be displayed as markers on the landscape. A time slider allows a view of terrain changes over time. In a test on the microsystems engineering literature a review article was used to provide seed terms to search Science Citation Index and retrieve 20,923 articles of which 13,433 were connected by citation to at least one other article in the set. The citation list was used to calculate similarity measures and x.y coordinates for each article. Four main categories made up the landscape with 90% of the articles directly related to one or more of the four. A second test used five databases: SCI, Cambridge Scientific Abstracts, Engineering Index, INSPEC, and Medline to extract 17,927 unique articles by Sandia, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory, with text of abstracts and RetrievalWare 6.6 utilized to generate the similarity measures. The subsequent map revealed that despite some overlap the laboratories generally publish in different areas. A third test on 3000 physical science journals utilized 4.7 million articles from SCI where similarity was the un-normalized sum of cites between journals in both directions. Physics occupies a central position, with engineering, mathematics, computing, and materials science strongly linked. Chemistry is farther removed but strongly connected.
    Type
    a
  2. Börner, K.; Chen, C.; Boyack, K.W.: Visualizing knowledge domains (2002) 0.00 
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    Abstract
    This chapter reviews visualization techniques that can be used to map the ever-growing domain structure of scientific disciplines and to support information retrieval and classification. In contrast to the comprehensive surveys conducted in traditional fashion by Howard White and Katherine McCain (1997, 1998), this survey not only reviews emerging techniques in interactive data analysis and information visualization, but also depicts the bibliographical structure of the field itself. The chapter starts by reviewing the history of knowledge domain visualization. We then present a general process flow for the visualization of knowledge domains and explain commonly used techniques. In order to visualize the domain reviewed by this chapter, we introduce a bibliographic data set of considerable size, which includes articles from the citation analysis, bibliometrics, semantics, and visualization literatures. Using tutorial style, we then apply various algorithms to demonstrate the visualization effectsl produced by different approaches and compare the results. The domain visualizations reveal the relationships within and between the four fields that together constitute the focus of this chapter. We conclude with a general discussion of research possibilities. Painting a "big picture" of scientific knowledge has long been desirable for a variety of reasons. Traditional approaches are brute forcescholars must sort through mountains of literature to perceive the outlines of their field. Obviously, this is time-consuming, difficult to replicate, and entails subjective judgments. The task is enormously complex. Sifting through recently published documents to find those that will later be recognized as important is labor intensive. Traditional approaches struggle to keep up with the pace of information growth. In multidisciplinary fields of study it is especially difficult to maintain an overview of literature dynamics. Painting the big picture of an everevolving scientific discipline is akin to the situation described in the widely known Indian legend about the blind men and the elephant. As the story goes, six blind men were trying to find out what an elephant looked like. They touched different parts of the elephant and quickly jumped to their conclusions. The one touching the body said it must be like a wall; the one touching the tail said it was like a snake; the one touching the legs said it was like a tree trunk, and so forth. But science does not stand still; the steady stream of new scientific literature creates a continuously changing structure. The resulting disappearance, fusion, and emergence of research areas add another twist to the tale-it is as if the elephant is running and dynamically changing its shape. Domain visualization, an emerging field of study, is in a similar situation. Relevant literature is spread across disciplines that have traditionally had few connections. Researchers examining the domain from a particular discipline cannot possibly have an adequate understanding of the whole. As noted by White and McCain (1997), the new generation of information scientists is technically driven in its efforts to visualize scientific disciplines. However, limited progress has been made in terms of connecting pioneers' theories and practices with the potentialities of today's enabling technologies. If the difference between past and present generations lies in the power of available technologies, what they have in common is the ultimate goal-to reveal the development of scientific knowledge.
    Type
    a

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