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