Browsing by Author "du Toit, Tiaan"

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    Visual exploration of large geolocation-rich data sets using formal concept analysis
    (Stellenbosch : Stellenbosch University, 2022-04) du Toit, Tiaan; Britz, Katarina; Fischer, Bernd; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Information Science.
    ENGLISH SUMMARY: The rate at which data is being generated is ever-increasing, resulting in an abundance of very large data sets of di erent structures, all requiring improved methods of data capture, processing and storage. This in turn requires improved representation and data exploration methods. In an age of web applications, one such structure that has gained popularity is semi-structured data. Unlike relational data which can be speci cally queried, semi-structured data relies on di erent methods for data exploration and knowledge discovery. One such method is the visualisation of data beyond a purely granular textual format, in a dynamic and reactive manner. ConceptCloud, a exible interactive web application for exploring, visualising, and analysing semi-structured data sets, uses a combination of an intuitive tag cloud visualisation with an underlying formal concept lattice to provide a formal structure for navigation through a data set. It is an e ective, robust and scalable tool that allows for extension. The underlying formal concept lattice also allows for alternative possibilities of exploring data. This research describes the development and implementation of extensions made to the existing ConceptCloud tool, which are focused on improving the visualisation of, and the knowledge discovery through interaction with a data set, especially data with aspects that could be visualised in a more e ective manner. These extensions include a map based viewer for visualising geolocation data, a graph based viewer for visualising the composition of the data as well as a REST API to allow for mobile application development and further unique visualisations. These extensions are demonstrated and evaluated by visualising and exploring two semi-structured data sets in the viticultural domain, namely atmospheric measurements of grape growing regions and wine reviews. It is shown how these extensions aid in and support data exploration and knowledge discovery of these multi- faceted semi-structured data sets. These visualisations can not only be re ned and expanded upon to include other types of visualisations, but also improve data mining and knowledge discovery using ConceptCloud. This could result in further research and improvements in similar tools and processes.