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The HABITATS Approach to Build the
INSPIRE Infrastructure

Karel Charvát, Otakar Čerba, Štěpán Kafka,
Tomáš Mildorf, and Přemysl Vohnout
Help Service Remote Sensing
Neusiedl am See, October 9 2013
Technological objectives

• Data modeling and transformation
• Architecture design and implementation
Data Models and Transformation
Process
Input and information sources:

Content from project partners (questionnaires, inputs to deliverable),

Reports from the EU level, INSPIRE TWG BR-HB-SD,

Information from D3.1, D3.2 and INSPIRE TWG BR-HB-SD discussions,

Analysis of good practice from other EU projects such as Plan4all, Humboldt
Main tasks:

To assist end users to describe their current models using interactive
modelling tools

To develop training materials and provide training sessions for users.

To design the main transformation processes required for data sets, based on
the requirements activities
Basic Transformations
Two solutions for data merging

Basic data merge of data
maintained in multiple file
structure using free and
opensource desktop
application

Basic script for automated
data merge of data
maintained as multiple
files
Basic Transformations
Two solutions for data extracting
Basic SQL script for
geometry extraction from
multigeometry, further can
be used as one setep in
larger data transformation
process

Basic geometry extraction
from multigeometry using
free and opensource
desktop application
Advanced Transformations

Data Specifications 2.0

Harmonization
Habitats and
biotopes

FMI Data
Advanced Transformation –
Schema
Open SHP file
and its scheme
New data
model

Save final
SHP file

Reclassification
FMI → EUNIS
New Data Model
Existing FMI data model +
referenceHabitatTypeId: CharacterString
referenceHabitatTypeScheme: ReferenceHabitatTypeSchemeValue
localSchemeURI: URI
localNameValue: CharacterString

geometry: polygon
referenceHabitatTypeId: eunis_value
referenceHabitatTypeScheme: eunis
localSchemeURI: link_to_FMI_classification
localNameValue: FMI_classification_value
FMI Data
INSPIRE / Habitats
Data
Changing Architecture Paradigm
Reference Laboratory (RL)
The HABITATS Reference Laboratory is a central hub
with the support of global data, but also supporting cross
scenarios implementations, and the HABITATS pilot
applications, as implementations of single HABITATS pilot
cases, which will also be used for testing the sharing of
local data and metadata.
Relation of RL to Pilots
RL Architecture
RL Advanced Principles
RL includes all basic Geoportal Functionality, but
 Supports work with maps, not only with services,
 Extends the INSPIRE services – use of KML,

 Includes possibilities for Open Linked Data,
 includes an option for embedding objects into HTML web sites.
RL Approach
RL Approach
RL Approach
WordPress GeoBlog
INSPIRE in Pocket
Motivation
SuperCAT
For end-users operating services are crucial
 Availability
 Quality – service / data / metadata
Preparing catalogue of „clean services“ to ensure availability
First step - only WMS
Establishment of SuperCAT
Harvesting existing catalogues
Catalogues CSW 2.0.2 ISO AP 1.0
Only services (type=service)
Periodically (P1D)
Sources
 GEOSS registry
 INSPIRE geoportal
 Catalogues we know about
Problems
 No central catalogue / we don’t know about services
 Classical search engines did not succeed
 Many catalogues do not response
Steps Towards INSPIRE in Pocket
HS-CAT
View Services
Cadastral Parcels
KML Resources
Liberec Example
Liberec Example
Liberec Example
Thanks!
http://www.habitats.cz/

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The habitats approach to build the inspire infrastructure

  • 1. The HABITATS Approach to Build the INSPIRE Infrastructure Karel Charvát, Otakar Čerba, Štěpán Kafka, Tomáš Mildorf, and Přemysl Vohnout Help Service Remote Sensing Neusiedl am See, October 9 2013
  • 2. Technological objectives • Data modeling and transformation • Architecture design and implementation
  • 3. Data Models and Transformation Process Input and information sources:  Content from project partners (questionnaires, inputs to deliverable),  Reports from the EU level, INSPIRE TWG BR-HB-SD,  Information from D3.1, D3.2 and INSPIRE TWG BR-HB-SD discussions,  Analysis of good practice from other EU projects such as Plan4all, Humboldt Main tasks:  To assist end users to describe their current models using interactive modelling tools  To develop training materials and provide training sessions for users.  To design the main transformation processes required for data sets, based on the requirements activities
  • 4. Basic Transformations Two solutions for data merging Basic data merge of data maintained in multiple file structure using free and opensource desktop application Basic script for automated data merge of data maintained as multiple files
  • 5. Basic Transformations Two solutions for data extracting Basic SQL script for geometry extraction from multigeometry, further can be used as one setep in larger data transformation process Basic geometry extraction from multigeometry using free and opensource desktop application
  • 6. Advanced Transformations Data Specifications 2.0 Harmonization Habitats and biotopes FMI Data
  • 7. Advanced Transformation – Schema Open SHP file and its scheme New data model Save final SHP file Reclassification FMI → EUNIS
  • 8. New Data Model Existing FMI data model + referenceHabitatTypeId: CharacterString referenceHabitatTypeScheme: ReferenceHabitatTypeSchemeValue localSchemeURI: URI localNameValue: CharacterString geometry: polygon referenceHabitatTypeId: eunis_value referenceHabitatTypeScheme: eunis localSchemeURI: link_to_FMI_classification localNameValue: FMI_classification_value
  • 9. FMI Data INSPIRE / Habitats Data
  • 11. Reference Laboratory (RL) The HABITATS Reference Laboratory is a central hub with the support of global data, but also supporting cross scenarios implementations, and the HABITATS pilot applications, as implementations of single HABITATS pilot cases, which will also be used for testing the sharing of local data and metadata.
  • 12. Relation of RL to Pilots
  • 14. RL Advanced Principles RL includes all basic Geoportal Functionality, but  Supports work with maps, not only with services,  Extends the INSPIRE services – use of KML,  Includes possibilities for Open Linked Data,  includes an option for embedding objects into HTML web sites.
  • 21. SuperCAT For end-users operating services are crucial  Availability  Quality – service / data / metadata Preparing catalogue of „clean services“ to ensure availability First step - only WMS
  • 22. Establishment of SuperCAT Harvesting existing catalogues Catalogues CSW 2.0.2 ISO AP 1.0 Only services (type=service) Periodically (P1D) Sources  GEOSS registry  INSPIRE geoportal  Catalogues we know about Problems  No central catalogue / we don’t know about services  Classical search engines did not succeed  Many catalogues do not response
  • 23. Steps Towards INSPIRE in Pocket HS-CAT