contextualizing the visualization of climate data
DESCRIPTION
EGU 2014, 27th April - 2nd May 2014, Vienna (Austria) Session: Techniques and tools for effective visualization and sonification in the geosciences Category: Earth & Space Science Informatics (ESSI)TRANSCRIPT
Contextualizing the Visualization of Climate Data:
The CHARMe Project
Raquel Alegre
European Geosciences Union General Assembly 27th April – 2nd May 2014
Iryna Rozum Jon Blower Frank Kratzenstein Uni. of Reading ECMWF Uni. of Reading DWD
• Introduction to the CHARMe project
• Use of Open Annotation in CHARMe
• CHARMe system • CHARMe’s basic use case
• CHARMe’s advanced tools
Summary
Introduction to CHARMe
Introduction to CHARMe
Post-fact annotations
Introduction to CHARMe
Post-fact annotations
External events
Introduction to CHARMe
Post-fact annotations
External events
Data Provenance
Introduction to CHARMe
Post-fact annotations
External events
Data Provenance
User feedback
Introduction to CHARMe
Post-fact annotations
External events
Data Provenance
User feedback
Data policy
Introduction to CHARMe
Post-fact annotations
External events
Data Provenance
User feedback
Data policy
Results of assessments
Post-fact annotations
External events
Data Provenance
User feedback
Data policy
Results of assessments
CHARMe
Introduction to CHARMe
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
CHARMe plug-in
CHARMe plug-in
CHARMe plug-in
CHARMe plug-in
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
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
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
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…
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.
What's a Climate Dataset?
What's a Climate Dataset?
jpl.nasa.gov
What's a Climate Dataset?
jpl.nasa.gov
jpl.nasa.gov
What's a Climate Dataset?
jpl.nasa.gov
esa.int
What's a Climate Dataset?
esa.int
jpl.nasa.gov jpl.nasa.gov
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.
Some advanced use cases...
Climate data users discuss about data:
PML-SOLAS
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
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.
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.
Significant Events Viewer
• Significant Events are external events that can affect the results when recording or processing climate data:
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
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
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
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
Significant Events Viewer
The user selects datasets and events to plot alongside the data.
Significant Events Viewer
Data is plotted and displayed with an event timeline underneath.
Significant Events Viewer
Each flag represents an event. Further event’s info can be displayed.
Significant Events Viewer
Matching of events that can help explain data peaks.
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.
Record a comment about…
CHARMe Maps: some use cases
Record a comment about…
… the entire SST field within a multi-variable gridded dataset.
CHARMe Maps: some use cases
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
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
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
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
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
CHARMe Maps
CHARMe Maps
• Mockup showing how to enter comments
CHARMe Maps
Fine-Grained Commentary Tool
• Mockup showing visual intercomparison
CHARMe will provide a framework for the users to discover, understand and exploit climate data they need through commentary metadata and tools.
Conclusions
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
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
