Author ORCID Identifier
Alva Couch https://orcid.org/0000-0002-4169-1077
David G. Tarboton https://orcid.org/0000-0002-1998-3479
Environmental Modelling & Software
NSF, Office of Advanced Cyberinfrastructure (OAC), 1664061
NSF, Office of Advanced Cyberinfrastructure (OAC)
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
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.
Xue, Zhaokun, Couch, Alva, and Tarboton, David. “Map Based Discovery of Hydrologic Data in the HydroShare Collaboration Environment.” Environmental Modelling & Software, vol. 111, 2018, pp. 24–33. https://doi.org/10.1016/j.envsoft.2018.09.014.