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
