Joan Masó, Ivette Serral and Xavier Pons

1. GeoViQua: a FP7 scientific project to promote spatial data quality usability: metadata, search and visualization Joan Masó, Ivette Serral and Xavier Pons Center of Research in Ecology and Forestry Applications (CREAF and UAB) Joan.Maso@uab.cat andcontact@geoviqua.org October 12th, 2011

2. The context • GEOSS is the Global Earth Observation System of Systems • Links existing and planned observing systems around the world • Supports the development of new systems where gaps currently exist • Promotes common technical standards and interoperability • GEOSS common infrastructure (GCI) • Allows accessing, searching and using the data, information, tools and services • The GEO Portal • The Components and Services Registry • The GEOSS Clearinghouse

3. GEOSS common infrastructure Main GEO Web Site Registered Community Resources GEOSS Common Infrastructure Client Tier Registries GEO Web Portals Community Portals Client Applications Components & Services Standards and Interoperability Business Process Tier Best Practices Wiki Community Catalogues Workflow Management GEOSS Clearinghouse User Requirements Alert Servers Processing Servers Access Tier GEONETCast Product Access Servers Sensor Web Servers Model Access Servers

4. Before GEOSS Access Tier Product Access Servers Model Access Servers Business Process Tier Community Catalogues Sensor Web Servers GEONETCast Community Resource User SBA Disasters Health Energy Climate Water Weather Ecosystems Agriculture Biodiversity

5. How GEOSS works today Components & Services Registry Standards and Interoperability Registry GEOSS Clearinghouse Catalogue Access Tier Product Access Servers DB GEO Web Portal Model Access Servers Business Process Tier Community Catalogues Sensor Web Servers GEONETCast GEOSS Common Infrastructure Community Resource User SBA Disasters Health Energy Climate Water Weather Ecosystems Agriculture Biodiversity

6. GEOSS Strategic Targets Data Management Before 2015, GEOSS aims to: 2. Provide a shared, easily accessible, timely, sustained stream of comprehensive data of documented quality, as well as metadata and information products, for informed decision making. This will be achieved through: Development of best practices, identified in the appropriate GCI registry, for observation, collection and access to data and information, including best practices for data quality assurance for both observing system data and information products http://www.earthobservations.org/documents/geo_vi/12_GEOSS Strategic Targets Rev1.pdf

7. Quality assurance framework QA4EO • This framework consists of a set of operational guidelines derived from “best practices” for implementation by the community. These guidelines have been collated into three theme areas: • Data Quality, • Data Policy and • Communication & Education • Each theme has an overarching “guiding principle” towards achieving interoperability. • Next meeting: - 20th October 2011. Hosted by Rutherford Appleton Laboratory (RAL) in Harwel, Oxfordshire, UK.

8. GeoViQua (265178) FP7 Collaborative Project Environment 10 partners with CREAF coordinating Duration: 36 months 1 February 2011 – 31 January 2014 Budget: 4.024.256,42 € EC Contribution: 3.266.803,98 € QUAlity aware VIsualisation for the Global Earth Observation system of systems

9. The team Universities Research centers Small or Medium Enterprises International producer

10. The problem • Is there quality information in the GCI? • There is some in the form of ISO19115 DQ elements and lineage • Not enough • GEOSS GCI does not follow a global model for quality • GEOPortal search and results • are not ranged by quality • quality indicators are not shown • Common data viewers do not generally include quality information in parallel with the data

11. The aim Quality Elicitation C R O S S S B A Dissemination Communitybuilding Geo-search Validation Pilot case studies Visualisation Standards GEO S&T Label GeoViQua will provide a set of scientifically developed software components and services that facilitate the creation, search and visualization of quality information on EO data integrated and validated in the GEOSS Common Infrastructure.

12. How GEOSS works today Components & Services Registry Standards and Interoperability Registry GEOSS Clearinghouse Catalogue Access Tier Product Access Servers DB GEO Web Portal Model Access Servers Business Process Tier Community Catalogues Sensor Web Servers GEONETCast GEOSS Common Infrastructure GEO Label Community Resource User SBA Disasters Health Energy Climate Water Weather Ecosystems Agriculture Biodiversity

13. From GEOSS-Centrism to User-Centrism • Enhanced geo-search tools • Quality-aware catalogue service • Quality-aware catalogue client • Quality aware visualisation components • Integrate of quality information • Show the quality information • Not only for GEOPortal and GCI. • Generic quality methodologies for GIS and RS • Components for map browsers, virtual globes, GIS and RS Delivery of solutions to end users Data quality elicitation mechanism Enhanced geo-search tools Quality aware visualisation tools Dissemination and Capacity Building

14. Pilot cases scenarios GEO Label Search & Visualization components

15. Time table Extraction from categorical variables Metadata extraction Best practices quality encoding Direct extraction from continuous variables User feedback Quality elicitation Validation Mobile Solutions Search & Visualization Prototypes Start Quality recommendations Data ready Testing solutions Pilot cases User & technical requirements to CoP User & technical solutions to CoP Workshops GeoLabel Proposals evaluation Final document December 2013 February 2011 January 2012 January 2013 2014

16. Data quality model • Types of uncertainty in four models of the geographic space • Typology of uncertainty of geospatial information MacEachren AM, A Robinson, S Hopper, S Gardner, R Murray, M Gahegan, E Hetzler (2005) Visualizing Geospatial Information Uncertainty; What We Know and What We Need to Know

17. ESDIN approach to quality (Antti Jakobsson) scope scope

18. Including data quality in search • SELECT  WHERE positional_accuracy < 20 and classification_correctness > 90%FROM GEOSS_GCI Enhanced geo-search tools Devillers R, Bédard Y, R Jeansoulin (2005) Multidimensional Management of Geospatial Data Quality Information for its Dynamic Use Within GIS

19. Quality visualization Quality aware visualisation tools Buttenfield, B. P., and R. Weibel. 1988. Visualizing the quality of cartographic data. Presented at Third International Geographic Information Systems Symposium (GIS/LIS 88), San Antonio, Texas.

20. Quality map visualization Quality aware visualisation tools • Dark color represents poorquality and light color goodquality • Quality Dashboard • In tables with different levels of detail Blackmond Laskey K, EJ. Wright PCG da Costa (2009) Envisioning uncertainty in geospatial information Devillers R, Bédard Y, R Jeansoulin (2005) Multidimensional Management of Geospatial Data Quality Information for its Dynamic Use Within GIS

21. Quality map visualization • Symbols with poor clarity for poorquality • Noise in the overlaid gridlines poorquality • Overlaid quadtree grid where smaller rectangles indicates less uncertainty (goodquality) Quality aware visualisation tools Griethe H, H Schumann (2006) The Visualization of Uncertain Data Methods and Problems MacEachren AM, A Robinson, S Hopper, S Gardner, R Murray, M Gahegan, E Hetzler (2005) Visualizing Geospatial Information Uncertainty; What We Know and What We Need to Know

22. 3D representations representation of estimated water balance surplus/deficit and their uncertainty (using bars above and below the surface). Main problems Makes visualization more complicated and difficult to understand Attracting the attention to the more uncertain objects!! Quality map visualization Quality aware visualisation tools Pang A (2001) Visualizing Uncertainty in Geo-spatial Data MacEachren AM, A Robinson, S Hopper, S Gardner, R Murray, M Gahegan, E Hetzler (2005) Visualizing Geospatial Information Uncertainty; What We Know and What We Need to Know

23. GEOLabel  GEO Label • What is it? • The GEO Label is intended to “assist the user to assess the scientific relevance, quality, acceptance and societal needs of the components” (ST-09-02 Task Team, 2010). • Purposes? • be a quality indicator for GEOSS geospatial data and datasets • Problem: Usability depends on data application; there is no defined threshold. • improve user recognition and trust in validated datasets. • Problem: who is going to certify this? • assist in searching by providing users with visual clues of dataset quality and relevance. • provide accreditation, provenance, monitoring • increase visibility of EO data • Emphasize in open access and easy availability • Possible shape? • Certification label • A formal way to present • quality indicators • provenance • attribution

24. GEOLabel GEO Label • GEOLabel questionnaire • Starting in the next GEO Plenary in November 2011. Istanbul. • Publicly available in the web for 3 weeks • We encourage you to participate!

25. http://twiki.geoviqua.org/twiki/bin/view/GeoViQua/GeoViQuaWorkshopsAny final suggestions for requirements in the project? Thanks Joan.Maso@uab.cat (CREAF)