OceanObs’09 Community White Paper Proposal
Meta-data Management in Global Distributed Observation
networks (tentative title)
Lead author:
Derrick Snowden
NOAA Climate Program Office, Climate Observation Division
1100 Wayne Avenue, Suite 1202
Silver Spring, MD 20910 USA
Derrick.Snowden@noaa.gov
Contributing authors:
Mathieu Belbeoch
JCOMM Observing Platform Support Center
8-10, rue Hermes
Parc Technologique du Canal
31526 Ramonville cedex
France
belbeoch@jcommops.org
Bill Burnett
NOAA National Data Buoy Center
1007 Balch Blvd.
Building 3203
Stennis Space Center, MS 39529-6000 USA
Bill.Burnett@noaa.gov
Ted Habermann
NOAA National Geophysical Data Center
325 Broadway
Building DSRC
Boulder, CO 80305-3328 USA
Ted.Habermann@noaa.gov
Hester Viola
JCOMM Observing Platform Support Center
8-10, rue Hermes
Parc Technologique du Canal
31526 Ramonville cedex
France
viola@jcommops.org
OceanObs’09 Community White Paper Proposal
Extremely raw bullets of topics to consider
** note that suggest we don’t talk about metadata recovery here at all, but focus on
how to avoid the mistakes of the past and improve for the future. **
This paper will describe the fundamentals of metadata, existing management
systems used, how and why these management methods could be improved and the
long term vision of metadata management across the global in-situ ocean observing
system.
Some of the elements of current metadata management systems will be described.
These systems have been designed based on weather forecasting requirements for
example the BUFR/CREX, ODAS, Pilot Projects such as Meta-T which until now
have not been standardized. Climate applications require more accurate data
metadata than weather forecasting and it is becoming apparent that the largest
uncertainties in the global ocean observation record can be traced to poor metadata.
This paper will describe different types or layers of metadata which are important
within the data flow for a global observing network.
 Sensor
 Measurement and/or Observation
 Instrument/platform/site
 Product (e.g. GTS Message or data/file or derived product or analysis or
climatology etc) layer (collection of same or different observations)
Metadata management for climate purposes must apply to individual sensors as well
as collections of observations and derived products. An explanation will be given of
examples of these different levels of metadata and discuss the different requirements
for metadata of stakeholders, for instance platform operators, program managers,
monitoring centers, data users
Some recent examples will be used to demonstrate how proper records of these
layers of metadata could have helped to avoid data issues and loss of utility of
datasets. These examples, which are specific to individual data flows highlight that
metadata must be managed through the lifetime of the observation (e.g. in the case
of recalibration, data quality assessments, modifications and flagging of
observations), at many distinct points in the data flow, not just at the time of
measurement. They also highlight that there is aneed to introduce better metadata
management to avoid similar issues in the future.
More general metadata requirements will then be discussed which relate to
the full data flow for ocean observations, and what is missing at the moment which
impacts data users and those monitoring observation programs (inc. network status
and data quality).
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Challenges?
Assessment of what’s missing for a better system, what are the main
metadata gaps
What needs to be done to identify and then fill gaps operationally in Future?
o Requires More than a Pilot Project! I agree with what you said, ie that
if the same methods to collect metadata are used in the
implementation of the Meta-T proposals (i.e. relying on people to enter
the required information manually and sometimes into multiple
OceanObs’09 Community White Paper Proposal
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systems) and as those have not been successful in the past - then
the methods proposed will not improve the situation
perhaps META-T’s main output will be this “gap analysis”
What’s the vision for meta-t and climate data users & long term –
sensor ML, smart/self reporting platforms,
operational metadata sharing based on what’s needed by users at all levels
(ability to opt into certain levels of metadata in the hierarchy),
unique identifiers for all measurements and groups of observations,
metadata reporting mechanisms enforced by international/regional/national
resolutions(? Like the Argo Notification requirement) with coordination of
standards and data content across multiple national efforts that collectively
make up GOOS
Remote and often expendable instruments that are never serviced after
deployment.