Collaborative Educational Geoanalytics Applied to Large Statistics Temporal Data
Collaborative Educational Geoanalytics Applied to Large Statistics Temporal Data
复制标题
协作教育地理分析应用于大型统计时态数据
DOI：
10.5220/0002780302330238
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
M. Jern
中科院分区：
文献类型：
--
作者：
M. Jern
Web 2.0图形技术的最新进展有可能对开发协作性地理可视化分析产生巨大影响，这些分析、可视化、交流和呈现官方统计数据。在本文中，我们引入了新颖的“讲故事”方法，让专家们首先探索大的、时间的和多维的统计数据，然后与同事合作，最后将动态可视化嵌入到Web文档（如HTML、博客或MediaWiki）中，以交流获得的重要见解和知识。其目的是让分析师（作者）探索数据，同时保存重要的发现，从而能够在互联网上分享获得的见解。通过便于描述性元文本的故事机制，通过快照机制超链接的文本注释，结合交互式可视化，作者可以让读者跟随分析者的逻辑推理方式。这种新兴技术可以在许多方面改变学习的术语和结构。
Recent advances in Web 2.0 graphics technologies have the potential to make a dramatic impact on developing collaborative geovisual analytics that analyse, visualize, communicate and present official statistics. In this paper, we introduce novel “storytelling” means for the experts to first explore large, temporal and multidimensional statistical data, then collaborate with colleagues and finally embed dynamic visualization into Web documents e.g. HTML, Blogs or MediaWiki to communicate essential gained insight and knowledge. The aim is to let the analyst (author) explore data and simultaneously save important discoveries and thus enable sharing of gained insights over the Internet. Through the story mechanism facilitating descriptive metatext, textual annotations hyperlinked through the snapshot mechanism and integrated with interactive visualization, the author can let the reader follow the analyst’s way of logical reasoning. This emerging technology could in many ways change the terms and structures for learning.