Map based discovery of hydrologic data in the HydroShare collaboration environment. (January 2019)

• Record Type: Journal Article
• Authors: Xue, Zhaokun; Couch, Alva; Tarboton, David
• Is Part Of: Environmental modelling & software. Volume 111(2019)
• Page Start: 24
• Page End: 33
• Publication Date: 2019-01
• Subjects: Data discovery -- Data publication -- Open data -- Data sharing; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.09.014
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Data discovery refers to the process of locating pre-existing data for use in new research. In the HydroShare collaboration environment for water science, there are more than twenty kinds of data that can be discovered, including data from specific sites on the globe, data corresponding to regions on the globe, and data with no geospatial meaning, such as laboratory experiment results. This paper discusses lessons learned in building a data discovery system for HydroShare. This was a surprisingly difficult problem; default behaviors of software components were unacceptable, use cases suggested conflicting approaches, and crafting a geographic view of a large number of candidate resources was subject to the limits imposed by web browsers, existing software capabilities, human perception, and software performance. The resulting software was a complex melding of user needs, software capabilities, and performance requirements. Highlights: Hydrologic data can be discovered via maps of overlapping coverage. Maps must balance user expectations for performance with software capabilities. The HydroShare data discovery environment achieves such a balance via user-driven design. Overlapping area coverages are depicted by darkening overlapping regions. This depiction provides one solution to browsing large data collections using maps.