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Nuno Oliveira
Andrea Aime
GeoSolutions
Publishing INSPIRE datasets
in GeoServer made easy with
Smart Data Loader and
Features Templating
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GeoSolutions
Enterprise Support
Services
Deployment
Subscription
Professional
Training
Customized
Solutions
GeoNode
• Offices in Italy & US, Global Clients/Team
• 30+ collaborators, 25+ Engineers
• Our products
• Our Offer
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Affiliations
We strongly support Open
Source, it is in our core
We participate in OGC
testbeds and get funded to
advance new open
standards
We support standards
critical to GEOINT
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Where are we?
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INSPIRE support in GeoServer
● INSPIRE Compliance we have (capabilities) full internationalization!
● Available specific INSPIRE extension
● Free and Open Source
● New GUI Sections on services
● Inject new elements in GetCapabilities
● Download Services
● OGC WFS 2.0 and GML 3.2.1
● OGC WCS 2.0.1 Enhancements in progress
● OGC API - Features GeoJSON (and GML)
● View Services
● OGC WMS 1.1.1, 1.3
● OGC WMTS 1.0.0
● Transformation Service
● OGC WPS 1.0.0, gs:Reproject process
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GeoServer App-Schema
● Official extension, part of releases
● PostgreSQL, Oracle, Solr and MongoDB
● Support for complex features:
1
2
3
4
5
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GeoServer App-Schema
● No special schema requirement on the data sources!
App-Schema produces the
expected GML output by
transforming data on the fly!
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HALE App-Schema plugin
● Available at (compatible with HALE 3.5.x):
●
http://hale-geoserver.geo-solutions.it/index.html
● Open Source visual editor for schema mappings!
● Main features:
● Import source schema(s) and data
●
Shapefile, databases, XSD / XML, etc…
● Import target schema(s)
●
XSD, databases, INSPIRE schemas
● Transformations are:
●
Graphically designed
●
Interactively executed
●
Interactively viewed
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HALE App-Schema plugin
Create GeoServer
App-Schema
mapping from it
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New mappings approaches
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Our use case
WARNING: Simple Didactical Example!
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What are the moving parts?
Data
Model
Data
Storage
Relational database
… and more
Complex UML
model
or equivalent
XML schema
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What are the moving parts?
Data
Model
Data
Storage
Publishing
Complex GML
or complex GeoJSON
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Welcome to app-schema
Data
Model
Data
Storage
Data
Mapping
Querying Building Publishing
The app-schema plugin does all this, maps the data
storage onto complex features, and eventually GML, to
match a given target XML schema
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The app-schema mapping file
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GML schemas lead the dance!
Currently the target GML schema is
the mandatory starting point
Just too hard for many, which
reduces the uptake!
But not all data is a flat table
what do we do?
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Smart data loader jumps in!
Data
Storage
Data
Mapping
Querying Building Publishing
Smart Data
Loader
Smart data loader maps flat tables to an automatically
generated complex structure. Valid complex output.
Separation of
concerns!
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Features templating jumps in!
Data
Modeling
Data
Storage
Data
Mapping
Querying Building Publishing
Smart Data
Loader Features
templating
Features templating allow to map an initial complex
model to a desired target structure with a template
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Flow of data overview
Domain
Model
OGC
Services
and
OGC APIs
GML
Output Format
GeoJSON
Output Format
JSON-LD
Output Format
Data
Smart Data Loader
Memory
Features
Stream
Features
Templating
HTML
Output Format
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Smart data loader
● Community module
● Will Automatically:
○ Walk the Data Source and produce a
Domain Model.
○ Generate an internal target GML
Schema and an internal App-Schema
Mapping.
○ Build an in-memory Stream of Complex
Features.
● Generates a valid complex GML and JSON
output, which might already be enough for
you!
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Smart data loader
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Smart data loader
● Choose the “root
entity”... the table that
is the center of your
model
● Automatic navigation
of foreign keys drives
the generation of tree
model
● Choose which parts
to include
● Automatically
generate app-schema
mapping
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Smart data loader
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Smart data loader
With GeoServer smart data
loader 😊, complex
features are no big deal —
publish them as easily as
simple ones!
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Features templating
● Community module
● What You See Is What You Get (WYSIWYG) approach:
○ Define how your features should appear with an example with
interpolations.
○ Query the dataset using the output format structure thanks to
backwards mapping capability.
● Integrated with both OGC API - Features, WFS and
WMS.
● Efficient Acts as a mapping over an in-memory
stream of features!
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Our use case (reminder)
WARNING: Simple Didactical Example!
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Stations GeoJSON template
1. {
2. "type":"FeatureCollection",
3. "features":[
4. {"$source":"stations"},
5. {
6. "Identifier":"${id}",
7. "geometry":"${position}",
8. "properties":{
9. "Name":"${common_name}",
10. "Code":"$${strConcat('STATION-', property('code'))}",
11. "Location":"$${toWKT(property('position'))}",
12. "Observations":[
13. {"$source":"observations"},
14. {
15. "Timestamp":"${time}",
16. "Value":"$${strConcat(strConcat(property('value'),
17. 'property('parameters.param_unit'))}",
18. "Type":"${parameters.param_name}"
19. }
20. …
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Stations GeoJSON template
1. {
2. "type":"FeatureCollection",
3. "features":[
4. {"$source":"stations"},
5. {
6. "Identifier":"${id}",
7. "geometry":"${position}",
8. "properties":{
9. "Name":"${common_name}",
10. "Code":"$${strConcat('STATION-', property('code'))}",
11. "Location":"$${toWKT(property('position'))}",
12. "Observations":[
13. {"$source":"observations"},
14. {
15. "Timestamp":"${time}",
16. "Value":"$${strConcat(
17. strConcat(property('value'),
18. 'property('parameters.param_unit'))}",
19. "Type":"${parameters.param_name}"
20. }
21. ]
22. }
23. }
24. ]
25. }
1. {
2. "type":"FeatureCollection",
3. "features":[
4. {
5. "Identifier":7,
6. "geometry":{
7. "type":"Point",
8. "coordinates":[11.34, 44.5]
9. },
10. "properties":{
11. "Name":"Bologna",
12. "Code":"STATION-BOL",
13. "Location":"POINT (11.34
44.5)",
14. "Observations":[
15. {
16. "Timestamp":"2016/28...",
17. "Value":"35.0 C",
18. "Type":"temperature"
19. },
20. {
21. "Timestamp":"2016/29...",
22. "Value":"80.0 Km/h",
23. "Type":"wind speed"
24. }
25. ]
26. }
27. }
28. (...)
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Creating the templates
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Live testing the templates
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Contextual template lookup
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Use cases highlights
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BRGM - Boreholes use case
● Demo with almost 1 million boreholes:
● Available through:
● WFS 2.0.0
● OGC API – Features
● Simple Features
(SF-0) and Complex
Features (SF-1)!
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BRGM - Boreholes use case
● Templated
JSON-LD
output!
● What You
See Is What
You Get!
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BRGM - Boreholes use case
● Filtering using CQL is supported:
● http://.../geoserver/ogc/features/collections/eposb:Borehole/items?f=applica
tion/ld+json&limit=50&filter=features.gsmlp:boreholeLength_m.om:amount>
83&filter-lang=cql-text
Filtering using the
JSON-LD
properties!
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BRGM - BDLISA QGIS Integration
● BDLISA, the French hydrogeological database
● QGIS needs a valid schema for loading the features:
Schemas can be
defined and then
linked to an
operation per
layer!
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BRGM - BDLISA QGIS Integration
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NPRA – DATEX II use case
● Complex GeoJSON served using WMS
and WFS!
● Norwegian Public Road Administration (NPRA).
● DATEX II (3.0), traffic related data:
We are using
GeoServer
MongoDB
Schemaless!