[CF-metadata] CF data model

David Hassell david.hassell at ncas.ac.uk
Thu Jul 20 09:18:14 MDT 2017


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

​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

​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 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
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