Data analytics on maps (web application for interactive map exploration) - Koh, Matthew Joon Min (2018)
Social media information packets like Twitter Tweets and Instagram photos are able to be geo-mapped through their respective geographical metadata. This allows us to view at a glance on a mapping platform like Google Maps the concen tration and speciﬁc information being talked about on social media at a glance. However, due to the exponential inﬂux of diﬀerent types of informative data, traditional forms of displaying such data in a ﬁnite location space can lead to over-clutter and overlapping information. Over-clutter makes it extremely hard to interpret the data in the map space. Hence, Geo-spatial elements have to be properly arranged and ﬁltered to be able to retrieve any meaningful information. This project aims to develop a functional system to extract a representative set of data via algorithmic processing and display the result to the end user. Such a process has to be consistent with the motivations and guidelines to ensure that objects are distinguishable and spaced apart at a reasonable distance to reduce the overall clutter. The algorithm has to eﬃciently operate on large enough sets of data to achieve a more accurate result. We will tackle the problem of eﬃcient selection of data points in a large data-set with inputs and parameters set by the user to display the updated result in real-time.