Contextualizing the Visualization of Climate Data
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The CHARME project aims to enhance the visualization and usability of climate data through open annotation, creating interconnected repositories of commentary information. It includes advanced tools for assessing uncertainties in climate products, visualizing relevant data, and allowing user interactions via a web-based platform. The project focuses on providing users with a framework to discover and understand climate data, which can also be applied to other fields.
Contextualizing the Visualization of Climate Data
- 1. Contextualizing the Visualization of Climate Data: The CHARMe Project Raquel Alegre European Geosciences Union General Assembly 27th April – 2nd May 2014 Iryna Rozum Jon BlowerFrank Kratzenstein Uni. of ReadingECMWF Uni. of ReadingDWD
- 2. • Introduction to the CHARMe project • Use of Open Annotation in CHARMe • CHARMe system • CHARMe’s basic use case • CHARMe’s advanced tools Summary
- 4. Introduction to CHARMe Post-fact annotations
- 5. Introduction to CHARMe Post-fact annotations External events
- 6. Introduction to CHARMe Post-fact annotations External events Data Provenance
- 7. Introduction to CHARMe Post-fact annotations External events Data Provenance User feedback
- 8. Introduction to CHARMe Post-fact annotations External events Data Provenance User feedback Data policy
- 9. Introduction to CHARMe Post-fact annotations External events Data Provenance User feedback Data policy Results of assessments
- 10. Post-fact annotations External events Data Provenance User feedback Data policy Results of assessments CHARMe Introduction to CHARMe
- 11. Post-fact annotations External events Data Provenance User feedback Data policy Results of assessments Sharing knowledge about Climate Data to help users judge fitness-for-purpose CHARMe Introduction to CHARMe
- 12. CHARMe plug-in
- 13. CHARMe plug-in
- 14. CHARMe plug-in
- 15. CHARMe plug-in
- 16. CHARMe node CHARMe node CHARMe node 3rd party system Data provider website • CHARMe will create connected repositories of commentary information • Annotations will be stored as RDF triples in “CHARMe nodes” The CHARMe system
- 17. CHARMe node CHARMe node CHARMe node 3rd party system Data provider website • Information can be read and entered through websites or web services. • Advanced tools can be developed that interact with the CHARMe nodes. The CHARMe system
- 18. CHARMe Annotation Metadata Climate Dataset Overlapping volcanic eruption I recently published a paper about this dataset CHARMe and W3C Open Annotation Does anyone know about other related datasets? http://www.someURL.com/dataset
- 19. CHARMe Annotation Metadata Climate Dataset Overlapping volcanic eruption I recently published a paper about this dataset CHARMe and W3C Open Annotation Does anyone know about other related datasets? http://www.someURL.com/dataset W3C Open Annotation is a natural fit for CHARMe…
- 20. CHARMe Annotation Metadata Climate Dataset Overlapping volcanic eruption I recently published a paper about this dataset CHARMe and W3C Open Annotation Does anyone know about other related datasets? http://www.someURL.com/dataset W3C Open Annotation is a natural fit for CHARMe… …plus it lets us record motivation, tags, author, time, have multiple targets.
- 21. What's a Climate Dataset?
- 22. What's a Climate Dataset? jpl.nasa.gov
- 23. What's a Climate Dataset? jpl.nasa.gov jpl.nasa.gov
- 24. What's a Climate Dataset? jpl.nasa.gov esa.int
- 25. What's a Climate Dataset? esa.int jpl.nasa.gov jpl.nasa.gov
- 26. What’s a Climate Dataset? Climate data often comes in 2D, 3D and 4D formats. The targets of the annotation can also be subsets of these.
- 27. Some advanced use cases... Climate data users discuss about data: PML-SOLAS
- 28. Some advanced use cases... Climate data users discuss about data: - Intercompare datasets - Research on events timing - Focus on specific areas of the world PML-SOLAS
- 29. Significant Events Viewer • Fully interactive web based tool • Under development at ECMWF. • Help to assess uncertainties in climate products to determine whether the climate signals represented by the product are real.
- 30. Significant Events Viewer • Fully interactive web based tool • Under development at ECMWF. • Help to assess uncertainties in climate products to determine whether the climate signals represented by the product are real. • Allows: • Visualization of relevant information about the data product (source, limitations, error estimates, etc.) • Search for alternative climate products. • Study of possible causes of variability, shifts and drifts apparent in the climate product.
- 31. Significant Events Viewer • Significant Events are external events that can affect the results when recording or processing climate data:
- 32. Significant Events Viewer • Significant Events are external events that can affect the results when recording or processing climate data: • Climate events: • Hurricanes • Volcanic eruptions • El-Niño index
- 33. Significant Events Viewer • Significant Events are external events that can affect the results when recording or processing climate data: • Climate events: • Hurricanes • Volcanic eruptions • El-Niño index • Software events: • Software cycle updates
- 34. Significant Events Viewer • Significant Events are external events that can affect the results when recording or processing climate data: • Climate events: • Hurricanes • Volcanic eruptions • El-Niño index • Software events: • Software cycle updates • Operational events: • Satellite or instrument failure • Operational changes to satellite orbit calculations
- 35. Significant Events Viewer • Significant Events are external events that can affect the results when recording or processing climate data: • Climate events: • Hurricanes • Volcanic eruptions • El-Niño index • Software events: • Software cycle updates • Operational events: • Satellite or instrument failure • Operational changes to satellite orbit calculations • Data/Observing system events: • How the data was obtained
- 36. Significant Events Viewer The user selects datasets and events to plot alongside the data.
- 37. Significant Events Viewer Data is plotted and displayed with an event timeline underneath.
- 38. Significant Events Viewer Each flag represents an event. Further event’s info can be displayed.
- 39. Significant Events Viewer Matching of events that can help explain data peaks.
- 40. CHARMe Maps • Interactive web map application • Based on previous efforts: • Godiva • ncWMS • Under development at DWD and Uni. of Reading • Will allow: • Visualization of 3D and 4D climate data (netCDF, HDF, OPeNDAP, …). • Visualization and insertion of fine-grained commentary metadata. • Visual intercomparison of data.
- 41. Record a comment about… CHARMe Maps: some use cases
- 42. Record a comment about… … the entire SST field within a multi-variable gridded dataset. CHARMe Maps: some use cases
- 43. Record a comment about… … the entire SST field within a multi-variable gridded dataset. … all SST data from 2006 from within a long gridded time series covering a given area. CHARMe Maps: some use cases
- 44. Record a comment about… … the entire SST field within a multi-variable gridded dataset. … all SST data from 2006 from within a long gridded time series covering a given area. … a particular pixel corresponding to the position of an in situ station CHARMe Maps: some use cases
- 45. Record a comment about… … the entire SST field within a multi-variable gridded dataset. … all SST data from 2006 from within a long gridded time series covering a given area. … a particular pixel corresponding to the position of an in situ station … a transect navigated by a scientific cruise who wants to start a conversation about their findings comparing their data with EO SST data CHARMe Maps: some use cases
- 46. Record a comment about… … the entire SST field within a multi-variable gridded dataset. … all SST data from 2006 from within a long gridded time series covering a given area. … a particular pixel corresponding to the position of an in situ station … a transect navigated by a scientific cruise who wants to start a conversation about their findings comparing their data with EO SST data …. a vertical section from a pixel of interest in an SST dataset to compare with buoy measurements. CHARMe Maps: some use cases
- 47. Record a comment about… … the entire SST field within a multi-variable gridded dataset. … all SST data from 2006 from within a long gridded time series covering a given area. … a particular pixel corresponding to the position of an in situ station … a transect navigated by a scientific cruise who wants to start a conversation about their findings comparing their data with EO SST data …. a vertical section from a pixel of interest in an SST dataset to compare with buoy measurements. … the particular differences found in an area or interest between CCI SST and CCI Cloud data. CHARMe Maps: some use cases
- 48. CHARMe Maps
- 49. CHARMe Maps
- 50. • Mockup showing how to enter comments CHARMe Maps
- 51. Fine-Grained Commentary Tool • Mockup showing visual intercomparison
- 52. CHARMe will provide a framework for the users to discover, understand and exploit climate data they need through commentary metadata and tools. Conclusions
- 53. CHARMe will provide a framework for the users to discover, understand and exploit climate data they need through commentary metadata and tools. It focuses on Climate Data, but its principles can be applied in many other fields. Conclusions
- 54. CHARMe will provide a framework for the users to discover, understand and exploit climate data they need through commentary metadata and tools. It focuses on Climate Data, but its principles can be applied in many other fields. CHARMe advanced tools are prototypes under development to demonstrate CHARMe usability. Conclusions