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EWall: A visual analytics environment for collaborative sense-making

机译：EWall：用于协作感官分析的可视化分析环境

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摘要

We introduce EWall, an experimental visual analytics environment for the support of remote-collaborative sense-making activities. EWall is designed to foster and support 'object focused thinking', where users represent and understand information as objects, construct and recognize contextual relationships among objects, as well as communicate through objects. EWall also offers a unified infrastructure for the implementation and testing of computational agents that consolidate user contributions and manage the flow of information among users through the creation and management of a 'virtual transactive memory'. EWall users operate their individual graphical interfaces to collect, abstract, organize and comprehend task-relevant information relative to their areas of expertise. A first type of computational agents infers possible relationships among information items through the analysis of the spatial and temporal organization and collaborative use of information. All information items and relationships converge in a shared database. A second type of computational agents evaluates the contents of the shared database and provides individual users with a customized selection of potentially relevant information. A learning mechanism allows the computational agents to adapt to particular users and circumstances. EWall is designed to enable individual users to navigate vast amounts of shared information effectively and help remotely dispersed team members combine their contributions, work independently without diverting from common objectives, and minimize the necessary amount of verbal communication.
机译：我们介绍了EWall，这是一种实验性的视觉分析环境，可为远程协作式感官活动提供支持。 EWall旨在促进和支持“以对象为中心的思维”，用户在其中将信息表示和理解为对象，在对象之间构建和识别上下文关系，并通过对象进行通信。 EWall还为计算代理的实施和测试提供了统一的基础架构，可通过创建和管理“虚拟事务存储”来巩固用户的贡献并管理用户之间的信息流。 EWall用户操作他们各自的图形界面来收集，抽象，组织和理解与他们专业领域相关的与任务相关的信息。第一类计算代理通过对空间和时间组织的分析以及对信息的协同使用来推断信息项之间的可能关系。所有信息项和关系都聚合在一个共享数据库中。第二种类型的计算代理评估共享数据库的内容，并为单个用户提供可能相关信息的定制选择。学习机制允许计算代理适应特定的用户和环境。 EWall旨在使个人用户有效地浏览大量共享信息，并帮助分散在各个角落的团队成员共同贡献自己的力量，独立开展工作，而不会偏离共同的目标，并最大程度地减少了口头交流。

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