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