Map based discovery of hydrologic data in the HydroShare collaboration environment

• Published in: Environmental modelling & software : with environment data news Vol. 111; pp. 24 - 33
• Main Authors: Xue, Zhaokun, Couch, Alva, Tarboton, David
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.01.2019; Elsevier Science Ltd
• Subjects: Collaboration; Computer programs; computer software; Data collection; Data discovery; Data publication; Data sharing; Human performance; humans; hydrologic data; Hydrology; Information sharing; laboratory experimentation; Open data; Software; Data discovery; Data publication; Data sharing; Open data
• ISSN: 1364-8152; 1873-6726
• DOI: 10.1016/j.envsoft.2018.09.014

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. •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.