using spatial business intelligence for asset managementspatial bi foss4g2013
DESCRIPTION
The maintenance of waterways is expensive. Optimization of reconstruction projects can save money and limit hindrance for the public. In this presentation I show how the implementation of Spatial OLAP can give better insight in the quality of the construction of waterway banks. By spatially overlaying inspection results with construction records, a better estimation can be made about the overall quality, potential danger and repair costs. Spatial OLAP is an excellent way to provide insight into the different variables involved in the planning proces of maintenance.TRANSCRIPT
Using Spatial Business Intel l igence For Asset Management
Niels Hoffmann20 Sep 2013
2.5 million people2670 km2 55 municipalities
Planning and/or Funding:• Welfare• Environment, nature and landscape• Public transport• Culture• Infrastructure network
http://maps.noord-holland.nl/Dataportaalhttp://maps.noord-holland.nl/structuurvisie2040/
Province of Noord-Holland
Assets:• 656 km Roads• 254 km Waterways• 39 km Buslanes• 370 km Cycleways• 700+ bridges/tunnels etc.• ~ 60,000 trees
Infrastructure Budget 2014:€ 33.5 Million – maintenance€ 28 Million – new infrastructure
Province of Noord-Holland
ACTACT
PL
AN
PL
AN
DODO
CH
EC
KC
HE
CK
Asset ManagementOptimize Life cycle of assetsMinimize disturbance to the public
⇒ Cluster work in ‘trajecten’ ⇒ Every 12 yr major works⇒ Minor work every 6 yr
⇒ Data/Information about Assets and their performance
IMGeoDatamodel
NEN 2767-4Decomposition
Relational Datamodel
Business Intelligence
BI is ‘event’ driven
Sales:• What• When• Where • Who
Asset Management is about ‘events’ as well:
• Construction
• Inspection
• Maintenance
BI Tools should be a good fit for Asset Management.
What about Spatial BI?
Data Architecture
BGT / IMGeo
Asset DB
DWH
Asset DB
Kruispuntnr Kilometrage Roestvorming Scheefstand Natuurlijke aanslag Graffiti enz Materiaal bord Folieklasse
24408540,5
A+ A+ A A+ metaal III
Datamart
Datamart
Waterways have a lot of constructions:
Not all of it good quality…
NEN 2767-4Beheerobject Element BouwdeelKanalen Kerende constructie DamwandKanalen Oeverbescherming BeschoeiingKanalen Oeverbescherming Elementverharding
Relational
Quality information
Vaarweg Oevervak Orientatie hm_start hm_eind Inspectiedatm Kwaliteit_CROW288 Type_oever Functie_oeverbescherming LengteK20 080 Rechter
oever32,4 32,5 18-apr-12A Zetsteen Oeverbescherming 96
K20 081 Rechter oever
32,5 32,5 12-apr-12B Damwand staal
Grondkering 17
K20 082 Rechter oever
32,5 33,3 18-apr-12A Beschoeiing hout + zetsteen
Oeverbescherming 744
Dimensional
Pilot project to evaluate (spatial)BI Tools for Asset Management
• Pentaho BI Server• Mondrian• GeoMondrian• Saiku• GeoKettle
Pro’s and Con’s
GeomondrianSuper powerful
Lacking in usability
Performance seems to be a
problem with large datasets
No ‘drag and drop’ UI
Saiku (with ‘plain’ Mondrian)
Nice UI
User friendly
No spatial functionality
• Calculate spatial measures on loading
Conclusions
• Our relational model has strong attribute relations describing the spatial relations
• A user friendly UI is more important to us than spatial BI capabilities
• Pre-calculating spatial measures gives us the option to use ‘spatial’ relations in standard BI tools
Further plans
• Re-engineer datamarts for maximum flexibility
• Evaluate map UI’s like geojsp