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Plans and targets for WP3: Data quality elicitation mechanisms

Plans and targets for WP3: Data quality elicitation mechanisms. Dan Cornford d.cornford@aston.ac.uk Aston University Birmingham, UK. Overview of WP3. Main tasks [partners] Task 3.1 Metadata extraction quality component [CREAF, UAB, S&T]

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Plans and targets for WP3: Data quality elicitation mechanisms

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  1. Plans and targets for WP3:Data quality elicitation mechanisms Dan Cornford d.cornford@aston.ac.uk Aston University Birmingham, UK

  2. Overview of WP3 • Main tasks [partners] • Task 3.1 Metadata extraction quality component [CREAF, UAB, S&T] • Task 3.2 Semi-automatic collocation including EO and in-situ (CAL/VAL) data [AST, S&T, 52N, UREAD] • Task 3.3 Computation and validation of quality indicators for continuously-valued data[AST, 52N, UREAD, S&T] • Task 3.4 Quality indicators for categorical variables [AST, 52N] • Task 3.5 User feedback and quality assessment of data sets in GEOSS [FRAUN, S&T, AST, CREAF]

  3. Task 3.1 Metadata extraction quality component[CREAF, UAB, S&T] • Main activities • extract quality information from existing metadata using model developed in Task 6.1 (UncertML in metadata) • provide a common model for all metadata based on ISO19115 – links to GIcat (CNR)? • provide a software tool to help harvest existing metadata and integrate this into a common model • Issues • who does what • links to existing software

  4. Task 3.2 Semi-automatic collocation including EO and in-situ (CAL/VAL) data[AST, S&T, 52N, UREAD] • Main activities • develop methodology for collocation of data sets, in particular gridded data using space-time interpolation methods (data assimilation?), supporting uncertainty and spatial support • implement a software tool for continuous valued variables that allows collocation of observations, particularly for gridded data, but also for point sensor observations • Issues • who will do what: AST / 52N develop theory, 52N / S&T implement, UREAD requirements?

  5. Task 3.3 Computation and validation of quality indicators for continuously-valued data[AST, 52N, UREAD, S&T] • Main activities • use tool from Task 3.2 to compute quality indicators – to populate quality metadata – implement as a service • explore the possibility of developing more sophisticated, e.g. spatially varying quality indicators, consulting users • create a software tool to validate quality indicators statistically • Issues • who will do what: AST / 52N develop theory, 52N / S&T implement, UREAD requirements? • how does this link to the GEO portal?

  6. Task 3.4 Quality indicators for categorical variables[AST, 52N] • Main activities • extend tool from Task 3.2 to compute collocations for discrete valued (categorical) observations • enhance tool from Task 3.3 to compute quality indicators for categorical variables – to populate quality metadata – implement as a service • Issues • who will do what: AST / 52N develop theory, 52N implement? • what is the scope and how sophisticated will the tool be?

  7. Task 3.5 User feedback and quality assessment of data sets in GEOSS[FRAUN, S&T, AST, CREAF] • Main activities • develop a system for user rating of data quality • integrate with GEO portal to enable users to add their ratings and comments to existing data resources • Issues • who will do what: FRAUN, S&T implement, AST provide guidance on trust and ecommerce, CREAF requirements? • what is the scope and how sophisticated will the tool be? • how linked in will it be with the GEO portal?

  8. Issues and next steps • Need to define the scope of the work. • Need to define the responsibilities • CREAF – metadata collection • AST – statistical aspects • 52N – implementation • UREAD – requirements and implementation? • S&T – integration and implementation • I will be talking to you all!!!

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