Data Visualization 99
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Topology-Based Methods in Visualization II
Author: Hans-Christian Hege
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-02-07
Visualization research aims to provide insight into large, complicated data sets and the phenomena behind them. While there are di?erent methods of reaching this goal, topological methods stand out for their solid mathem- ical foundation, which guides the algorithmic analysis and its presentation. Topology-based methods in visualization have been around since the beg- ning of visualization as a scienti?c discipline, but they initially played only a minor role. In recent years,interest in topology-basedvisualization has grown andsigni?cantinnovationhasledto newconceptsandsuccessfulapplications. The latest trends adapt basic topological concepts to precisely express user interests in topological properties of the data. This book is the outcome of the second workshop on Topological Methods in Visualization, which was held March 4–6, 2007 in Kloster Nimbschen near Leipzig,Germany.Theworkshopbroughttogethermorethan40international researchers to present and discuss the state of the art and new trends in the ?eld of topology-based visualization. Two inspiring invited talks by George Haller, MIT, and Nelson Max, LLNL, were accompanied by 14 presentations by participants and two panel discussions on current and future trends in visualization research. This book contains thirteen research papers that have been peer-reviewed in a two-stage review process. In the ?rst phase, submitted papers where peer-reviewed by the international program committee. After the workshop accepted papers went through a revision and a second review process taking into account comments from the ?rst round and discussions at the workshop. Abouthalfthepapersconcerntopology-basedanalysisandvisualizationof ?uid?owsimulations;twopapersconcernmoregeneraltopologicalalgorithms, while theremaining papers discuss topology-based visualization methods in application areas like biology, medical imaging and electromagnetism.
Topology-based Methods in Visualization
Author: Helwig Hauser
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-05-24
Enabling insight into large and complex datasets is a prevalent theme in visualization research for which different approaches are pursued. Topology-based methods are built on the idea of abstracting characteristic structures such as the topological skeleton from the data and to construct the visualizations accordingly. There are currently new demands for and renewed interest in topology-based visualization solutions. This book presents 13 peer-reviewed papers as written results from the 2005 workshop “Topology-Based Methods in Visualization” that was initiated to enable additional stimulation in this field. It contains a longer chapter dedicated to a survey of the state-of-the-art, as well as a great deal of original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in topology-based visualization research.
Visualizing the Semantic Web
Author: Vladimir Geroimenko
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-06-29
Vladimir Geroimenko and Chaomei Chen The Semantic Web is avision that has sparked a wide-ranging enthusiasm for a new generation of the Web. The Semantic Web is happening. The central idea of this vision is to make the Web more understandable to computer programs so that people can make more use of this gigantic asset. The use of metadata (data about data) can clearly indicate the meaning of data on the Web so as to provide computers with enough information to handle such data. On the future Web, many additionallayers will be required if we want computer programs to handle the semantics (the meaning of data) properly without human intervention. Such layers should deal with the hierarchical relationships between meanings, their similarities and differences, logical rules for making new inferences from the existing data and metadata, etc. Dozens of new technologies have emerged recently to implement these ideas. XML (eXtensible Markup Language) forms the foundation of the future Web, RDF (Resource Description Framework), Topic Maps and many other technologies help to erect a "multi storey" building of the Semantic Web layer by layer by adding new features and new types of metadata. According to Tim Berners-Lee, the inventor of the current Web and the Semantic Web, it may take up to ten years to complete the building. The new Web will be much more complex than the current one and will contain enormous amounts of metadata as weIl as data.