#AGU2020: Maturity of Data and Metadata

ELightning presentation of AtMoDat project partners at the virtual AGU 2020.
  • When Dec 15, 2020 05:35 PM to Dec 16, 2020 05:40 AM (Europe/Berlin / UTC100)
  • Where AGU 2020
  • Attendees Amandine Kaiser (German Climate Computing Centre (DKRZ)), Daniel Heydebreck (German Climate Computing Centre (DKRZ)), Anette Ganske (Technische Informationsbibliothek (TIB)), Angelina Kraft (Technische Informationsbibliothek (TIB))
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Data maturity describes the degree of the formalisation/standardisation of a data object with respect to FAIRness and quality of the (meta-) data. Therefore, a high (meta-) data maturity increases the reusability of data. Moreover, it is an important topic in data management, which is reflected by a growing number of tools and theories trying to measure it, e.g. the FAIR testing tools assessed by RDA1 or the NOAA maturity matrix2.


If the results of stewardship tasks cannot be shown directly in the metadata, reusers of data cannot easily recognise which data is easy to reuse. For example, the DataCite Metadata Schema does not provide an explicit property to link/store information on data maturity (e.g. FAIRness or quality of data/metadata). The AtMoDat project3 (Atmospheric Model Data) aims to improve the reusability of published atmospheric model data by scientists, the public sector, companies and other stakeholders. These data are valuable because they form the basis to understand and predict natural events, including the atmospheric circulation and ultimately the atmospheric and planetary energy budget. As most atmospheric data has been published with DataCite DOIs, it is of high importance that the maturity of the datasets can be easily found in the DOI’s Metadata. Published data of other fields of research would also benefit from easily findable maturity information.

Therefore, we developed a Maturity Indicator concept and propose to introduce it as a new property in the DataCite Metadata Schema. This indicator is generic and independent of any scientific discipline and data stewardship tool. Hence, it can be used in a variety of research fields.


1 https://doi.org/10.15497/RDA00034

2 Peng et al., 2015: https://doi.org/10.2481/dsj.14-049

3 www.atmodat.de