首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Orca: A Visualization Toolkit for High-Dimensional Data
Authors:Peter Sutherland  Anthony Rossini  Thomas Lumley  Nicholas Lewin-Koh  Julie Dickerson  Zach Cox
Institution:1. Neomorphic, Inc. , 2612 8th Street, Berkeley , CA , 94710 , USA;2. Department of Biostatistics , University of Washington , Seattle , WA , 98105 , USA;3. Department of Statistics , Iowa State University , Ames , IA , 50011 , USA;4. Department of Electrical and Computer Engineering , Iowa State University , Ames , IA , 50011 , USA;5. Department of Electrical Engineering , Iowa State University , Ames , IA , 50011 , USA
Abstract:Abstract

This article describes constructing interactive and dynamic linked data views using the Java programming language. The data views are designed for data that have a multivariate component. The approach to displaying data comes from earlier research on building statistical graphics based on data pipelines, in which different aspects of data processing and graphical rendering are organized conceptually into segments of a pipeline. The software design takes advantage of the object-oriented nature of the Java language to open up the data pipeline, allowing developers to have greater control over their visualization applications. Importantly, new types of data views coded to adhere to a few simple design requirements can easily be integrated with existing pipe sections. This allows access to sophisticated linking and dynamic interaction across all (new and existing) view types. Pipe segments can be accessed from data analysis packages such as Omegahat or R, providing a tight coupling of visual and numerical methods.
Keywords:Brushing  Compositional data  Data projections  Dynamic graphics  Interactive graphics  Java  Motion graphics  Multiple linked views  Multivariate space-time data  Object-oriented software  Plot matrices
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号