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Date

23. 3.2008 19:10:22

Footnote

Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.

Pages

xiii, 407 S

Type

s

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Pages

309 S

Type

s

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Footnote

Rez. in: IWP 60(1009) H.4, S.245-246 (C. Wolff): "Der von Andrea Back (St. Gallen), Norbert Gronau (Potsdam) und Klaus Tochtermann herausgegebene Sammelband "Web 2.0 in der Unternehmenspraxis" verbindet in schlüssiger Weise die systematische Einführung in die Themen Web 2.0 und social software mit der Darstellung von Möglichkeiten, solche neuen Informationssysteme für Veränderungen im Unternehmen zu nutzen und zeigt dies anhand einer ganzen Reihe einzelner Fallstudien auf. Auch zukünftige Anwendungen wie das social semantic web werden als Entwicklungschance erörtert. In einer knappen Einleitung werden kurz die wesentlichen Begriffe wie Web 2.0, social software oder "Enterprise 2.0" eingeführt und der Aufbau des Bandes wird erläutert. Das sehr viel umfangreichere zweite Kapitel führt in die wesentlichen Systemtypen der social software ein: Erläutert werden Wikis, Weblogs, Social Bookmarking, Social Tagging, Podcasting, Newsfeeds, Communities und soziale Netzwerke sowie die technischen Besonderheiten von social software. Die Aufteilung ist überzeugend, für jeden Systemtyp werden nicht nur wesentliche Funktionen, sondern auch typische Anwendungen und insbesondere das Potenzial zur Nutzung im Unternehmen, insbesondere mit Blick auf Fragen des Wissensmanagements erläutert. Teilweise können die Autoren auch aktuelle Nutzungsdaten der Systeme ergänzen. Auch wenn bei der hohen Entwicklungsdynamik der social software-Systeme ständig neue Formen an Bedeutung gewinnen, vermag die Einteilung der Autoren zu überzeugen.

Pages

XI, 332 S

Type

s