The difficulties of a simple trail network

Jos Pyck VisitFLANDERS

Recreational trail networks in Flanders

• Managed by 5 provinces in Flanders

• Common guidelines and coordination by VisitFLANDERS

Recreational trail networks in Flanders #nodes length

Hiking 2769 8.377 km

Biking 3442 13.120 km

Horseback riding 328 1.171 km

Based on datasets published on http://data.toerismevlaanderen.be/

• Published as Open Data • Reused by app providers,

online routeplanning, publishers,…

• Reused by non-profit organizations and the public sector

The Challenge

Challenge

Users need route network data that is:

• for the whole of Flanders

• up-to-date

• geometrically correct (<3m accuracy)

• routable (route planners)

Place your screenshot

here

Challenge

5 different data sources: Provincial Tourist Organisations each have their own systems:

≠ data model

≠ ID’s

≠ topological consistency

Challenge

Manually merging 5 different data sources is

• error prone

• inefficient (lost updates)

• a huge coordination effort

• not timely (biking season has already started)

Challenge

Can we build a solution that automatically normalises, aggregates, and validates the data?

Challenge

VisitFLANDERS put forward these principles:

• provincial solutions remain the authentic source

• corrections are applied at the source

• stable ID’s (ID coupling table) and delta files must make updates lighter

• stable, canonical data model

• automated topological validation

Challenge

VisitFLANDERS put forward these principles: • provincial solutions remain the authentic source • corrections are applied at the source • stable ID’s (ID coupling table) and delta files must make

updates lighter • Connection of the provincial ID and the Flemish ID via ID

coupling table • stable, canonical data model • automated topological validation

Challenge

Topological validation rules for the output data:

each node must snap to a trajectory start or

ending.

Challenge

Topological validation rule for the output data: trajectories must not consist of multipart lines

FME Server (in the FME Cloud) to the

rescue

FME Server runs a workspace every hour

FME Server

GeoServer

Web Feature Service

WFS

API

File Server

Data Portal

(S)FTP HTTP(S)

API

Mail Server

E-mail reports SMTP

1. Get input data from provincial tourist organisations

2. Normalise the data

3. Assign stable Ids + Match edges

4. Validate topological consistency

5. Write output and delta file

FME Server runs a workspace every hour

Transformers: Joiner,

Neigborfinder, …

Transformers: Neigborfinder, Snipper, LineOnLineOverlayer,

… HTMLReportGenerator

PythonCaller (FTP) + FeatureReader

FME Cloud FME Server + PostGIS DB instance was started from FME Cloud. 100% scalable.

Place your screenshot here

The provinces get a daily e-mail with links to validation report (html / shp)

Results • Solution operational after 5 weeks • Provincial Tourist Organisations say the validation

report really helped to improve data quality • > 500 topological errors fixed at the source • VisitFLANDERS coordinated removal of duplicates and

edge matching at the borders (provinces)

Thank you!

Jos Pyck

Consulent Marketing Office

Toerisme Vlaanderen

Grasmarkt 61 - Brussel

toerismevlaanderen.be

data.toerismevlaanderen.be