Visualization of time series data with spatial context: communicating the energy production of power plants

Visualization of time series data with spatial context: communicating the energy production of power plants
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DOI:
10.1145/3105971.3105982
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发表时间:
2017-08
期刊:
Proceedings of the 10th International Symposium on Visual Information Communication and Interaction
影响因子:
--
通讯作者:
Nils Rodrigues;Rudolf Netzel;Kazi Riaz Ullah;Michael Burch;Alexander Schultz;B. Burger;D. Weiskopf
Nils Rodrigues;Rudolf Netzel;Kazi Riaz Ullah;Michael Burch;Alexander Schultz;B. Burger;D. Weiskopf
中科院分区:
其他
文献类型:
--
作者:
Nils Rodrigues;Rudolf Netzel;Kazi Riaz Ullah;Michael Burch;Alexander Schultz;B. Burger;D. Weiskopf

文献摘要

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在空间背景下可视化时间序列数据是一个越来越常见的问题,因为小巧轻便的GPS设备允许我们用位置信息丰富时间序列数据。一个例子是电厂能量输出的可视化。我们提供了一个基于web的应用程序,旨在提供有关特定地区能源生产的信息,以及有关发电厂的位置信息。该应用程序旨在作为政治讨论、推动和讲述德国能源向可再生能源转型(称为“Energiewende”)的坚实数据基础。因此,它被设计成直观、易于使用,并为不需要任何特定领域知识的广泛用户提供信息。用户可以选择不同类别的发电厂,并在总览地图上查找它们的位置。字形表示它们的确切位置,选择机制允许用户使用堆叠面积图或ThemeRivers在不同的时间尺度上比较功率输出。作为对应用程序的评估,我们收集了网络访问统计数据,并就其直观性、可用性和信息性进行了在线调查。
Visualizing time series data with a spatial context is a problem that appears more and more often, since small and lightweight GPS devices allow us to enrich the time series data with position information. One example is the visualization of the energy output of power plants. We present a web-based application that aims to provide information about the energy production of a specified region, along with location information about the power plants. The application is intended to be used as a solid data basis for political discussions, nudging, and story telling about the German energy transition to renewables, called "Energiewende". It was therefore designed to be intuitive, easy to use, and provide information for a broad spectrum of users that do not need any domain-specific knowledge. Users are able to select different categories of power plants and look up their positions on an overview map. Glyphs indicate their exact positions and a selection mechanism allows users to compare the power output on different time scales using stacked area charts or ThemeRivers. As an evaluation of the application, we have collected web access statistics and conducted an online survey with respect to the intuitiveness, usability, and informativeness.