Inspire in pocket dresden 2

559 views
487 views

Published on

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
559
On SlideShare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Inspire in pocket dresden 2

  1. 1. INSPIRE IN POCKETIs it possible to Integrate Smartphone’sand Tablets with INSPIRE infrastructure?Help Service - Remote SensingŠtěpán Kafka, Karel Charvát
  2. 2. From Habitats towards INSPIRE inPocket• The HABITATS project focused on the adoptionof INSPIRE standards through a participatoryprocess to design and validate environmentalgeo-spatial data, metadata, and servicespecifications with European citizens andbusinesses.
  3. 3. Habitats Data and Metadata Modeling• Define data and metadata models for thefollowing INSPIRE data themes:– 16. Sea regions– 17. Bio-geographical regions– 18. Habitats and Biotopes– 19. Species distribution• The results should be in compliance withINSPIRE directive and possible INSPIRE datamodels.
  4. 4. HABITATS benefits from participationin INSPIRE TWG Habitats project conceptual data model wasprepared short period before INSPIRE TWGwas established All HABITATS activities related to INSPIRE datathemes after establishment of TWG wasreported in TWG Feedback from TWG decisions guaranteedcomplete harmonization of HABITATSconceptual data models with INSPIREcorresponding Annexes
  5. 5. Data usage use cases• Regional data are used regionally• Global data are used regionally• Regional data are used cross-regionally (here worksINSPIRE)• Regional data are used globally (here works INSPIRE)• Global data are used globally (here works INSPIRE)
  6. 6. Regional data used regionally• There is not direct requirement for INSPIREdata models– Local data models could be wider– Local data models reflect regional needs and alsoregional decision processes– If data are not shared outside of region (but inmany cases it is necessary), in principle globalstandards are not needed– Standards are needed in case of more datasuppliers, to guarantee data consistence
  7. 7. Global data used regionallyGlobal data are in some content something like de facto standardsIn some cases it is necessary to be possible transform data intosuch models, which is required by regional decision processesThe global model has to cover regional decision needs (GMES casefor example)Open problems: the transformation happens either on fly or as pretransformeddata snapshotLanguage problem in the case on fly
  8. 8. Regional data used cross regionallyIn the case of cross border regions data harmonizationfaces extreme challenges.In many cases, for example tourism, we need to dealsimultaneously with several INSPIRE related datathemes. This is much more complex task than singledata theme case.In some applications data model could be broader thancorresponding INSPIRE definition.Open problem – how to manage multi lingual problems
  9. 9. Regional data used globally• Probably most relevant case for INSPIRE data model• The idea is to combine several local data sets intosingle standardized data set• The regional data has to be transformed (in manycases simplified) into global data model• Relevant cases are tourism, transport, education,research, environment protection, risk management,strategic decision• Language problem
  10. 10. Global data used globally• Global data are either standard or de factostandard.• It is expected that in the case of public sector dataINSPIRE compliance will be guaranteed.• Concrete application areas may require specifictransformation. Transformation could be based onFeature Encoding or Styled Layer Descriptor (SLD)
  11. 11. Basic transformationsBasic script for automateddata merge of datamaintained as multiple filesBasic data merge of datamaintained in multiple filestructure using free andopensource desktopapplicationTwo solutions for data merging
  12. 12. Basic transformationsBasic SQL script forgeometry extraction frommultigeometry, further canbe used as one setep inlarger data transformationprocessBasic geometry extractionfrom multigeometry usingfree and opensourcedesktop applicationTwo solutions for data extracting
  13. 13. Advanced transformationsData Specifications 2.0Habitats and biotopesHarmonizationFMI Data
  14. 14. Advanced transformation – scheme (1)Open SHP fileand its schemeSave finalSHP fileReclassificationFMI → EUNISNew datamodel
  15. 15. New data model (1)Existing FMI data model +referenceHabitatTypeId: CharacterStringreferenceHabitatTypeScheme: ReferenceHabitatTypeSchemeValuelocalSchemeURI: URIlocalNameValue: CharacterStringgeometry: polygonreferenceHabitatTypeId: eunis_valuereferenceHabitatTypeScheme: eunislocalSchemeURI: link_to_FMI_classificationlocalNameValue: FMI_classification_value
  16. 16. Data model mapping (1)
  17. 17. Taxonomy – reclassification(FMI → EUNIS) (1)0 Pine → G3.42,"4","Middle European *Pinus sylvestris+ forests"1 Oak → G1.87,"4","Medio-European acidophilous [Quercus] forests"2 Beech-oak → G1.82,"4","Atlantic acidophilous [Fagus] - [Quercus] forests"3 Oak-beech → G1.82,"4","Atlantic acidophilous [Fagus] - [Quercus] forests"4 Beech → G1.6,"3","*Fagus+ woodland"5 Fir-beech → G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland"6 Spruce-beech → G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland"7 Beech-spruce → G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland"8 Spruce → G3.1D,"4","Hercynian subalpine *Picea+ forests"9 Dwarp pine → F2.45,"4","Hercynian *Pinus mugo+ scrub"
  18. 18. Reclassification (1)
  19. 19. FMI DataINSPIRE / HabitatsData
  20. 20. Advanced transformation (2)CQLfilter
  21. 21. Advanced transformation (3)OntologyDescriptionNomenclaturesDerivedtransformationrules
  22. 22. Description in ontology (3)
  23. 23. Reference Laboratory• The HABITATS Reference Laboratory is a central hubwith the support of global data, but also supportingcross scenarios implementations, and the HABITATSpilot applications, as implementations of singleHABITATS pilot cases, which will also be used fortesting the sharing of local data and metadata.
  24. 24. Reference of RL to Pilots
  25. 25. RL Architecture
  26. 26. RL advanced principles• RL include all basic Geoportal Functionality, but– Support work with Maps not only with services– Extending of INSPIRE services – usage of KML– Include already possibilities for Open Linked Data– Embeded functionality
  27. 27. RL approach
  28. 28. RL approach
  29. 29. RL Approach
  30. 30. WordPress GeoBlog
  31. 31. IDEAS• INSPIRE is not commonly known• Heavy formats (GML)• For government …• INSPIRE data may be widely used• Portal is not everything• Need to have bridge (apps) making it accessible• Social apps may contribute INSPIRE !• Mobile technologies may help to disseminate
  32. 32. SOAP, CSW, WFS, GML …JSON, KML, …OFF-LINE / ON-LINE useSpecial apps rather than „portal“INSPIRE infrastructure
  33. 33. View servicesDefinujte vlastní zkratky!
  34. 34. CADASTER PARCELSDefinujte vlastní zkratky!
  35. 35. KML resources
  36. 36. FIELD EditingBatch postADAPTORWMS / WFS /KML /
  37. 37. Thanks for attentionKarel Charvatcharvat@hsrs.cz

×