Assessing the state of research data publication in hydrology: A perspective from the Consortium of Universities for the Advancement of Hydrologic Science, Incorporated

Abstract

Many have argued that datasets resulting from scientific research should be part of the scholarly record as first class research products. Data sharing mandates from funding agencies and scientific journal publishers along with calls from the scientific community to better support transparency and reproducibility of scientific research have increased demand for tools and support for publishing datasets. Hydrology domain-specific data publication services have been developed alongside more general purpose and even commercial data repositories. Prominent among these are the Hydrologic Information System

Prescreening-Based Subset Selection for Improving Predictions of Earth System Models With Application to Regional Prediction of Red Tide

“…To better support transparency and reproducibility of scientific research, data and codes of scientific research should be part of the scholarly work, and must be considered and treated as a first-class research product ( Horsburgh et al, 2020 ). We follow the FAIR Guiding Principles for scientific data management and stewardship ( Wilkinson et al, 2016 ).…”

Social barriers to open (water) data

“…As summarized by Attard et al (2015), factors that can limit data discoverability in open portals include low metadata quality, simplistic search functionality, lack of ways to explore datasets to determine their relevance. Another factor cited in the case of HIS is the need for there to be a critical mass of data big enough to improve the chances of a scientist discovering data that they want to use and to keep using the repository (Horsburgh et al, 2020).…”

“…There is another barrier that lies at the intersection of open data and open science: the lack of rewards and incentives, which reduces the likelihood that a researcher will expend valuable time to work through the costs and risks of making data open (Bierer et al, 2017;Borgman, 2007Borgman, , 2012Burgelman et al, 2019;Saenen et al, 2019). In the context of water data, Horsburgh et al (2020) have identified lack of rewards and incentives for researchers as a key challenge inhibiting the publication of hydrologic data in open repositories. This can be viewed as part of larger problem of data sharing in the research community more broadly (Borgman, 2012;Flint et al, 2017;Wallis et al, 2013).…”

“…In the United States, these have commonly involved traditional data collecting agencies such as the U.S. Bureau of Reclamation and U.S. Geological Survey at the federal level, and state water agencies in New Mexico, Texas, California, and others (Blodgett et al, 2016; Colorado Water Conservation Board, 2020; Maidment, 2016; Myatt, 2019; Rea et al, 2015). Key roles are also played by inter‐state organizations such as the Western States Water Council's (2020) Water Data Exchange, and by nonprofit entities such as the Consortium of Universities for the Advancement of Hydrologic Science's (CUAHSI) (2020) Hydrologic Information System and HydroShare (Ames & Tarboton, 2015; Horsburgh et al, 2020); OpenET; and the Open Water Foundation. Water data have also become open as part of larger efforts such as the European Data Portal, http://environment.uk.gov, and the U.S. Open Data Initiative (USGSA, 2020).…”

“…When data are hard to access or it takes a long time to find them, the lack of discoverability or “findability” can be an impediment to the use and reuse of open data (Attard et al, 2015; Benitez‐Paez et al, 2018; Janssen et al, 2012; van der Waal et al, 2014). One of the reasons why the use of CUAHSI's Hydrologic Information System (HIS) repository has not grown as much as originally anticipated is due to lack of awareness among data providers of HIS and its services (Horsburgh et al, 2020). As summarized by Attard et al (2015), factors that can limit data discoverability in open portals include low metadata quality, simplistic search functionality, lack of ways to explore datasets to determine their relevance.…”