Olika typer av data genereras kontinuerligt varje sekund och för att kunna analysera denna data måste den transformeras till någon typ av visuell representation. En vanlig typ av data är spatio-temporal data, vilket är data som existerar i både rymd och tid. Hur denna typ av data kan visualiseras har undersökts under en lång period och området är fortfarande relevant idag. Ett antal metoder har undersökts i detta arbete och en genomgående litteraturstudie har genomförts. En applikation som implementerar ett antal av dessa undersökta metoder för att visualisera klimatdata har även skapats. / Different kinds of data is generated continuously every second and in order to be ableto analyze this data it has to be transformed into some kind of visual representation. Onecommon type of data is spatio-temporal data, which is data that exists in both space andtime. How to visualize this kind of data have been researched for a long time and is still avery relevant subject to expand on today. A number of approaches have been explored inthis work. An extensive literature study has also been performed and can be read in thisreport. The study has been divided into different classifications of spatio-temporal dataand the visual representations are structured by these classes.Another contribution of this thesis is a climate data application to visualize spatiotemporaldata sets of temperatures collected for several countries in the world. This applicationimplements several of the visual representations presented in the survey includedin this thesis. This resulted in a four display application, each showing a different aspect ofthe chosen data sets that consisted of climate data. The result shows how effective multiplelinked views are in order to understand different characteristics of the data.