The impact of the adoption:
With the operational application for Dynamic Data Citation the data becomes significantly more attractive for data analysts. The user gets a dynamic generated citation text, which contains the original author, label of the dataset, versions, selected and applied subsetting parameters as well the alignment to the persistent identifier. For a new created and published subset, all metadata are inherited from the original ones and supplemented by the defined arguments, like the adapted bounding box, observed parameter and the name of the subset creator.
If we had not adopted the Dynamic Data Citation Sub-Set Service, our users would be forced to download data themselves and thus create an unintended first disruptive point against data provenance information. Data would still, for example, be prepared by selecting the area of interest and time range on the user’s desktop computer. Dynamic data citation clearly increases the handling of data quality through redraw-able corrections and improvements.
The CCCA-Data Centre Software components are Open Source and published on GitHub.
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