EOS7.10

Good scientific practice requires research results to be reproducible, experiments to be repeatable and methods to be reusable. This is a particular challenge for hydrological research, as scientific insights are often drawn from analysis of heterogeneous data sets comprising many different sources and based on a large variety of numerical models. The available data sets are becoming more complex and constantly superseded by new, improved releases. Similarly, new models and computational tools keep emerging and many are available in different versions and programming languages, with a large variability in the quality of the documentation. Moreover, how data and models are linked together towards scientific output is very rarely documented in a reproducible way. As a result, very few published results in hydrology are reproducible for the general reader.
A debate on good scientific practice is underway, while technological developments accelerate progress towards open and reproducible science. This session aims to advance this debate on open science, collect innovative ways of engaging in open science and showcase examples. It will include new scientific insights enabled by open science and new (combinations of) open science approaches with a documented potential to make hydrological research more open, accessible, reproducible and reusable.

This session should advance the discussion on open and reproducible science, highlight its advantages and also provide the means to bring this into practice. We strongly believe we should focus on the entire scientific process, instead of the results alone, obtained in a currently still rather fragmented way.

This session is organized in line with other Open Science efforts, such as FAIR Your Science.

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Co-organized by HS1.2
Convener: Remko C. NijzinkECSECS | Co-conveners: Niels Drost, Francesca Pianosi, Stan Schymanski
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| Attendance Mon, 04 May, 16:15–18:00 (CEST)

Good scientific practice requires research results to be reproducible, experiments to be repeatable and methods to be reusable. This is a particular challenge for hydrological research, as scientific insights are often drawn from analysis of heterogeneous data sets comprising many different sources and based on a large variety of numerical models. The available data sets are becoming more complex and constantly superseded by new, improved releases. Similarly, new models and computational tools keep emerging and many are available in different versions and programming languages, with a large variability in the quality of the documentation. Moreover, how data and models are linked together towards scientific output is very rarely documented in a reproducible way. As a result, very few published results in hydrology are reproducible for the general reader.
A debate on good scientific practice is underway, while technological developments accelerate progress towards open and reproducible science. This session aims to advance this debate on open science, collect innovative ways of engaging in open science and showcase examples. It will include new scientific insights enabled by open science and new (combinations of) open science approaches with a documented potential to make hydrological research more open, accessible, reproducible and reusable.

This session should advance the discussion on open and reproducible science, highlight its advantages and also provide the means to bring this into practice. We strongly believe we should focus on the entire scientific process, instead of the results alone, obtained in a currently still rather fragmented way.

This session is organized in line with other Open Science efforts, such as FAIR Your Science.

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