My perception of thefundamental problem

• Data are not sexy

• PI easily signs up to need to deliver

• But the published paper takes priority

• and then the next proposal takes priority

• Data managers are viewed as geeks

• who can only cajole, not enforce, data delivery

My perception of fundamental questions

• How can we raise the profile of data management?

• How can we persuade scientists to take it really seriously?

• NB carrot not stick e.g.– Funding specifically for data management– Show PIs how it can help them

Background - some of theGEOTRACES recommendations

• Appoint a Data Liaison Officer (DLO) at the IPO

• Appoint a Data Specialist on each Project to be responsible for data

• Agree time scales for data submission and release

• Use CCDHO for CTD and bottle data• Involve data management professionals in all

GEOTRACES data activities from the start

DLO responsibilities• Maintain a list of IMBER projects• Keep track of project metadata• Maintain a catalogue of actual and expected data sets (DIF) or

equivalent discovery metadata records (ISO19115 standard)• Ensure that standardized parameter descriptions are adopted (e.g.

the BODC parameter usage vocabulary)

• Ensure that protocols for naming of cruise, station positions, etc., adhere to a rule system developed by the DMC

• Interact with DAC(s) to coordinate their activities and interactions with PIs

• In particular, ensure timely delivery of metadata and actual data to the DAC(s)

• Contribute to (and possibly maintain) the project web-site

The DLO will be an ex officio member of the DMC, and will report to the Director of the IPO and to the DMC

Data Specialist

• Ensure that suitable log sheets have been provided for all activities

• Assist and support scientists in preparation of metadata

• Maintain regular checks that all logs are being correctly completed

• Assemble all metadata from a section or process study

• Assist with preparation of data files, ensuring that all necessary parameters are included

• Evaluate the quality of data, either by personal expertise or by discussion with PIs, and help to document quality and missing or suspect data

• Facilitate assembly of shipboard data sets and data integrity checks

Data Management for IMBER

• IMBER is a relatively young project• But has taken early initiatives on data

management• Sophie Beauvais appointed as Data

Liaison Officer (DLO) in May 2006• Data Management Committee (DMC)

appointed recently• DMC discussions by email/blog? Getting

off to a slow start - need to meet face to face

Data Management Committee

• Observationalists– Raymond Pollard, Jay Cullen

• Modellers (data users)– Wilco Hazeleger, Reiner Schlitzer

• Data specialists– Todd O’Brien, Gwen Moncoiffe, Toru Suzuki

Balanced to improve communication and mutual understanding

Data v metadata

• IMBER manages no projects so strictly owns no data

• IMBER can encourage but not enforce improved standards for both metadata and data

• Should DMC emphasize the minimum (basic metadata) or the maximum (streamlined access to data?)

• Answer: both

Metadata

• One view says it is hard enough to get decent metadata, so if we can achieve that it will be a major step forward

• Cruise Summary Report (CSR) - can we persuade all nations/labs to complete them (USA included)?

• Create DIFs at GCMD

Data

• Another view is that we must aim for accessible, high quality end data, arguing that nothing is more irritating than going through a dozen metadata links only to end up at “data - contact PI” - and of course the PI never answers

• Possible ways to achieve this– Seamless access to widely distributed data– Relatively small number of specialist data centres

• Both cost serious money

Specialist data centres(by which I mean, specializing in a particular type of data)

• CCHDO (CLIVAR and Carbon Hydrographic Data Office), at Scripps, was WHPO (WOCE Hydrographic Programme Office)

• COPEPOD, the global plankton database

Are these the way forward?

Why advocate specialist data centres?

• To gather in data from individuals to central archives

• To have the ability to quality check a particular kind of data

• To have specialist experience to help an individual PI

Useless without long term funding

Improving communication

• A major goal must be to get scientists and data managers talking to each other.

• Carrot, not stick. How can data specialists HELP scientists– Backup PIs data at early stage - security– Help with calibration– Help with validation– Long term archive– Answer requests for data

Summary - points for discussion

• Raise profile of data management

• Improve communication (meeting, blogs)

• Carrots (funding, recognition, support)

• Specialist data centres (cf WOCE)

• Metadata standards (CSR, DIF)

• Adequate manpower