This document discusses linking real-time transport data in Ghent, Belgium. It addresses open data challenges like semantic domain modeling, scaling, and queryability. It presents examples of these challenges for parking data from multiple departments. The proposed solution is a large-scale information system using linked data principles of URIs, HTTP, and hypermedia-based querying. An example use case demonstrates determining suitable ontologies, mapping live data to them, and enabling federated querying of parking availability across data sources using semantic mappings. The results can be plotted on an interactive map.

1. Real-time
Linked Transport Data
in Ghent
Dieter De Paepe
Thimo Thoeye
Pieter Colpaert

2. A virtual Traffic Centre in Ghent

5. Open Data Challenges
Semantic domain modelling
Making sure we’re talking about the same things
Scaling
Providing a stable data source for many users
Queryability
Allowing users to ask broad questions

6. Example: Parking spaces
Semantic domain modelling
There are 4 departments that manage parking spaces that are “accessible for
people with disabilities”. Social service, roadworks, etc. Each uses a different
way of storing this information and terms are not re-used.
Scaling
Slowly, we are connecting more and more data sources to the triple store,
which forces services to think about shared semantics and concepts.
Nevertheless, a triple store is not scalable. We need to find a way in which
semantics can be fed back into the existing processes and tools (GIS, etc.)
Queryability
Right now, querying is done on the scale of 1 service/dept. Federated querying
remains a huge exercise and should definitely be improved.

7. Solution: a large-scale information system
Linked Data
use URIs for identifying and documenting things
HTTP with REST constraints
● Uniform interface
● Stateless
● Cacheable
Hypermedia based querying

8. Use case: availability of parking sites in Ghent
1. Determine suitable RDF ontologies
2. Map live data to these ontologies
3. Add metadata and hypermedia
4. Set up REST enabled webpage

9. Federated Querying using TPF
Data sources
● http://linked.open.gent/parking/
● http://data.linkeddatafragments.org/linkedgeodata
Query (link)
SELECT ?name ?free ?wktString WHERE {
?ParkingGent a <http://vocab.datex.org/terms#UrbanParkingSite>.
?ParkingGent owl:sameAs ?parkingLGD .
?ParkingGent rdfs:label ?name.
?parkingLGD <http://geovocab.org/geometry#geometry> [
<http://www.opengis.net/rdf#asWKT> ?wktString] .
?ParkingGent <http://vocab.datex.org/terms#parkingNumberOfVacantSpaces> ?free .
FILTER ( ?free > 200 )
}

10. And this can be used in a user-interface plotting
the updating availability based on this federated
query on a map
Tweakable code example:
http://codepen.io/pietercolpaert/pen/wgoPNV