Presentation Open Access
Stockhause, Martina; Lautenschlager, Michael
Climate research like CMIP (Coupled Model Intercomparison Project) and IPCC (Intergovernmental Panel on Climate Change) Assessment Reports, currently in their 6th cycle, depend heavily on data, which is well-curated and remains available on the long-term (see abstract by Juckes et al., 2018). To improve the traceability of climate research and assessments, the CMIP6 data sources need to be referenced. Data references and thus giving credit to data providers, their funders and contributors have been part of principles for Good Scientific Practice (e.g. DFG, 2013) for several years, but have not yet become a natural and effective part of research workflows.
For CMIP6 for the first time in the history of CMIP, it is possible to cite the evolving CMIP6 data on model/MIP and experiment granularities (Stockhause and Lautenschlager, 2017). A good example how to cite data in an article’s reference list is provided in the paper by Durack et al. (2018).
The CMIP6 data citation service enables data users to find data references:
Accompanying initiatives and projects such as the “Enabling FAIR Data” project (Stall et al., 2018) are developing best practices for the integration of data and other digital resources into author guidelines and the general research workflow in collaboration with academic publishers and repositories. Thereby data FAIRness (Findable, Accessible, Interoperable, Reusable data) in the Earth sciences is advanced.
Deutsche Forschungsgemeinschaft (DFG) (2013). Safeguarding Good Scientific Practice. doi:https://doi.org/10.1002/9783527679188.oth1.
Durack, P. J., et al. (2018). Toward standardized data sets for climate model experimentation, Eos, 99, doi:https://doi.org/10.1029/2018EO101751. Published on 02 July 2018.
Juckes, M., et al. (2018). The role of the IPCC Data Distribution Centre in supporting assessments of climate change, submitted abstract for “CMIP6 Model Analysis Workshop”, 25-28 March 2019.
Stall, S., et al. (2018). Advancing FAIR data in Earth, Space, and Environmental Science, Eos, 99, doi:https://doi.org/10.1029/2018EO109301. Published on 05 November 2018.
Stockhause, M., and M. Lautenschlager (2017). CMIP6 Data Citation of Evolving Data. Data Science Journal, 16, p.30. doi:https://doi.org/10.5334/dsj-2017-030.
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