Using Spatial
Business Intelligence
For Asset
Management
Niels Hoffmann
20 Sep 2013
2.5 million people
2670 km2
55 municipalities
Planning and/or Funding:
• Welfare
• Environment, nature and landscape
• Pub...
Assets:
• 656 km Roads
• 254 km Waterways
• 39 km Buslanes
• 370 km Cycleways
• 700+ bridges/tunnels etc.
• ~ 60,000 trees...
ACTACT
PLANPLAN
DODO
CHECKCHECK
Asset Management
Optimize Life cycle of assets
Minimize disturbance to the public
⇒ Cluste...
IMGeo
Datamodel
NEN 2767-4
Decomposition
Relational
Datamodel
Business Intelligence
BI is ‘event’ driven
Sales:
• What
• When
• Where
• Who
Asset Management is about
‘events’ as well:
...
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 G...
Waterways have a lot of constructions:
Not all of it good quality…
NEN 2767-4
Beheerobject Element Bouwdeel
Kanalen Kerende constructie Damwand
Kanalen Oeverbescherming Beschoeiing
Kanalen ...
Vaarweg Oevervak Orientatie hm_start hm_eind Inspectiedatm Kwaliteit_CROW288 Type_oever Functie_oeverbescherming Lengte
K2...
Pilot project to evaluate (spatial)BI
Tools for Asset Management
• Pentaho BI Server
• Mondrian
• GeoMondrian
• Saiku
• Ge...
Pro’s and Con’s
Geomondrian
Super powerful
Lacking in usability
Performance seems to be a
problem with large datasets
No ‘...
Conclusions
• Our relational model has strong
attribute relations describing the
spatial relations
• A user friendly UI is...
Further plans
• Re-engineer datamarts for
maximum flexibility
• Evaluate map UI’s like geojsp
Using Spatial Business Intelligence For Asset ManagementSpatial bi foss4g2013
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Using Spatial Business Intelligence For Asset ManagementSpatial bi foss4g2013

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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.

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Using Spatial Business Intelligence For Asset ManagementSpatial bi foss4g2013

  1. 1. Using Spatial Business Intelligence For Asset Management Niels Hoffmann 20 Sep 2013
  2. 2. 2.5 million people 2670 km2 55 municipalities Planning and/or Funding: • Welfare • Environment, nature and landscape • Public transport • Culture • Infrastructure network http://maps.noord-holland.nl/Dataportaal http://maps.noord-holland.nl/structuurvisie2040/ Province of Noord-Holland
  3. 3. 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
  4. 4. ACTACT PLANPLAN DODO CHECKCHECK Asset Management Optimize Life cycle of assets Minimize 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
  5. 5. IMGeo Datamodel NEN 2767-4 Decomposition Relational Datamodel
  6. 6. Business Intelligence BI is ‘event’ driven Sales: • What • When • Where • Who Asset Management is about ‘events’ as well: • Construction • Inspection • Maintenance
  7. 7. BI Tools should be a good fit for Asset Management. What about Spatial BI?
  8. 8. Data Architecture BGT / IMGeo Asset DB DWH Asset DB Kruispuntnr Kilometrage Roestvorming Scheefstand Natuurlijke aanslag Graffiti enz Materiaal bord Folieklasse 244085 40,5 A+ A+ A A+ metaal III Datamart Datamart
  9. 9. Waterways have a lot of constructions: Not all of it good quality…
  10. 10. NEN 2767-4 Beheerobject Element Bouwdeel Kanalen Kerende constructie Damwand Kanalen Oeverbescherming Beschoeiing Kanalen Oeverbescherming Elementverharding Relational Quality information
  11. 11. Vaarweg Oevervak Orientatie hm_start hm_eind Inspectiedatm Kwaliteit_CROW288 Type_oever Functie_oeverbescherming Lengte K20 080 Rechter oever 32,4 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
  12. 12. Pilot project to evaluate (spatial)BI Tools for Asset Management • Pentaho BI Server • Mondrian • GeoMondrian • Saiku • GeoKettle
  13. 13. Pro’s and Con’s Geomondrian Super 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
  14. 14. 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
  15. 15. Further plans • Re-engineer datamarts for maximum flexibility • Evaluate map UI’s like geojsp

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