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Visualization techniques in metadata information systems for geospatial data

机译:用于地理空间数据的元数据信息系统中的可视化技术

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This paper describes MIS in general and presents - by means of an information system for residual waste - several approaches to overcome the lack of usability in these information systems for environmental and geospatial data. MetaViz uses visualization techniques and spatial metaphors to generate effective and intuitive representations of the metadata. InfoCrystal is settled in the field of mathematics and tries to facilitate the query formulation and query refinement process by using abstract Venn diagrams instead of traditional fill-in forms. VisDB and TileBars are two approaches which have originated in the field of visual data mining/exploration, aimed at visualizing as much information as possible. Finally, some suggestions for further research in that field are described. The more information and data that are produced in the actual information society, the more important mechanisms and systems which organize the data and include information on where to find these data become. Most popular peculiarities of such information systems are digital libraries, metadata information systems (MIS) and catalogue systems (CS). Recent initiatives to geospatial libraries and environmental MIS/CS provide access to a wealth of distributed data, but offer only basic levels of interactivity and user assistance. This includes all steps of the information retrieval process: query formulation, query modification, comparison of (metadata) result sets and detailed presentation with respect to the visualization of result sets.
机译:本文概述了MIS,并通过残留废物信息系统介绍了几种方法来克服这些信息系统对环境和地理空间数据的可用性不足。 MetaViz使用可视化技术和空间隐喻来生成有效且直观的元数据表示。 InfoCrystal专注于数学领域,并尝试通过使用抽象的维恩图代替传统的填写表格来简化查询的制定和查询的细化过程。 VisDB和TileBars是起源于可视数据挖掘/探索领域的两种方法,旨在可视化尽可能多的信息。最后,描述了对该领域进一步研究的一些建议。在实际的信息社会中产生的信息和数据越多,组织数据并包括有关在何处找到这些数据的信息的重要机制和系统就越重要。这种信息系统最流行的特性是数字图书馆,元数据信息系统(MIS)和目录系统(CS)。地理空间图书馆和环境MIS / CS的最新计划可访问大量分布式数据,但仅提供基本级别的交互性和用户帮助。这包括信息检索过程的所有步骤:查询表述,查询修改,(元数据)结果集的比较以及关于结果集可视化的详细介绍。

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