Design and evaluation of overview components for effective semantic data exploration
Design and evaluation of overview components for effective semantic data exploration
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有效语义数据探索的概述组件的设计和评估
DOI：
10.1145/2479787.2479824
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Josep Maria Brunetti
中科院分区：
文献类型：
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作者：
Josep Maria Brunetti
网络中可用的语义数据的增长导致需要处理信息过载现象。这些数据量的潜力是巨大的，但是在大多数情况下，用户很难可视化，探索和使用此数据，尤其是对于没有语义Web技术经验的外行用户。 Shneiderman提出的视觉信息寻求咒语“首先概述，缩放和过滤器，然后在按需详细信息”中描述了如何在不同阶段显示数据以实现有效的探索。概述是处理数据集时的第一个用户任务。目的是用户能够了解数据集的整体结构。但是，获得当前的语义Web浏览器无法轻松完成此概述。使用大型异质数据集，概述变得难以实现，这在语义网络中是典型的。在探索新数据集开始时，几乎没有或没有支持来快速，轻松地获得概述信息。首次探索数据集时，这可能是一个严重的限制，特别是专门用于外行用户。我们的建议是重复使用和调整现有信息体系结构（IA）组件，以向用户提供此概述。此类IA组件是Web用户众所周知的，因为它们在大多数网页中都存在：导航栏，站点地图和站点索引。我们用Treemaps补充它们，这是一种可视化技术，用于显示层次数据。我们报告了这些组件的设计及其对执行实际任务的最终用户的评估。
The growing volumes of semantic data available in the Web result in the need for handling the Information Overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The Visual Information-Seeking Mantra "Overview first, zoom and filter, then details-on-demand" proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a dataset. The objective is that the user is capable of getting an idea about the overall structure of the dataset. However, obtaining this overview cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous datasets, which is typical in the Semantic Web. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new dataset. This can be a serious limitation when exploring a dataset for the first time, specially for lay-users. Our proposal is to reuse and adapt existing Information Architecture (IA) components to provide this overview to users. Such IA components are well known to Web users, as they are present in most web pages: navigation bars, site maps and site indexes. We complement them with treemaps, a visualization technique for displaying hierarchical data. We report about the design of these components as well as their evaluation with end-users performing real tasks.