地理空间数据可视化与加拿大大选关键预测
Geo-Spatial Data Visualization and Critical Metrics Predictions for Canadian Elections
摘要：
由各种组织发布的开放数据旨在向公众提供数据。在世界各地，许多组织维护着大量的开放数据库，其中包含大量的事实和数字。然而，它们中的大多数都没有提供一个简洁和有见地的数据解释或可视化工具，可以帮助用户以一致的可比方式处理所有信息。加拿大联邦和省选举是这些数据库的一个例子。这些信息存在于许多网站中，作为单独的表格，使得用户需要遍历网站上分散的信息的树结构，并且留给用户进行比较，而不提供适当的工具、数据解释或可视化。在本文中，我们提供了解决这个问题的技术细节，通过使用加拿大选举数据（自1867年以来）作为一个具体的案例研究，因为它有许多技术挑战。我们希望这里使用的方法可以帮助开发类似的工具，以实现公开数据集的一些目标。开发的工具包含数据可视化，趋势分析和预测组件。可视化使用户能够通过各种技术与数据进行交互，包括地理空间可视化。为了重现结果，我们开源了该工具。
英文摘要：
Open data published by various organizations is intended to make the data available to the public. All over the world, numerous organizations maintain a considerable number of open databases containing a lot of facts and numbers. However, most of them do not offer a concise and insightful data interpretation or visualization tool, which can help users to process all of the information in a consistently comparable way. Canadian Federal and Provincial Elections is an example of these databases. This information exists in numerous websites, as separate tables so that the user needs to traverse through a tree structure of scattered information on the site, and the user is left with the comparison, without providing proper tools, data-interpretation or visualizations. In this paper, we provide technical details of addressing this problem, by using the Canadian Elections data (since 1867) as a specific case study as it has numerous technical challenges. We hope that the methodology used here can help in developing similar tools to achieve some of the goals of publicly available datasets. The developed tool contains data visualization, trend analysis, and prediction components. The visualization enables the users to interact with the data through various techniques, including Geospatial visualization. To reproduce the results, we have open-sourced the tool.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
