Data growth in the environmental sciences has resulted in multidimensional datasets that are heterogeneous and extensive. Scientific academic research includes scalar, sensor, or vector data, which may be publically available. The datasets generated extend to local environmental groups whose trained citizens contribute to the surveillance of local habitats and ecological conditions that can potentially enhance various data analyses on a national and international level. While the abundance of environmental data is growing, tools to select, compare, and utilize the growing number of datasets generated from multiple institutions and groups are not keeping pace. This paper focuses on planning the construction of a dataset visualization that concentrates on the use of metadata to facilitate the identification, selection, and comparison of dataset information. It is presented in the visualization framework at the School of Information Sciences called VIBE (Visual Information Browsing Environment) and plans to adapt the Dublin Core Metadata Element Set as a basis for its development. In the long term, visualization may emerge not only as a primary tool for modeling environmental scientific metadata, but also as a mechanism used at the incipience of environmental scientific discovery.