Transforming EADRN into INSPIRE Hydrography

577 views

Published on

GO Publisher demonstration of transforming the EA Detailed River Network into the INSPIRE Annex I Hydrography Theme - presented at the UKLP Data Publishing Workshop Feb 2012 by Debbie Wilson

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
577
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Transforming EADRN into INSPIRE Hydrography

  1. 1. Transforming EA Detailed River Network into INSPIRE Annex I Hydrography Theme Debbie Wilson – Business Consultant debbie.wilson@snowflakesoftware.com UK Location Data Providers Event Thursday February 9, 2012
  2. 2. Introduction • Detailed River Network provides information about the River Network for England & Wales • Contains 3 layers: – DRN – DRNNODES – DRNOUTLINES • Falls within scope of the Annex I Hydrography Theme: – HydroNetwork <<Application Schema>>
  3. 3. Mapping DRN to HydroNetwork DRN DRNNODES fictitiousbeginLifeSpanVersion Mandatory property but assigned <<voidable>> stereotype so we can create a nilReason value = “Unknown” Reclassification of codelist values Conditional statements were used to transform values form one codelist to another using If-then-else logic Example: If flowDirection = 1 then output value is ‘inDirection’ Create references from DRNNODE to DRN – spokeStart & spokeEnd Relationship is defined in one direction from DRN to DRNNODES so had to join DRN table to DRNNODES twise
  4. 4. Mapping DRN to HydroNetwork DRN DRNNODES DRN to WatercourseLink: • 7 of 11 properties map to data in DRN table • 1 of 7 properties mapped required transformation (reclassification) • 1 of 11 properties can be derived using constants • 1 of 11 properties mapped to nilReason • 2 of 11 properties don’t apply in real-world so not mapped DRNNODES to WatercourseLink: • 3 of 9 properties map to data in DRNNODES table • 1 of 3 properties mapped required transformation (reclassification) • 2 of 9 properties can be derived using joins • 1 of 9 properties mapped to nilReason • 3 of 9 properties don’t apply in real-world so not mapped
  5. 5. Transforming data using GO Publisher Desktop Source Data Output XML Preview Sample Validate Sample
  6. 6. Create XML structure by grouping columns
  7. 7. Adding new content: inspireID/namespace
  8. 8. Deriving content using joins NOTE: These local object references can be replaced by a Linked Data URIs when publishing data via a web service to enable then to be retrieved. Example: http://location.data.gov.uk/so/hy/hydroNode/eaew.drn/ eaew1001000000066258/1
  9. 9. Reclassifying code values and creating NilReason values using conditional statements (if-then-else)
  10. 10. CRS Transformation
  11. 11. Publishing and Validating Data Copy Schema includes all the relevant schemas into output folder for exchange with data Output data can be raw xml or compressed (zip/gzip) Validate shall run in-built data validation to check data is: 1. Well-formed 2. Schema valid 3. Conforms to business rules/constraints (in production)
  12. 12. Publishing Data via WFS in 4 steps Step 1: Change mapping to output data within wfs:FeatureCollection not base:SpatialDataSet & update object references
  13. 13. Publishing Data via WFS in 4 steps Step 2: Configure GetCapabilities
  14. 14. Publishing Data via WFS in 4 steps Step 3: Bundle transformation configuration, WFS software and schemas, within WAR ready for deployment
  15. 15. Publishing Data via WFS in 4 steps Step 4: Deploy to application server and test
  16. 16. WFS Response: Get first 10 WatercourseLinks http://localhost:8080/Hydrography_DRN/GOPublisherWFS?service=wfs&version= 2.0.0&request=GetFeature&count=10&typenames=hy-n:WatercourseLink

×