1. Open Source Tools for Uncertainty Enabling the Model Web Benjamin Proß University of Münster FOSS4G, Denver, 12-16 Sept 2011

2. UncertWeb Data Encodings/Profiles Web Services Other Tools Overview

3. UncertWeb Facts Uncertainty-enabled Model Web, FP7 Project (http://www.uncertweb.org/) Feb 2010 – Jan 2013 8 Partners Aston University Italian National Research Council Food and Environment Research Agency Joint Research Centre Norwegian Institute for Air Research Eindhoven University of Technology University of Muenster Wageningen University

4. The UncertWeb concept The “model web”. When chaining services of limited or unknown quality, uncertainty must be accounted for if rational decisions are to be made. “UncertWeb develops mechanisms, standards, tools and test-beds for accountable uncertainty propagation in web service chains.”

5. Definitions Uncertainty –Model inputs E.g. through measurement errors of sensors Taking outputs of other models as inputs –Models itself By aproximating reality, models introduce errors, and should inform the user about (annotate its output with) the degree this happens

6. Biodiversity and climate change Land-use response to climatic and economic change Short term uncertainty-enabled forecasts for local air quality Individual activity in the environment Application Scenarios

7. Data encodings

8. UncertML is a dictionary and encoding for uncertain information. –JSON and XML encoding –Provides support for distributions, statistics and realisations. –Aim to cover a very wide range of uses: SWE, SBML, Semantic Web Uncertainty Model Language (UncertML)

9. Profiles

10. Profiles: specification or standard consisting of a set of references to one or more base standards and/or other profiles, and the identification of any chosen conformance test classes, conforming subsets, options and parameters of those base standards, or profiles necessary to accomplish a particular function In other words: –Restricts a base standard to suite a certain application purpose Why Profiling?

11. Vector Data: –GML Profile: Restriction of geometry types –ISO 19139 extension for uncertainty –O&M Profile: Spatio-temporal and result restrictions Raster Data: –NetCDF-U: extension of NetCDF for uncertainty values UncertWeb Profiles

12. Goal: provide easy-to-use and simplified profiles GML Profile used to encode vector-based geometries and features: Restrictions on Geometries Restrictions on Metadata O&M Profile: Uses GML Profile Restrictions on result types Common ways to encode uncertainties UW Profiles – Vector Data

13. Spatial Geometries –Point –LineString –Polygon –Grid Multigeometries –Collection for each of the geometries defined above (e.g. Multipoint, MultiLineString, etc.) Temporal Geometries: –TimeInstant, TimePeriod Uncertainty Property Type GML Profile

14. ISO 19139 Extension Extends DQ_QuantitativeResult with DQ_UncertaintyResult Used for resultQuality in O&M

15. O&M Profile - restrictions Spatial restrictions to SamplingFeature as defined in O&M Geometries of SamplingFeatures as defined in GML Profile Temporal Restrictions TimeInstant and TimePeriod according to GML profile resultQuality has to be ISO 19139 data quality Includes extension with Uncertainty result

16. O&M Profile – Observation Subtypes Measurement: result is double with uom info BooleanObservation DiscreteNumericObservation Result is integer TextObservation Result is String UncertaintyObservation Result is UncertML AbstractUncertainty ReferenceObservation Result is reference to e.g. file on a server

17. O&M Profile - Collections Collection for each observation subtype –MeasurementCollection –BooleanObservationCollection –…

18. Network Common Data Format support the creation, access, and sharing of array-oriented scientific data Structure: Header + Body: –Header defines variables –Body contains binary-encoded variable values NetCDF-U

19. NetCDF-U Header Example URLs to UncertML Dictionary

20. Goal: provide easy-to-use lightweight Java API for Information Models Is used in Web Service implementations for encoding/decoding of inputs and outputs UncertWeb Java APIs

21. Web Services

22. Web Services and Models Models not developed with automation in mind. –Can require a user interface. Wrappers enable them to be called with code (e.g. Java) in the service interface. –Write input files, run, parse output files into usable objects. –Mechanisms for running each model may vary substantially.

23. Service interface overview Open Geospatial Consortium (OGC): –WPS for processing (i.e. models). Including utility services for translating between uncertainty types. –WCS, WFS, WMS, SOS for data access. W3C Web Services (WS): –SOAP for information exchange. –WSDL for service description.

24. UncertWeb Proxy Service (UPS) –Proxy for (not uncertainty-enabled) model-WPS –Executes Monte Carlo simulations Uncertainty Transformation Service (UTS) –Transforms Uncertainties –E.g. distributions to realisations Spatio Temporal Aggregation Service (STAS) –Transforms different data into a common scale Use of WPS

25. Uncertainty Transformation Service Transforms Uncertainties –E.g. distributions to realisations Can handle: –UncertML (UncertML parser/encoder) –NetCDF-U (UncertWeb binary parser/encoder) –O&M R-backend

26. UncertWeb Proxy Service MonteCarloSimulation process Inputs: –Identifier of the process to be executed by the model-WPS –Uncertain inputs for the process –Static inputs for the process –URL of the model-WPS –Output uncertainty type (e.g. distribution or realisations) –Number of realisations (i.e. monte carlo runs) Outputs: –The specified uncertainty type

27. UPS Monte Carlo Service (UPS) Monte Carlo Service (UPS) SamplesRealisations Model Service (WPS) Model Implementation 1 Sample1 Realisation 1 Sample1 Realisation LOOP

28. UPS + UTS Monte Carlo Service (UPS) Monte Carlo Service (UPS) PDF Model Service (WPS) Model Implementation 1 Sample1 Realisation 1 Sample1 Realisation LOOP Uncertainty Transformatio n (UTS) Uncertainty Transformatio n (UTS) Realisations PDF Uncertainty Transformatio n (UTS) Uncertainty Transformatio n (UTS) PDF Samples

29. Local Air Quality Model Chain Demo chain with UncertWeb components Uncertainty enabled Austal model (UPS + WPS + UTS) Uncertainty enabled Austal model (UPS + WPS + UTS) UncertML JSON O&M Web-based Visualisation client Web-based Visualisation client INTAMAP service (WPS) INTAMAP service (WPS) Air quality observations (SOS) UncertML + GML Overlay Service (WPS + UTS) Overlay Service (WPS + UTS) UncertML realisations Interpolation of background concentration Estimation of air pollution from local emissions at point locations Adding both outputs to final concentration map

30. USOS/UWCS Can handle: –UncertWeb O&M profile (USOS) –NetCDF-U (UWCS)

31. SOAP/WSDL SOAP protocol. –Use in combination with information models (GML, O&M). –Standard fault messages. WSDL service description. –Available operations. –Required structure of messages, both request and response. –Where to find the service.

32. SOAP/WSDL Advantages: –Widely adopted by the rest of the web. –Tool support for generating code. –Compatibility with workflow software (Taverna, Kepler) and orchestration engines. Disadvantages: –Lack of semantics. –Not fully adopted by the OGC.

33. JSON A lightweight format for exchanging data. Preferred over XML for JavaScript client development. Used by Google, Facebook, Twitter...

34. Applying the technology Web service supporting two interfaces: SOAP/WSDL and JSON. Web service interface sits separately from model. Wrappers need to be developed so the interface can communicate with the model.

35. Other tools

36. Composition as a Service Offers functionality to –Create uncertainty enabled model chains –Execute them CaaS

37. Visualization tool Different visualizations of uncertainties in spatio-temporal data

38. Elicitator Expert elicitation of uncertainties E.g. parameters of distribution functions –Mean and standard deviation of a Gaussian normal distibution

39. Sensitivity Analysis tool Performs sensitivity analysis –Identify the influence of the different inputs to the model output

40. Links http://www.uncertweb.org/ http://uncertml.org/ https://svn.52north.org/svn/geostatistics/main/uncertweb

41. Thank you Questions? The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° [248488].