Testing INSPIRE data specifications

1. Testing INSPIRE data specifications Anders Östman Anders.Ostman@hig.se Imad Abugessaisa imad@fpx.se Xin He Xin.He@fpx.se

2. Implementation rules Metadata (ready) Information models (data specifications) According to themes listed in three annexes Network services Search services Viewing services Download services Transformation services Invokation services

3. Why testing? INSPIRE demands that the data specifications shall be balanced with respect to costs and benefits Transformation tests: Can the member states deliver data according to the specifications? At what cost? Applikation tests: Are the data specifications useful? Which benefits do they generate? We have mainly worked with transformation tests related to the data specifications for Annex I themes.

4. Five themes have been tested Adresses Geographical Names Cadastral Parcels Hydrography Transportation Networks

5. Method in brief INSPIRE schema NLS schema NLS database Data extraction Schema matching and mapping NLS shapefiles Source consistency test Shape to GML conversion Transformation rules Source GML files Schema transformation Schema transformation report Source data consistency report Schema matching & mapping report Target GML files

6. Schema translation A schema specify the structure of a dataset Schema matching – to find corresponding elements in the source schema and target schema Automation may be based on ontologies and semantic matching Schema mapping – to find rules for the transformation Simple: Datum -> text Difficult: Point -> polygon, different classification systems Schema translation – to make the translation

7. INSPIRE Feature & Attributes types Feasdla;ldk;alk NamedPlace sourceOfName Text typeLocal Geometry Identifier Language Conversion Rules ID-NR LMV Feature & Attributes types Feasdla;ldk;alk XKOORD, YKOORD SPRÅK Missing attributes referencePointMeaning relatedSpatialObject DETALJTYP endLifespanVersion levelOfDetail ORTNAMN URSPRUNG Ortnamn

8. Simple mappings Code lists -> Text string 2 numbers -> GML Point Integer -> Text string Datum -> Datum

9. Complicated mappings Reclassification, Ortnamn -> NamedPlaceType {BEBTX, BEBTÄTTX, KULTURTX, KYRKATX, NATTX, SANKTX VATTDELTX, VATTDRTX, VATTTX} -> {Others} {} -> {Road, BasicRoadLink, RoadNode, RailwayLine} {ANLTX} -> {Airport, Heliport, Others} {TERRTX} -> {MountainRange, Archipelago} {FÖRSAMLTX, KOMMUNTX, SOCKENTX, TRAKTTX} -> {Administrative Unit} {GLACIÄRTX} -> {GlacierSnowfield}

10. Matching of feature types

11. Matching of mandatory attributes

12. Summary of matching and mapping The Swedish Land Survey is able to deliver data to 11 of 14 schemas (79 %) For these 11 schemas, The Swedish Land Survey can deliver data to 55 % of the feature types (30 / 55) For these 30 feature types, the Swedish Land Survey can deliver 75 % of the mandatory elements (30 / 55) The corresponding value for optional elements is 30 % (102 / 342)

13. Some expensive problems CadastralParcel.Geometry is to be a simple polygon. About 7,5 % of the Swedish parcels are represented by a point or line. NamedPlace.Type, see previous slide RoadLink.FormOfWay: About 80 % are uncertainly classified RoadLink.RoadWidth: Classes shall be converted to width in meter

14. Metadata

15. Summary The GeoTest project is a part of the Swedish geodata strategy Transformation tests of data specifications in INSPIRE Annex I are performed The responsibility of each agency needs to be reviewed The cooperation among the agencies needs to be developed further Some transformations will be costly Current metadata do not comply to any standard

16. Solutions for GML Schema Transformation

17. Objective To evaluate existing tools for schema transformation Restricted to tools performing the operations in the XML/GML domain

18. Tested Tools Safe FME 2008 Desktop Altova MapForce 2009 Snowflake Go-publisher 1.4

19. FME 2008 Desktop

20. Altova MapForce 2009

21. Snowflake Go Publisher 1.4

22. Overview of tools

23. Types of transformation (Liljergren et.al 2006) Semantic transformations Source and target domains may be the same. Example: Swedish -> English. Domain transformations Different domains. May also include semantic transformations Coordinate transformation Geodetic reference systems, linear reference systems, …

24. Transformations being studied Strings and codelists (semantic + domain) Geometric transformations (domain) Levels of measurement (domain)

25. Strings and codelists

26. Geometric transformations

27. Levels of measurements

28. What is the best solution? FME can perform almost all transformations in the matrices. However, it lacks the ability to handle XML hierarchical structure. Both MapForce and GoPublisher can do this job. However, GoPublisher is not designed for schema transformation and lacks of developed functions and data interfaces. Luckily, MapForce is on the other side.

29. Conclusions No single tool can fulfill all requirements of the transformation between GML schemas; The best solution at present is to use FME and MapForce together. However, the efficiency of handling XML/GML files are not so high at this stage. E.g. GML files that only smaller than 50 MB can be handle by MapForce at our computers.

30. www.geotest.se