Making sense of Open Data Statistics with Information from Wikipedia
Daniel Hienert, Dennis Wegener, Siegfried Schomisch

TL;DR
This paper presents a method to enhance understanding of open data statistics by integrating them with Wikipedia historical events in an interactive visualization, aiding laymen in interpreting raw data.
Contribution
It introduces a novel interface combining open data with Wikipedia events, facilitating intuitive exploration and contextual understanding of statistical trends.
Findings
Users found the interface intuitive to use.
Users could identify relations between data trends and historical events.
The approach improved data interpretation for lay users.
Abstract
Today, more and more open data statistics are published by governments, statistical offices and organizations like the United Nations, The World Bank or Eurostat. This data is freely available and can be consumed by end users in interactive visualizations. However, additional information is needed to enable laymen to interpret these statistics in order to make sense of the raw data. In this paper, we present an approach to combine open data statistics with historical events. In a user interface we have integrated interactive visualizations of open data statistics with a timeline of thematically appropriate historical events from Wikipedia. This can help users to explore statistical data in several views and to get related events for certain trends in the timeline. Events include links to Wikipedia articles, where details can be found and the search process can be continued. We have…
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Taxonomy
TopicsWikis in Education and Collaboration · Data Visualization and Analytics · Mobile Crowdsensing and Crowdsourcing
