Dynamic Data Visualization

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1 Dynamic Data Visualization Jon Blower Technical Director, Reading e-science Centre, University of Reading Head of Visualization and Applications Centre, International Space Innovation Centre

2 Motivation Earth Observation data are large, complex and varied Many data providers, wide variety of formats and data policies Quality of data is often unknown These are barriers to scientific insight and use in downstream services for societal benefit

3 The Digital Earth vision The tools we have most commonly used to interact with data are not really suited to this new challenge. I believe we need a Digital Earth. A multi resolution, three dimensional representation of the planet, into which we can embed vast quantities of data. Al Gore, California Science Centre, 1998

4 A view from science Unfortunately, visualization too often becomes an end product of scientific analysis, rather than an exploration tool that scientists can use throughout the research life cycle. Fox and Hendler Science 331 (2011),

5 What do we need? New approaches to visualization Accessible Interactive and exploratory Integrative (bringing multiple datasets together) Informative Engaging A highly interdisciplinary community Scientists Engineers Decision-makers Service providers

6 A new community Supported by the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (CEODE)

7 New tools and techniques

8 Geobrowsers Simple tools Simple data formats Google Earth Non-proprietary standards Google Maps Free or very low cost OpenStreetMap Accessible to all (often on the web) NASA World Wind Bing Maps (Microsoft)

9 Godiva2: extending the geobrowser

10 MyOcean : European Marine Core Service

11 Model-satellite intercomparison

12 OceanDIVA

13 OceanDIVA and Data Assimilation Control run (model only) After assimilation of observed data Model doesn t capture mode water Model now captures mode water Significantly reduced RMS errors

14 Quality control in ocean observations

15 From prototypes to services: International Space Innovation Centre Interactive visualization tools help to generate ideas Cross-sector partnerships take them forward to operational services

16 Science Visualization Service Earth Observation EO data products: primary production estimated from SeaWiFS data (NCEO/Plymouth Marine Laboratory) Exploration, visualisation and comparison of EO and climate model data on the web Climate model simulation: 1.5m temperature from HADGEM1 model (UKMO) Scientific tool, but also allows allows creation of images and animations for public engagement Web access to EO and climate data from CEDA archives and interface to videowall

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18 MetOcean Information Provision End to End (MIPe2e)

19 Conclusions The Digital Earth vision will drive many new uses of space-derived information Dynamic data visualization is a powerful new technique for gaining insight: Multi-scale: global to local Previewing large data holdings Intercomparison of diverse datasets Assessing data quality Diagnosing and improving forecast models Making data accessible to new audiences Open standards are important Does not necessarily mean open data! Developing operational services will require: New ideas plus the capacity to achieve them Cross-sector and international collaboration

20 Digital Earth is an integral part of other advanced technologies What including: can earth observation, the geo-information UK systems, global positioning systems, communication networks, sensor webs, electromagnetic identifiers, virtual reality, grid computation, etc. and China do Digital Earth should play a strategic and sustainable role in addressing such challenges to human society as natural resource together depletion, food and to water achieve insecurity, energy shortages, environmental degradation, natural disasters response, population explosion, and, in particular, global climate change. these goals? From the Beijing Declaration on Digital Earth, th International Symposium on Digital Earth, Beijing