General Indicator Modeling for Decision Support based on 3D city and - PowerPoint PPT Presentation

Lehrstuhl für Geoinformatik Technische Universität München General Indicator Modeling for Decision Support based on 3D city and landscape models using Model Driven Engineering Mostafa Elfouly, Thomas H. Kolbe Chair of Geoinformatics Technische Universität München mostafa.elfouly@tum.de 6th of June 2015 Source: shuttersock.com

Technische Universität München Lehrstuhl für Geoinformatik Measuring Landscape / City Performance Energy Ecological Indicators Indicators Landscape / City (and its parts) Source: shuttersock.com Mobility Indicators Financial Social Indicators Indicators ► Evaluation is typically based on indicators, the most relevant are called Key Performance Indicators (KPIs) General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 2

Technische Universität München Lehrstuhl für Geoinformatik Indicators Geobase data CityGML Data Energy Indicators ALKIS Data Mobility Indicators ATKIS Data Ecological Indicators INSPIRE Data Social Indicators BIM Data Financial Indicators General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 3

Technische Universität München Lehrstuhl für Geoinformatik Observations 1. Geobase data are available for entire countries and can be used for computing indicator values ● (however, typically additional domain specific data are required) 2. All these geospatial information are based on standardised semantic data models / ontologies 3. So far, indicators are typically not formally modelled using a standardised framework 4. Furthermore, no systematic model exists yet for linking indicators and geobase data General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 4

Technische Universität München Lehrstuhl für Geoinformatik Model Driven Engineering (MDE) ► … is a software engineering paradigm which began to evolve in the 1980s ► MDE puts the “model” in the form of formal specifications in the centre of software analysis and design ● Application relevant structures are represented by formal data models (e.g. using Unified Modeling Language, UML ) ● Program code is automatically derived from models ► MDE also addresses the linking of different models ● This is called Model Weaving ● Different models are linked by a weaving model which takes care of data transformation across the models General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 5

Technische Universität München Lehrstuhl für Geoinformatik Geospatial Information Modelling This is the general schema which General Feature all geospatial data models follow Model (e.g. ALKIS, INSPIRE, CityGML) ISO 19109 M2: Metamodel This is the data model of the 3D city model (here: CityGML) CityGML It defines the structures of all Application Schema possible 3D city models M1: Model X Y Z 3D city model data, e.g. the objects of the 3D city model of Berlin M0: Instance General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 6

Technische Universität München Lehrstuhl für Geoinformatik Indicator Modelling Domain specific General Feature General Model Indicator indicators follow a ISO 19109 Model General Ind. Model M2: Metamodel These are the Energy Related indicator models KPIs Application Schema CityGML from different Application application Schema domains Climate Related KPIs Application Schema M1: Model Concrete indicators X Y Z KPI B Building Z for concrete city / landscape objects KPI A Building Y M0: Instance General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 7

Technische Universität München Lehrstuhl für Geoinformatik Requirements for Indicator Models ► Different types of indicators need to be distinguished (i.e. numerical, textual, categorical indicators) ► Complex indicators can be composed & computed from ● attribute values from associated city / landscape model objects ● constants ● mathematical expressions (unary / binary arithmetic operations) on other indicators ► Indicator value aggregation (e.g. summation, average, maximum, etc.) of other indicators ► Augment indicator values with meta information like accuracy, lineage / source etc. ● allowing for automatic sensitivity analysis General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 8

Technische Universität München Lehrstuhl für Geoinformatik General Indicator Model (GIM) in UML Indicator + name :CharacterString + value :IndicatorValueType TextIndicator ClassifierIndicator operand2 NumericIndicator operand1 + accuracy :Real [0..1] 1..* operand + unit :UnitOfMeasure operand + value :Real ArithmeticOperation NumericConstant NumericAttribute + source :CharacterString + referenceToObjectAttribute :URI + source :CharacterString UnaryArithmeticOperation BinaryArithmeticOperation NumericAggregationOperation + operation :UnaryOperation + operation :BinaryOperation + operation :AggregationOperation «enumeration» «enumeration» «enumeration» General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 9

Technische Universität München Lehrstuhl für Geoinformatik Domain Specific Indicator Modelling Domain General Indicator Indicators Model Numeric HeatDemand Indicator + value Domain of the stakeholder/application specialist Where do I get the data from? Energy Planner General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 10

Technische Universität München Lehrstuhl für Geoinformatik Domain Specific Indicator Modelling Reference Object Related Domain General Indicator Objects Domain Indicators Indicators Model DistrictHeat District EnergyDemand Numeric HeatDemand «Aggregation» Indicator num + value * * BuildingHeat Building EnergyDemand -volume + compute() OCL Rule 2 Many of the reference objects in the context of urban or landscape Domain of the stakeholder/application specialist indicators are spatial Where do I get objects the data from? Energy Planner General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 11

Technische Universität München Lehrstuhl für Geoinformatik Linking Geospatial and Indicator Models Geospatial Application Model Weaving Reference Object Related Domain General Indicator (e.g. CityGML) Model Objects Domain Indicators Indicators Model District DistrictHeat * District CityObject Connector EnergyDemand Numeric HeatDemand «Aggregation» Indicator num CityObject Building + value * Group * BuildingHeat geometry Building Building EnergyDemand Connector Solid -volume + compute() OCL Rule 1 OCL Rule 2 Domain of the geodata provider Domain of the stakeholder/application specialist What can Where do I get we do with the data from? our data? City Modeler Energy Planner General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 12

Technische Universität München Lehrstuhl für Geoinformatik Rules in Object Constraint Language (OCL) - 1 Reference Object Related Domain General Indicator Objects Domain Indicators Indicators Model refDistrict DistrictHeat District EnergyDemand Numeric HeatDemand Indicator + value * * BuildingHeat refBuildingHeat refBuilding Building EnergyDemand + volume + compute() Type ageClass context context DistrictHeatEnergyDemand inv: BuildingHeatEnergyDemand inv: self.value = refBuilding.volume * self.value = 0.97 Sum(refDistrict.refBuilding.refBuil dingHeatEnergyDemand.value) General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 13

Technische Universität München Lehrstuhl für Geoinformatik Rules in Object Constraint Language (OCL) - 2 Object Related Weaving Reference Geospatial Application Model Domain Indicators Classes Objects DistrictHeat * CityObject District District EnergyDemand Connector * Building CityObject * BuildingHeat Group Building refBuilding Building EnergyDemand refCityGMLBuilding Connector + volume + compute() Solid context BuildingConnector inv: refBuilding.volume = refCityGMLBuilding.volume General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 14

Technische Universität München Lehrstuhl für Geoinformatik Conclusions ► General Indicator Model: new framework for model based representation and automated computation of indicators ● Indicators for different domains are specified in a standardised and interoperable way using UML class diagrams and OCL rules ● Indicator models are linked to geobase data models using model weaving ► The framework facilitates ● systematic analysis of (also very complex) indicators and their relationships to digital landscape and city models ● representing and explaining key performance indicators for evaluation of landscape (aspects) represented by 3D models ● automatic derivation of programs to compute indicator values General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 15

Technische Universität München Lehrstuhl für Geoinformatik General Indicator Modeling for Decision Support based on 3D City & Landscape Models 06.06.2015 16