Hansi Senaratne

Learn More
With the ubiquity of advanced web technologies and locationsensing hand held devices, citizens regardless of their knowledge or expertise, are able to produce spatial information. This phenomenon is known as volunteered geographic information (VGI). During the past decade VGI has been used as a data source supporting a wide range of services, such as(More)
Visual analytics supports humans in generating knowledge from large and often complex datasets. Evidence is collected, collated and cross-linked with our existing knowledge. In the process, a myriad of analytical and visualisation techniques are employed to generate a visual representation of the data. These often introduce their own uncertainties, in(More)
With the increased availability of user generated data, assessing the quality and credibility of such data becomes important. In this article, we propose to assess the location correctness of visually generated Volunteered Geographic Information (VGI) as a quality reference measure. The location correctness is determined by checking the visibility of the(More)
Visualisation of uncertain geospatial data has become an intriguing part of uncertainty communication. Many methods, which vary from static to dynamic or interactive, have evolved to cater to different data and user requirements which are determined by parameters such as the measurement scale of the phenomenon, type of uncertainty bound, the data format and(More)
The presented work helps users of spatio-temporal uncertainty visualisation methods to select suitable methods according to their data and requirements. For this purpose, an extensive web-based survey has been carried out to assess the usability of selected methods for users in different domains, such as GIS and spatial statistics. The results of the survey(More)
Today, a tremendous source of spatio-temporal data is user generated, so-called volunteered geographic information (VGI). Among the many VGI sources, microblogged services, such as Twitter, are extensively used to disseminate information on a near real-time basis. Interest in analysis of microblogged data has been motivated to date by many applications(More)
Visualization of spatial data uncertainties is crucial to the data understanding and exploration process. Scientific measurements, numerical simulations, and user generated content are error prone sources that gravely influence data reliability. When exploring large spatial datasets, we face two main challenges: data and uncertainty are two different sets(More)
Visual analytics combines human and machine abilities to generate new knowledge from data. Within this process, uncertainty often plays an important role in hindering the sensemaking process and analysis tasks. On the machine side, uncertainty builds up from the data source level to the visual output. On the human side, these uncertainties often result in(More)
This paper presents the results of a web based survey assessing the usability of main uncertainty visualisation methods for users belonging to different key domains such as GIS and Climate change research. We assess the usability of the visualisation methods based on the user's performance in selected learnability tasks, in addition to assessing user(More)