CONCERTO PremiumTechnical Monitoring Database &
Semantic Layer
Milan Marinov, KIT
Prof. Andreas Wagner
23.10.2012, Brussels
Objectives
• Show how the data of CONCERTO projects is managed in the database
• Introduce the Technical Monitoring Database and Semantic Layer components
• Give a basis for a discussion• Collect feedback
General data from CONCERTO project sites
EnergyData
EconomicData
TechnologicalData
Data about Political
Instruments
SocialData
country data
Indicators AAAA AA AAWebsite
Visualization Environment
CONCERTO projects
Intelligent queries
TMD
Semantic Layer
CONCERTO Premium – Information flow
Premium TMD: Flexible Data Management
Semantic layer: Flexible Indicator Calculation
Software Components Overview
TMDConcerto Data
Semantic Layer
CONCERTO Knowledge Base
Defaultfacts & rules
Customized facts & rules
Data Monitor
Visualization
Reasoner
Interactive sandbox
TMD key data
• 159.018 data nodes• 169.695 relationships
Building, Ref. Building, Area Relationships
Data Sheets and the TMD
• Integrity of relations depends on the quality of IDs and references in data sheets
More about data collection and data quality will be discussed in the workshop „Status quo of
buildings, data and indicators first results“
Software Components Overview
TMDConcerto Data
Semantic Layer
CONCERTO Knowledge Base
Defaultfacts & rules
Customized facts & rules
Data Monitor
Visualization
Reasoner
Interactive sandbox
Concerto Premium SL Functionalities
• Defines the meaning of data fields, e.g. how do different types of floor areas relate to building capacity.
• Defines the contexts in which indicator variables are calculated.
• Defines the indicator calculation formulas
• Performs indicator calculations
• Enables definition and management of customized calculation formulas
SL Example: Data Collection / Data Import
Building 1120
kWh/(m²a)10 kWh/(m²a) 100 m² 4
Building 2 … … … …
Building 3 … … … …
Building 1 … … …
Building 2 150 kWh/(m²a)
110 m² 2
City 1
City 2
CONCERTO PremiumTechnical Monitoring Database
…………Building 2
4100 m²10 kWh/(m²a)120 kWh/(m²a)Building 1
…………Building 3
…...Building 1
2110 m²150 kWh/(m²a)Building 2
...
SL Example: Approximation Rules
Customized Facts & Rules, City 1
Customized Facts & Rules, City 2
Default Facts & Rules
A: Energy consumption for space heating and domestic hot water = Energy consumption for space heating + Energy consumption for domestic hot water
B1: Approximated energy consumption for hot water = floor area * energy consumption for hot water/ floor area of a comparable building
B2: Approximated energy consumption for hot water = #Occupants * energy consumption for hot water/ occupant of a building
C: Buildings are comparable if the difference of the building floor areas is less than 20%
Rules and data interpretation
Rule configuration Building 1 Building 2
Without rules 120 ?
Rule A 120 SH < 150 & DHW < 150
Rules A & B1 120 SH<150 & SH==139
Rules A & B2 120 SH<150 & SH==145
Rules A & B1 & C 120 SH<150 & SH==139
Rules A & B1 & B2 & C 120 SH<150 & 139<SH<145
More about indicators and first results will be discussed in the workshop „Status quo of buildings, data and indicators first results“
Software Components Overview
TMDConcerto Data
Semantic Layer
CONCERTO Knowledge Base
Defaultfacts & rules
Customized facts & rules
Data Monitor
Visualization
Reasoner
Interactive sandbox
Data Import using the Data & Rules Monitor
Software Components Overview
TMDConcerto Data
Semantic Layer
CONCERTO Knowledge Base
Defaultfacts & rules
Customized facts & rules
Data Monitor
Visualization
Reasoner
Interactive sandbox
Customized rules in the interactive sandbox
B2: Approximated energy consumption for hot water = #Occupants * energy consumption for hot water/ occupant of a building
Simplified rule specification in the IS
More about visualization, indicator calculaton and queries to come in the following
presentation
Questions?
Thank you for your attention
Interactive Database Queries
• Can be performed from the web based visualization or from the console
• Can have different levels of complexity• Increasing levels of complexity being
implemented incrementally in the web-based visualization