Today, vast amounts of data are collected from the internet, and the general public generates most data using social networks. There is a need to have a comprehensive approach to characterize the quality of such user-generated data collection from the internet. The data quality characteristics accepted among database and computer science communities have definitions that are not domain-specific. Therefore, there is no clear understanding of the data quality characteristics specific to user-generated content. This research examines different user-generated content platforms against the general data quality characteristics to determine which quality characteristics are essential for user-generated content. The research contributes to a list of definitions of those data quality characteristics specific to user-generated content. These definitions help identify quality characteristics useful for user-generated content platforms and their implementations. The quality of the content of Atlas of Living Australia, Twitter, YouTube, Wikipedia, and WalkingPaths is evaluated to assess the essence of the quality characteristics defined in this research.
The quality of the user-generated content of citizen science platforms has been discussed widely among researchers. Content is categorized into data and information: data is content stored in a database of a citizen science platform, while information is context-dependent content generated by users. Understanding data and information quality characteristics and utilizing them during design improves citizen science platforms’ overall quality. This research investigates the integration of data and information quality characteristics into a citizen science platform for collecting information from the general public with no scientific training in the area where content is collected. The primary goal is to provide a framework for selecting and integrating data and information quality characteristics into the design for improving the content quality on platforms. The design and implementation of a citizen science platform that collects walking path conditions are presented, and the resulting implication is evaluated. The results show that the platform’s content quality can be improved by introducing quality characteristics during the design stage of the citizen science platform.
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