Hello, I'm pleased to announce that we (Karl Taylor, Bryan Lawrence, Jon Blower, Jonathan Gregory and I) have submitted a paper on the CF data model to Geoscientific Model Development (GMD), and that it is open to public comment as part of the review process until 2017-09-04. The full manuscript may be read, downloaded and commented on by all at http://www.geosci-model-dev-discuss.net/gmd-2017-154/ - you will need an account, but anyone can get one and it is easy to sign up.
We would like to encourage feedback via the GMD discussion site from all those who wish to provide it. This paper * describes the need for a data model of CF, * summarizes netCDF and the CF-netCDF conventions at version 1.6, * proposes a CF data model for version 1.6 of the conventions, * relates this data model to other data models for geoscientific data, * demonstrates a Python implementation (cf-python v2.0) of the CF data model. This work grew from the original data model proposed in trac ticket #68 <https://cf-trac.llnl.gov/trac/ticket/68> and further discussed in tickets #88 <https://cf-trac.llnl.gov/trac/ticket/88>, #95 <https://cf-trac.llnl.gov/trac/ticket/95> and #107 <https://cf-trac.llnl.gov/trac/ticket/107> - the last comment being over three years ago, now. These discussions couldn't find enough common ground to progress, partly because there wasn't a sufficiently comprehensive proposal on the table at that time. We hope that this paper will address this. The abstract: Title: A CF data model and implementation The CF (Climate and Forecast) metadata conventions are designed to promote the creation, processing and sharing of climate and forecasting data using Network Common Data Form (netCDF) files and libraries. The CF conventions provide a description of the physical meaning of data and of their spatial and temporal properties, but they depend on the netCDF file encoding which can currently only be fully understood and interpreted by someone familiar with the rules and relationships specified in the conventions documentation. To aid in development of CF-compliant software and to capture with a minimal set of elements all of the information contained in the CF conventions, we propose a formal data model for CF which is independent of netCDF and describes all possible CF-compliant data. Because such data will often be analysed and visualised using software based on other data models, we compare the CF data model with the ISO 19123 coverage model, the Open Geospatial Consortium CF netCDF standard and the Unidata Common Data Model. To demonstrate that the CF data model can in fact be implemented, we present cf-python, a Python software library that conforms to the model and can manipulate any CF-compliant dataset. We look forward to any comments from the CF community, all the best, David -- David Hassell National Centre for Atmospheric Science Department of Meteorology, University of Reading, Earley Gate, PO Box 243, Reading RG6 6BB Tel: +44 118 378 5613 http://www.met.reading.ac.uk/
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