AVISTED: Analysis and Visualization Toolset for Environmental Data
StatisticsView Usage Statistics
Climate modeled datasets are available on the internet for exploration by researchers in the field of environmental sciences. In order to get insight into these large datasets, which are often in varying data formats, climate researchers use data analysis and visualization tools. At present, most of the tools used in the environmental sciences require a user to download and execute software locally, which is inconvenient if the user’s computer does not have sufficient computing power and the size of the dataset is very large. To address this problem, in this dissertation we propose a new approach, the Analysis and Visualization Toolset of Environmental Data (AVISTED), aimed at supporting scientific research in environmental sciences. The novelty of the proposed approach lies in the combination of its features, which allows dataset upload, dataset management, data extraction based on the user’s requirements, data download in different data formats, and interactive data visualizations. The AVISTED approach is supported through a web-based toolset consisting of capabilities such as User Management, Model Output Management, Model Output, and Archives and Download. Additionally, the toolset supports CSV, ASCII, NetCDF and HDF5 environmental data formats. Also, a new and original approach for software design that links the GUI-Enhanced UML Activity Diagrams (GEAD) to user interface snapshots is proposed in the design phase of the AVISTED toolset. The proposed approach addresses some major challenges faced in the field of data analysis and visualization by supporting large datasets in varying data formats, providing several interactive visualization techniques, operating on a broad range of devices, and enabling reusability. AVISTED fills the gap between the tools available in the environmental sciences and the generic tools currently used for data analysis and visualization. Although the approach was aimed at assisting researchers in environmental sciences, it can be adapted to other areas where analyses of large datasets are needed. To demonstrate the capabilities of the AVISTED approach and toolset, the dissertation presents three application scenarios that illustrate various modes of operations and work with different data formats using the main features of AVISTED. Details of the proposed GEAD software design technique are also provided. A comparison with related approaches is included, and several directions of future work are also outlined in the thesis.