CCI Visualisation

Mike GrantPlymouth Marine Laboratory

With contributions from the CCI SEWG

Context

CCI Datasets User CommunitiesCCI modellersCCI EO teams

General ECV data users

Context

CCI Datasets User CommunitiesCCI modellersCCI EO teams

General ECV data users

(for data users)

Why visualisation?

● Ease of access– Quick looks– No giant downloads or special viewers

● Presentation– visual appeal, ease of use

● Data exploration and selection– Initially, what's the data like? (2nd stage discovery)– Then, which parts of the data are relevant (exploring)– Finally, data selection (filtering, analysis, download)

● Appropriate communication– Best method for communicating outputs

Performance considerations

● Must be reasonably fast...

● What does this mean?– Interaction with controls: instant response– Loading of image / map data: <5 seconds

– Graph creation: 5 – 30 seconds, depending on perceived complexity

● Running a complex process:– >10 seconds? People start thinking something is broken; use a spinner– >30 seconds? People think the spinner is broken/lying ; use a %– >2-3mins? Must be a background job with notification/popup

How to visualise?

● Most appropriate method depends..– Web page with text and graphics (report style)

– Image browser

– Map-based viewer

● Centralised vs distributed?– Generic central vs ECV-customised local portals?– Centralised services (e.g. @ CEMS) vs distributed

services (per ECV)?

● Technology is flexible - you choose

NASA OBPG L3 browser

Some current CCI approaches

● Sea Ice: THREDDS/Godiva mapping portal

● Ice sheets: web page reporting● GHG: image browser● Aerosol: custom online analysis tools● SST: OPEC mapping portal● OC: image browser, OPEC mapping portal● Soil moisture: mapping portal● ...

Aerosol online analytics

Sea Ice Godiva

Data selection

● Basic selection– specific areas of interest

– easily view different variables

● Quick statistics or community-standard metrics– sea regions (political or geophysical boundaries)– aggregated metrics (average chlorophyll, annual variation, sea ice

coverage, etc)

● More advanced methods– Temporal selection (time bar)

– Based on data (smarter filtering)

Data selection

● Research questions– Uncertainty-based selection– Non rectangular selections (polygon regions)– Content based search

● Final outcome of selection is some sort of onward processing– Export (subsetting, etc)

● Typically a download link or a subsetting/filtering service

– Feeding into online analytics

Online analysis● Mixed boundary between visualisation aids

and online data tools

● Graphing (2D)

● Dataset/variable comparison– side-by-side, flickering, sliding/slicing, transparency, 3D, colouration, ..

– Complementary variables (e.g. uncertainty, height, etc)

– Psychology matters

● Online processing– Metrics

– Derived variables (e.g. watershed computation)

– Models, validation processes

– Workbenches/TEPs, etc

– Generic flexible service chaining

Soil moisture data viewer

OPEC benchmarking tool (BC)

Template: basic

● “Out of the box” data exploration– More or less off the shelf, but customisation always required

● Appropriate interface– Web page, image browser, etc– Smoothly interactive map-based viewer

● WMS server, OpenLayers, Javascript

● Pleasant to look at and use (subjective!), performant● Relevant to the user community

– Link to textual info for more complex stuff– Well populated with useful data

● Maintained and monitored!GHG reporting page

Template: advanced

● WCS/OPeNDAP data services● Some processing capability (e.g.

scripted middleware) for online analysis

● Graphing with high quality output● Fixed comparisons of some kind● Online help / tutorials / guides

Intercomparison, Jon Blower

Template: state of the art

● Generic processing capability (WPS, WCPS)● Functionality for basic metrics (averaging areas, etc)● Animation● Flexible comparisons● Collaboration functionality

– Notes (CHARME?), shared / live-shared sessions

● Veering into data tools - see Carsten's presentation!

Things to ask about at coffee

● Security (can of worms)– Federated vs centralised vs fragmented vs open

● Search / discovery– Many options, though Google often makes us all look bad!

● Remote processing– Also see Carsten's presentation

● Related initiatives– GEOSS integration (registry)

– ESA TEPs

– Other online platforms (e.g. NASA Giovanni)

Open questions

● How best to visualise uncertainty?

● Can we cope with the data volumes?● Technical “big data services and visualisation” workshop in UK (12th

March, Harwell)

● How well will online processing be accepted?

● HCI/user interface challenges