Wikipedia, the largest online collaboratively authored encyclopedia, allows anyone to easily contribute to its content. As it operates in a collaboratively authoring model, authors are not only responsible for writing up articles, but also assigning articles into categories in a way to classify by their topics. This makes the category system, which contains topic classifications under authors preferences is worth studying. However, given its large data volume and idiosyncrasies of its data structure, the analysis of Wikipedia’s category data is challenging. To facilitate ease and efficiency of understanding, we have designed a new visualization – a map-like visualization representing Wikipedia’s category data in a form similar to a geographic map. It allows readers to intuitively perceive large-scale patterns of categories and articles in the Wikipedia. In this thesis, we describe the algorithm of creating this novel type of visualization, and introduce our approaches for tackling the difficulties of handling the Wikipedia data.