Search (5 results, page 1 of 1)

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Date

22. 2.2003 17:25:39
22. 2.2003 18:13:11

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Date

22. 2.2003 17:25:39
22. 2.2003 18:20:07

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Date

22. 7.2006 16:11:05

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Abstract

The practical significances of identifying and accomodating individual differences has been established across a number of fields of research. There is a renewed interest in individual differences due to the advances in virtual environments, especially through far-reaching technologies such as information visualization and 3D graphical user interfaces on the WWW. The effects of individual differences on the use of these new technologies are yet to be found out. More fundamentally, theories and methods developed for the earlier generations of information systems are subject to a close examination of their applicability, efficiency, and effectiveness. In this article, we present a brief historical overview of research in in individual differences in the context of virtual environments. In particular, we highlight the notion of structure in the perception of individual users of an information system and the role of individuals' abilities to recognize and use such structures to perform various information-intensive tasks. Striking the balance between individuals' abilities and the demanding task for detecting, understanding, and utilizing such structures is an emerging theme across the 5 articles in this special issue. We outline the approaches and the major findings of these articles with reference to this central theme

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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.