干旱区生态环境知识资源中心(Arid): Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis

Arid

DOI	10.2172/1235087
报告编号	LBNL--1003958
来源ID	OSTI_ID: 1235087
	Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis
	Hoa T. Nguyen; Stone, Daithi [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)]; E. Wes Bethel
英文摘要	An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different case studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.
出版年	2016
报告类型	Technical Report
语种	英语
国家	美国
来源学科分类	54 ENVIRONMENTAL SCIENCES nonparmetric statistics ; visualizing data variation ; information interfaces and presentation ; multi-variate ; multi-resolution projection ; simulation and modeling ; simulation output analysis
URL	http://www.osti.gov/scitech/servlets/purl/1235087
资源类型	科技报告
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/260659
推荐引用方式 GB/T 7714	Hoa T. Nguyen,Stone, Daithi [Lawrence Berkeley National Lab. ,E. Wes Bethel. Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis,2016.