1. NOCS, PML, STFC, BODC, BADC The NERC DataGrid + ++ + = Bryan Lawrence Director of the STFC Centre for Environmental Data Archival (BADC, NEODC, IPCC-DDC etc) Representing the NDG and a dose of the “Portals Project”

2. Royal Society, April, 2008 http://ndg.nerc.ac.uk British Atmospheric Data Centre British Oceanographic Data Centre Simulations Assimilation Complexity + Volume + Remote Access = Grid Challenge

3. Royal Society, April, 2008 Data Sets Ground based observation networks Met Office surface stations Model output NWP, ECMWF reanalyses & Climate models Satellite data TOMS, Envisat & MSG NERC programmes data UTLS, CWVC & URGENT “A collection of files with a common theme and administration” Datasets statistics 147 datasets ~130TB (unique) ~80 Million files

4. Royal Society, April, 2008 The NDG Use Cases 1.Find data 2.Find out about data 3.Subset and difference data 4.Visualise data 5.All using SECURE interdisciplinary technology. Sound easy doesn’t it? Want interdisciplinary semantic access to information, not abstract data –getData(potential temperature from ERA-40 dataset in North Atlantic from 1990 to 2000) –not: getData(“era40.nc”, ‘PTMP’, 20:50, 300:340, 190:200) –or even worse: for j=1990:2000 getData(“era40_”+j+“.nc”, ‘PTMP’, 20:50, 300:340)

5. Royal Society, April, 2008 The big: Climate in 2010 – A graphic Illustration Figures from Gary Strand, NCAR, ESG website

6. Royal Society, April, 2008 … and the little … land use!

7. Royal Society, April, 2008 ISO19109 in a nutshell

8. Royal Society, April, 2008 Dataset Metadata

9. Royal Society, April, 2008 MOVIE(s)

10. Royal Society, April, 2008 NDG Deployment Vocab Server: 120,000+ concepts 100 lists 75,000 Relationships (SKOS )

11. Royal Society, April, 2008 Dataset Metadata

12. Royal Society, April, 2008 MOLES: Metadata Objects for Linking Environmental Science A data production tool deployed at an observation station on behalf of an activity produces a dataset. Datasets have provenance

13. Royal Society, April, 2008 Getting down to the data itself A-Metdata We choose to deploy an “Application Schema” of the “Geographic Markup Language”. This allows us to define our data to support RE-USE by other communities – interdisciplinarity, and to be INSPIRE compliant!

14. Royal Society, April, 2008 CSML Dataset Dictionaries: coordinate reference systems, phenomena (parameters) units of measure Feature Collections CSML Features are SPECIALISATIONS of GML Features! Storage Descriptor Re-usable description of storage (NB: CSML Software Stack, WMS, WCS etc)

15. Royal Society, April, 2008 CSML Feature Types Abstract Specific: point data, time-series of point data, trajectory data, point collections, profiles, profile series, Ragged profile series, section, ragged section, scanning radar, grid, gridseries and swath

16. Royal Society, April, 2008 Beyond measuring things at points CF concepts: Cell-Methods (statistical e.g means etc) Cell-Bounds (intensive quantities, Extensive quantities, Relationship to coverage domain) New work: Exploiting Sensor Web Enablement

17. Royal Society, April, 2008 Storage Descriptor

18. Royal Society, April, 2008 Data Modelling Workshop April 2007, at The Cosenors House, Abingdon Brought NDG, Unidata, OGC, Italian NRC together to get a shared vision for scientific data types. Roadmap for bringing our activities together over next few years. Harmonising: –NDG CSML –OGC Observations and Measurements (with CSML and MOLES) –UNIDATA Community Data Model –INRC NCML-G

19. Royal Society, April, 2008 Data Model Relationships Route to harmonising GeoSciML and CSML

20. Royal Society, April, 2008 The Original Vision

21. Royal Society, April, 2008 What we’ve done (are doing) Schema: MOLES CSML DIF + Lots of Population Issues Protocols: OGC +OAI Pylons based portal Python WCS/WMS Clients CSML Toolbox Vocab Server Pylons Interface & portals

22. Royal Society, April, 2008 Now and the Future More protocol improvements (= wider community of providers and users) More deployment. More population. Evolution WITH the web.