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Publishing reproducible results supported by FAIR data

Authors: Nieva de la Hidalga, Abraham;

Publishing reproducible results supported by FAIR data

Abstract

We discuss two techniques for processing and analysing data that at the same time generate the required metadata to create FAIR digital objects. These objects can then be published as supporting information for the results obtained. This approach requires minimum intervention from the researcher performing the processing and analysis tasks. Consequently, these methods are ideal for improving the practices of publishing data, facilitate reproducibility of results, and support greater reuse of published data. Both techniques produce the metadata required for reproducing the results, including data used, parameters set at each stage, sequence of operations and mapping between inputs and outputs. The use of these type of tools reduces the work for documenting supporting data, enables comparison of results when varying parameters, and supports exploratory testing of different parameter combinations. 

Poster presented during the Annual Digital Catalysis & Catalysis-Related Sciences Conference 2023 (ADCR 2023) 2 - 3 November 2023 DECHEMA House, Frankfurt, Germany 

Related Organizations
Keywords

Publishing Research Data, Scientific Workflows, FAIR Data Objects, Metadata generator, Galaxy Workflows, Jupyter Notebooks

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green