2016
DOI: 10.1002/hyp.10811
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Data rules: from personal belonging to community goods

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Cited by 5 publications
(10 citation statements)
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“…Additionally, the KCS database contains more than 15 million datapoints on water chemistry, and even more data from long‐term, high‐resolution timeseries on physical parameters. The KCS database builds on a concept we call FAIR & Square (Laudon & Taberman, 2016), which is guided by Data FAIR port requirements (https://www.datafairport.org/). While FAIR stands for Findable, Accessible, Interoperable, and Reusable, “Square” symbolizes the importance of acknowledging the original data producer.…”
Section: Research Infrastructurementioning
confidence: 99%
“…Additionally, the KCS database contains more than 15 million datapoints on water chemistry, and even more data from long‐term, high‐resolution timeseries on physical parameters. The KCS database builds on a concept we call FAIR & Square (Laudon & Taberman, 2016), which is guided by Data FAIR port requirements (https://www.datafairport.org/). While FAIR stands for Findable, Accessible, Interoperable, and Reusable, “Square” symbolizes the importance of acknowledging the original data producer.…”
Section: Research Infrastructurementioning
confidence: 99%
“…By providing an open-access research infrastructure and database, our ambition is to contribute to the scientific and societal needs of future generations at a time when the continuation of long-term research and monitoring programs is under serious threat. By providing freely available hydrology and water chemistry data, and a fully accessible research infrastructure, 97 we hope that the KCS will continue to allow empiricists and modelers to combine efforts toward advancing the field of catchment science.…”
Section: Process-based Research For the Futurementioning
confidence: 99%
“…The intention behind initiating this special issue jointly in HESS and ESSD was to emphasise the role of open data for progress in hydrological research. Reproducibility is seen as one of the basic principles of good scientific practice and requires access to the data and code that were used to produce the respective findings (Hutton et al, 2016;Laudon and Taberman, 2016). For data management and stewardship, widely accepted rules have been defined in the FAIR principles: findability, accessibility, interoperability and reusability (Wilkinson et al, 2016).…”
Section: Merits Of Full Data and Code Availabilitymentioning
confidence: 99%
“…Uncountable observations, experiments and models have advanced our understanding of the soil-vegetation-atmosphere system. Landscape organisation appearing as self-similar patterns (Rodriguez-Iturbe and Rinaldo, 1997), structured flow paths (Flury et al, 1994;Nimmo, 2016), thermodynamic optimality (Kleidon and Schymanski, 2008;Phillips, 2016) and other forms has always driven approaches to derive the relationship between the dominating hydrological and biogeochemical processes (Lin, 2010;Laudon and Sponseller, 2018) and identifiable landscape signatures (Gharari et al, 2011). Likewise, we can find a plethora of concepts about hydrological functioning aiming to explain landscape organisation based on self-reinforcing patterns out of smaller-scale heterogeneity (Hohenbrink and Lischeid, 2015;Berkowitz and Zehe, 2020), the transition of their impact through scales (Vogel and Roth, 1998) and their dynamic similarity (Loritz et al, 2018).…”
mentioning
confidence: 99%