Data citation is more than credit and more than DOIs

 Different stakeholders tend to discuss their specific interests in their separate communities:

• Scientific publishers focus on data references as part of the provenance information for a paper and basic reproducibility of its results.
• Researchers or data/paper authors are interested to get credit for their scientific results and the integration of data into common research impact metrics.
• Infrastructure providers want to connect scholarly information via PIDs such as DataCite and crossref DOIs or ORCIDs and ROR IDs.
• Long-term archives and data publishers contribute the data long-term preservation and the underpinning data services supporting the interests of the above stakeholders. They are essential to turn FAIRenabling into FAIRpreserving activities or in other words they are essential for sustainable data services.

The FAIR Guidelines (Pirani et al., 2022) introduced in the preparation of the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) were jointly developed and implemented by all stakeholders: the researchers and authors of the AR6, the scientific publisher IPCC, and the IPCC Data Distribution Centre (DDC) as infrastructure provider and long-term archive facility. 

The aim of the FAIR Guidelines, the enhancing the transparency of IPCC's output was approached in three aspects:

1. Traceability of key statements of the reports centered around the figure creation process and relating report to data;

2. Providing credit for input data and receiving credit for created final data underpinning figures; and

3. Long-term preservation of scripts as well as input, intermediate, and final data.

The IPCC FAIR Guidelines approach can serve as an example for a joint implementation of FAIR and TRUST principles including the interests and expertise of the different stakeholders.

Reference:
Anna Pirani, Andrés Alegria, Alaa Al Khourdajie, Wawan Gunawan, José Manuel Gutiérrez, Kirstin Holsman, David Huard, Martin Juckes, Michio Kawamiya, Nana Klutse, Volker Krey, Robin Matthews, Adam Milward, Charlotte Pascoe, Gerard van der Shrier, Alessandro Spinuso, Martina Stockhause, & Xiaoshi Xing. (2022). The implementation of FAIR data principles in the IPCC AR6 assessment process. Zenodo. https://doi.org/10.5281/zenodo.6504468.

How to find CMIP6 Data Citations (machine-access)?

The last post on April 2, 2020, explained how a human user can find CMIP6 data citations. For use cases where the data citation information was not stored during ESGF data download and many datasets have been analyzed, a script-based data citation access is required.

There are several APIs available at DKRZ, which are documented at https://www.wdc-climate.de/ui/cmip-api-docs/, and one provided by DataCite:

1. Citation Search API

In addition to the Citation Search GUI for human users, the Citation Search API provides flexible machine-access to selected CMIP6 data citations in JSON format. The response contains all components of a data reference and data use information:

http://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6search

Available filter options:

• filter by DRS:
•     mipEra
•     activityId
•     institutionId
•     sourceId
•     experimentId
• filter by granularity:
•     granularity=[exp|model]
• filter by date (in ISO 8601 format):
•     gePublicationDate=YYYY-MM-DD: DOI published at or after a given date
•     lePublicationDate=YYYY-MM-DD: DOI published before or at a given date

Sample Calls:

1. Data references on experiment (fine) granularity for a given source_id and activity_id:
   http://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6search?mipEra=CMIP6&activityId=CMIP&sourceId=HadGEM3-GC31-MM&granularity=exp
2. Update data references of request 1. with data references published at or after a given date:
   http://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6search?mipEra=CMIP6&activityId=CMIP&sourceId=HadGEM3-GC31-MM&granularity=exp&gePublicationDate=2020-01-01
3. Data references on model/MIP (coarse) granularity contributing to an activity_id available at a given snap-shot date:
   http://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6search?mipEra=CMIP6&activityId=ScenarioMIP&granularity=model&lePublicationDate=2020-03-31

 

2. Direct access using DRS_id

The content of the CMIP6 DOI landing pages is provided in two additional machine-readable formats: JSON and XML. The underlying metadata standard is that of DataCite 4 (see documentation: https://doi.org/10.14454/7xq3-zf69; schema definition: http://schema.datacite.org/meta/kernel-4/metadata.xsd):

http://cera-www.dkrz.de/WDCC/meta/CMIP6/
<mip_era>.<activity_drs>.<institution_id>.<source_id>[.<experiment_id>].[json|xml]

For possible values of the DRS (Data Reference Syntax) components, please check the CMIP6 Controlled Vocabulary at:
https://github.com/WCRP-CMIP/CMIP6_CVs. 

Example calls for json format:

a. Model/MIP granularity: 

http://cera-www.dkrz.de/WDCC/meta/CMIP6/CMIP6.CMIP.CNRM-CERFACS.CNRM-ESM2-1.json

b. Experiment granularity:  

http://cera-www.dkrz.de/WDCC/meta/CMIP6/CMIP6.CMIP.CNRM-CERFACS.CNRM-ESM2-1.1pctCO2.json

It is possible to use the ESGF Search API to collect these JSON urls for the 'experiment granularity' from the ESGF index. These 'citation_url's are part of every dataset information. More information on the ESGF Search API is available at: https://esgf.github.io/esg-search/ESGF_Search_RESTful_API.html

3. API to list data citations based on DRS components

A list of available CMIP6 data citations in a simple JSON response can be requested via an API:
https://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6Citations

Available attributes are combined as logical AND: institutionId, sourceId, complete (true|false), drsId.

• Search for all data references for an institution_id:
  https://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6Citations?institutionId=CNRM-CERFACS
• Search for all data references for a source_id from an institution_id:
  https://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6Citations?institutionId=CNRM-CERFACS&sourceId=CNRM-ESM2-1
• Search for all completed data references for an institution_id:
  https://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6Citations?institutionId=CNRM-CERFACS&complete=true
• Search for a specific data reference by drs_id:
  https://cera-www.dkrz.de/WDCC/ui/cerasearch/cerarest/cmip6Citations?drsId=CMIP6.CMIP.CNRM-CERFACS.CNRM-CM6-1

4. DataCite RestAPI to list data citations based on DRS components

DataCite also provides a RestAPI for the access of CMIP6 citation information with a registered DOI. It is documented at: https://support.datacite.org/docs/api . Examples for DataCite RestAPI requests are:

• Look-up of data citation information for a given DOI:
  https://api.datacite.org/dois/<DOI>
  https://api.datacite.org/dois/10.22033/ESGF/CMIP6.12104
  
• Search through all CMIP6 DOIs to extract information for specific DRS_ids:
  This requires a two step approach of

1. Access of all CMIP6 DOIs:
   https://api.datacite.org/dois?query=publisher:Earth%20System%20Grid%20Federation
2. Search through the entries in the JSON response to identify them by their DRS under 'attributes/subjects/subject' with subjectScheme='DRS', e.g.
   
   

   "id":	"10.22033/esgf/cmip6.14633",
   "type":	"dois",
   "attributes":	{
   "doi":	"10.22033/esgf/cmip6.14633",
   "identifiers":	[],
   "creators":	[…],
   "titles":	[…],
   "publisher":	"Earth System Grid Federation",
   "container":	{…},
   "publicationYear":	2021,
   "subjects":	[
   0	{…},
   1	{…},
   2	{
   "subject":	"CMIP6.PAMIP.MOHC.HadGEM3-GC31-MM.pa-futAntSIC",
   "subjectScheme":	"DRS" }], ...

                    

References and Links:
CMIP6 Citation Service: https://cmip6cite.wdc-climate.de
CMIP6: https://pcmdi.llnl.gov/CMIP6/
CMIP6 Registration/CV: https://github.com/WCRP-CMIP/CMIP6_CVs
DKRZ API documentation: https://www.wdc-climate.de/ui/cmip-api-docs/
DataCite: https://datacite.org
DataCite API documentation: https://support.datacite.org/docs/api

CMIP6 Citation Service in context of data citation principles and IPCC's 6th assessment cycle and its uncertain future

The CMIP6 Citation Service as part of the infrastructure for CMIP6 (Coupled Model Intercomparison Project Phase 6) enable the citation of CMIP data for the first time. Data references are planned to compliment paper references in the next IPCC (Intergovernmental Panel on Climate Change) assessment report AR6 (Stockhause et al., 2019). More specific IPCC author guidelines are about to be sent to the authors in early 2020. The goal is twofold:

• to improve the transparency of the AR6 by an increased traceability of its key results, and
• to give credit to the providers of source data analysed by the authors.

The IPCC author guidelines implement the general author guidelines for data citation developed within the 'Enabling FAIR data project' (Stall et al., 2017). Many publishers and repositories have subscribed these guidelines. Apart from FAIR (Findable, Accessible, Interoperable, Reusable), the long-term preservation and curation of the AR6 data in the trusted (TRUST: Transparency, Responsibility, Users, Sustainability, Technology) repository of the IPCC Data Distribution Centre (DDC) is part of IPCC's new author guidance.

The CMIP6 Citation Service itself recommends to cite input4MIPs (Durack et al., 2019) data as well as papers underpinning the CMIP6 data.

Implementation and maintenance as well as documentation and support for the CMIP6 Citation Service relies on institutional resources and an increasing share of my spare time. As many other infrastructure components for international projects, the service has no substantial nor long-term funding. Thus my institution has to be convinced that investing in the CMIP6 citation service is worthwhile, which requires

• usage numbers and
• user stories / feedback.

Thus, I cordially invite you to leave comments to share your opinion about the CMIP6 Citation Service - its value, your usage and experiences of it as well as your ideas for its further development and sustainable funding or anything else you want to share.

References and Links:
Durack et al. (2018). Toward standardized data sets for climate model experimentation, Eos, 99, https://doi.org/10.1029/2018EO101751. Published on 02 July 2018.
Stall et al. (2017). Enabling FAIR data across the Earth and space sciences, Eos, 98, https://doi.org/10.1029/2017EO088425. Published on 08 December 2017.
Stockhause et al. (2019). Data Distribution Centre Support for the IPCC Sixth Assessment. Data Science Journal, 18(1), p.20. https://doi.org/10.5334/dsj-2019-020.
Coupled Model Intercomparison Project Phase 6 (CMIP6): http://pcmdi.llnl.gov/CMIP6/
CMIP6 Citation Service: http://cmip6cite.wdc-climate.de 
CMIP6 Citatin Service Statistics: http://bit.ly/CMIP6_DOI_Statistics
Coalition for Publishing Data in the Earth and Space Sciences (COPDESS): http://www.copdess.org/enabling-fair-data-project/
Intergovernmental Panel on Climate Change (IPCC): http://www.ipcc.ch
IPCC Data Distribution Centre (DDC): http://www.ipcc-data.org