1. Introduction The IMBER SSC created a DMC, which has made three major proposals: Educate, change the negative ethos Help you to do DM by creating a cookbook of simple guidelines Advocate that every IMBER project or cruise identify a Data Scientist to help with DM

2. Writing papers Writing papers is an essential part of a researchers job Writing papers is time consuming Writing papers is tedious/boring Writing papers needs attention to detail Publications are a legacy of your research

3. Data management Data management is an essential part of a researchers job Data management is time consuming Data management is tedious/boring Data management needs attention to detail Data sets are a legacy of your research potentially more objective than your publications, and available for re-interpretation

4. So why do we accept that we must write papers, but treat DM as the poor relation? Because we get recognition for publishing Publish or perish But we dont get recognition for DM Lets try to change that

5. Recognition for DM Carrots and sticks Stick –No more funding Carrots –Referenceable data sets using DOIs (Digital Object Identifiers) - SCOR/IODE initiative –Give help with DM – develop a cookbook –Data Scientist will look good on your CV

6. Example 1 Example of data spreadsheet submission to the BODC

7. Good filename Good data set title Good overall data organisation Good explicit column headers

8. Use consistent data format – use a number to indicate a missing numerical value and use text to indicate a missing text value Avoid blank cells unless the value is missing Do not mix characters and numbers in same field Avoid free text for dates – best to use separate columns for year, month, day. Definitions need to be explicit

9. Example guideline 2

10. Example guideline 2 map stations

11. Some suggestions Talk to a Data Centre from the start Fill in Metadata right from the start Delegate someone to help right from the start Follow the guidelines in the cookbook Maintain an Event Log during a cruise Take regular copies of notes and data

12. The bottom line DM cannot be an afterthought If you give DM some thought when you first plan a project, it will be –relatively straightforward –not too much effort –remarkably useful to all participants –valuable to those who come after Help is at hand: talk to Data Centre right at the start

13. So, what is a Data Scientist? The Data Scientist is someone who helps and advises the project/cruise Principal Scientist and researchers to document their data sets so that they are properly described The DS also interacts with PIs and Data Specialists to calibrate, validate, save and archive data Why is it FUN? - because you learn so much yourself by having to talk to people Can be full or part-time; paid or unpaid; hire, cajole or volunteer

14. What does the DS gain? Broadening your experience, learning from other PIs Advancing your own DM skills Great management training! (listening to others, looking for problems) Looks great on your CV You might even get paid

15. IMBER cookbook Draft version by Christmas Find it on-line via IMBER web site –Click on Data/How to do? Advise widely and seek your comments Create downloadable version + supporting templates etc (to take to sea)

16. IMBER cookbook demo

17. Summary Plan DM right at the start and allocate funds (5-10%, includes Data Centre time) Help us get the cookbook right Follow the guidelines in the cookbook Appoint/delegate/cajole somebody to be Data Scientist on a major project/cruise –Both he/she and you will benefit