Faculty of Civil Engineering Institute of Construction Informatics, Prof. Dr.-Ing. Scherer Institute of Construction Informatics, Prof. Dr.-Ing. Scherer Technische Universität Dresden MIS 1 Management Information Systems Part 2: Data Model Prof. Dr.-Ing. Raimar J. Scherer Institute of Construction Informatics Dresden,

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 2 Overall Process of an Engineering System Treatment 1.System Capturing High level definition of the purpose, functions, processes and behaviour Formal Representation of the System (IDEF0) 2.data structure = {O,R} based on a specific meta model (= O-O-Model) development of a data model as an O-O-schema = ideal data structure of the concepts 3.transformation of the conceptual data model in an operational database; today being most appropriate as a relational data structure (approximations) 4.implementation of the schema in a data base software; 5.instantiation of an engineering model = configure the domain-specific engineering model from the data model 6.numerical program for the computation of the system behaviour = simulation = prognosis based on a model + model assumptions + quantitative values (statistics) (= {O-O + Impl.} + {Instantiation} ) 7.Communication M2M: between data base (= information) and computation program (= numerics) = data exchange (data conversion by importing program) M2H: Reports, i.e. graphical and alphanumerical representation of results (output and system changes) but also input, model and model assumptions 8.Monitoring + Evaluation + Reporting

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 3 Formalization How to solve problems with help of computer software? Which knowledge and information have to be modelled? (domain) model software application data structure (organization and management of all needed data, e.g. definition of a circle with centre point and radius) behavior (processing of stored data, e.g. calculation of circle area A = pi * radius²) process describe the activities and the resources for the activities for example with event driven process chains (ARIS, SAP) e.g. 1) input of parameters, 2) calculate area, 3) output of result graphical user interfaces (GUI) (visualization of model data, output of results, e.g. centre point (x,y) radius r

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 4 Formalization How to represent models, i.e. the knowledge and information needed to solve problems? “An abstract model (or conceptual model) is a theoretical construct that represents physical, biological or social processes, with a set of variables and a set of logical and quantitative relationships between them. Models in this sense are constructed to enable reasoning within an idealized logical framework about these processes and are an important component of scientific theories. …” ( Modelling techniques to represent functional and data structure oriented knowledge and information Entity-Relationship Model Object-Oriented Model IDEF0

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 5 Formalization Scope of modelling techniques? Entity Relationship Model - focus on data management (e.g. conceptional modelling for relational databases) - no behaviour, almost no information about consistency - strategy for modelling: avoid redundant data - aim: persistant storage of data (data source for applications) Object-Oriented Modelling - advanced programming concept for development of software applications (e.g. JAVA, C++, …) - allows definition of behaviour (reactive dependencies between data) - strategy for modelling: reusability and maintenance - aim: use of data (e.g. simulation of structural behaviour) Logic - knowledge representation for artificial intelligence and reasoning - aim: “interpretation” of data, e.g. consistency checks, planning, ect (dealing with information instead of data)

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 6 Object-Oriented Data Modelling Basic concepts for definition of data structures - objects - relationships - attributes Adapt concepts of the object oriented paradigm for data modelling Advanced concepts - classification - inheritance (reuse and redefinition of attributes) - select types - enumerations - aggregations (array, bag, list, set) supported by the Extended Entity-Relationship model (e.g. the EXPRESS language) similar to the Entity-Relationship model

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 7 Object-Oriented Data Modelling Constraints - inverse relationships - optional or mandatory attributes - cardinalities for aggregations - rules (e.g. range of values, …) - derived attributes (functional dependencies) Provided functionality differs between object-oriented modelling languages, e.g. UML, EXPRESS, as well as for programming languages C++, Java etc. functionality for data validation (consistency checks)

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 8 Object-Oriented Data Modelling Conceptual data modelling for the water-supply system Basis for layout of the data model: FUNCTION Input ? Output ? requirement analysis of the water-supply system (see first lesson: system modelling = 1view =>activity modell / process modell) -> provide answer to the question: Which kind of data/information need to be stored?

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 9 water-supply system (distribute water) Modelling Requirement: describe all information of a water-supply system needed for - dimensioning, - monitoring and - life-cycle management a possible water-supply system on a very abstract level water input water output

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 10 Modelling Requirement: describe all information of a water-supply system needed for - dimensioning, - monitoring and - life-cycle management possible water-supply system on the level of nodes: Objects are node, pipe node A water-supply system can be separated as a set of sub systems connected by pipes nodes connect pipes and allow water input/output

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 11 Modelling Requirement: describe all information of a water-supply system needed for - dimensioning, - monitoring and - life-cycle management possible water-supply system with water flow for a specific use case Q i-n1 Q d1, v d1, p d1 Q d2, v d2, p d2 Q d3, v d3, p d3 Q d4, v d4, p d4 Q d5, v d5, p d5 Q o-n4 Q o-n6 „geometry“ of pipe system is needed for pipe lengths l d1 input output

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 12 Concepts Modelling First sketch for modelling: describe the topology of the water-supply system NodePipe start, end concept relationship node pipe Topological Model Using instantiations of this concepts (O-O Model) we can build a water suply system

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 13 Modelling First sketch for modelling: describe the topology of the water-supply system nr NodePipe start, end concept relationship integer nr attributes integer nr startend Example: node 1 node 2 pipe 1 Topological Model: identification of elements needed to describe topology table Nodetable Pipe

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 14 Modelling First sketch for modelling: add geometry nrxyz NodePipe start, end concept relationship integerreal nrx, y, z attributes integer nr startend Example: x y 1 2 Topology + geometry : table Nodetable Pipe We are storing the length !!

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 15 Modelling with EXPRESS-G Modelling with EXPRESS-G (graphical notation of the EXPRESS language ISO ) NodePipe nr REAL INTEGER REAL x y z start_node end_node nr INTEGER

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 16 nr Modelling with EXPRESS-G (ISO ) Pipe INTEGER start_node end_node nr INTEGER Node REAL x y z node location requirements: 3D, use of Cartesian coordinate system measurement of x, y and z: variable are fixed to meter -> use of fixed measurement [m] origin of used coordinate system?: describing the real coordinates in the world (GIS) or use your own, but clearly express this (enough for dimensioning) Modelling with EXPRESS-G

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 17 start_node end_node Node REAL x y z Modelling with EXPRESS-G (ISO 10303) Pipe identification of nodes and pipes requirements: unique identification needed (for replacement of defect pipes etc.) possible solution:give human readable name (string) or give number for identification (integer) – some advantages for data management: less memory, indexing nr INTEGER nr INTEGER Modelling with EXPRESS-G

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 18 nr INTEGER nr INTEGER REAL x y z Modelling with EXPRESS-G (ISO 10303) geometry of pipes requirements: needed for flow resistant and length agreement:only support pipes with straight line -> start node and end node enough to describe geometry of a pipe start_node end_node NodePipe not possible for curved pipes We would have to extend pipe by an object(s) containing geo model Modelling with EXPRESS-G

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 19 Modelling with EXPRESS-G (ISO 10303) additional pipe parameter requirements: use individual pipe types parameter:individual pipe types -> diameter, k (roughness) pn (nominal pressure) Modelling with EXPRESS-G standard pipe types -> name (use additional library to get needed parameter or use optional relationship to pipe_Parameter) as well as standard pipe types(=outsourced) Pipe REAL diameter nr INTEGER pipe_type_select pipe_parameter pipe_Parameter REAL k pn pipe_Type name STRING (OPT) parameter standard pipe types -> name (use additional library to get needed parameter or use optional relationship to pipe_Parameter) as well as standard pipe types

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 20 Modelling with EXPRESS-G (ISO 10303) specialization of Nodes requirements: differ between input, output and inner nodes by using the concept of inheritance specialization defines a disjunct set of objects -> Node is an abstract superclass for Input_Node, Output_Node and Inner_Node (ABS) Node Input_Node Modelling with EXPRESS-G Output_NodeInner_Node 1

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 21 pressure Modelling with EXPRESS-G (ISO 10303) water source for the water-supply system requirements: human readable name of water source, inherits definition from Node (location, nr) max. water input in liter per second water pressure in level of water column (ABS) Node Input_Node REAL STRING REAL water_input name Modelling with EXPRESS-G

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 22 Modelling with EXPRESS-G (ISO 10303) water consumption for the water-supply system requirements: human readable name of water source, inherits definition from Node (location, nr) average water consumption (ABS) Node Output_Node REAL STRING consumption name Modelling with EXPRESS-G REAL required pressure

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 23 Modelling with EXPRESS-G (ISO 10303) water consumption for the water-supply system requirements: inherits definition from Node (location, nr) -> no additional attributes (ABS) Node Inner_Node Modelling with EXPRESS-G

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 24 Extensions for Monitoring Required extension for dimensioning and life-cycle management 1. dimensioning for different water consumptions (e.g. in case of fire) -> dimensioning for different load cases 2. documentation of water flow over time (aging of the pipe system) -> change of pipe parameters/flow rates (speed) 3. monitoring of water flow -> adding of a water flow sensor element

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 25 Extensions for Monitoring Extension of the pipe system: definition of node sensors requirements: water pressure and time of measurement location of the node sensor identification of the measurement with unique number Node Node_Sensor REAL location nr INTEGER REAL pressure time

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 26 Extensions for Monitoring Extension of the pipe system: definition of pipe sensors requirements: water velocity and time of measurement location of the pipe sensor identification of the measurement with unique number Pipe Pipe_Sensor REAL Pipe nr INTEGER REAL velocity time

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 27 Extensions for Monitoring Extension of the system: definition of fluids requirements: name, viscosity, density STRING Fluid REAL name REAL viscosity density

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 28 Water-Supply System as complete model

Institute of Construction Informatics, Prof. Dr.-Ing. Scherer MIS Technische Universität Dresden 29 Extensions for Monitoring Extension of the pipe system: definition of time series (records) requirements: water velocity and time of measurement location of the record identification of the measurement with unique number Time_Series REAL nr INTEGER REAL velocity time Pipe Pipe_Sensor Pipe Pipe_Sensor_ID