Buildings and Semantics

Data Models and Web Technologies for the Built Environment

Pieter Pauwels, Kris McGlinn, Pieter Pauwels, Kris McGlinn

• Publisher: CRC Press
• Year: 2022
• Print ISBN: 9781032023120
• eBook ISBN: 9781000613230
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Information Technology
• Index: Technology & Engineering

The built environment has been digitizing rapidly and is now transforming into a physical world that is at all times supplemented by a fully web-supported and interconnected digital version, often referred to as Digital Twin. This book shows how diverse data models and web technologies can be created and used for the built environment. Key features of this book are its technical nature and technical detail. The first part of the book highlights a large diversity of IT techniques and their use in the AEC domain, from JSON to XML to EXPRESS to RDF/OWL, for modelling geometry, products, properties, sensor and energy data. The second part of the book focuses on diverse software solutions and approaches, including digital twins, federated data storage on the web, IoT, cloud computing, and smart cities. Key research and strategic development opportunities are comprehensivelydiscussed for distributed web-based building data management, IoT integration and cloud computing.This book aims to serve as a guide and reference for experts and professionals in AEC computing and digital construction including Master's students, PhD researchers, and junior to senior IT-oriented AEC professionals.

Part I Semantics and data

Chapter 1 Building product models, terminologies, and object type libraries

Aaron Costin, Jeffrey W. Ouellette, and Jakob Beetz

DOI: 10.1201/9781003204381-2

CONTENTS

1. 1.1 Introduction
   1. 1.1.1 A brief history of CAD/BIM
   2. 1.1.2 Tackling CAD/BIM data exchange
   3. 1.1.3 Seamless data exchange: the endemic problem
2. 1.2 Concepts and definitions
   1. 1.2.1 Chapter definitions
3. 1.3 Structured vocabularies
   1. 1.3.1 Structured vocabulary types
      1. 1.3.1.1 Classification systems
      2. 1.3.1.2 Taxonomy
      3. 1.3.1.3 Ontology
      4. 1.3.1.4 Data dictionary
      5. 1.3.1.5 Object-type library
   2. 1.3.2 Functionality and features
      1. 1.3.2.1 Object-oriented functionality
      2. 1.3.2.2 Semantics and logic
4. 1.4 Digital building exchange formats and schemas
   1. 1.4.1 Semantic web and linked data
      1. 1.4.1.1 Resource description framework (RDF)
      2. 1.4.1.2 Web ontology language (OWL)
      3. 1.4.1.3 Simple knowledge organisation system (SKOS)
   2. 1.4.2 ISOs for building classifications
5. 1.5 Methods and techniques
   1. 1.5.1 Product and solid modelling techniques
   2. 1.5.2 Information collection mechanisms
   3. 1.5.3 Development and management
6. 1.6 Practical examples in the AECO industry
   1. 1.6.1 Core vocabularies and linked datasets
   2. 1.6.2 Existing AECO ontologies
   3. 1.6.3 Existing OTLs and data dictionaries
7. 1.7 Open research challenges
   1. 1.7.1 System limitations
   2. 1.7.2 Open standard limitations
8. 1.8 Conclusion
9. Notes

The built environment consists of a wide variety of digital representations of physical products and building elements. These product models have enabled new and efficient digitised methods for the architecture, engineering, construction, and operations (AECO) industry to design, construct, and operate a facility. As a result, product modelling is a key competence for anyone operating with assets in the built environment. In this first chapter of the book, we provide an overview of the way in which product modelling is performed in the AECO industry. Importantly, we hereby distinguish between product modelling in the AECO industry for (1) the design and construction of buildings, which typically needs to support continuous updates between a wide variety of stakeholders; and (2) the operational phase of buildings, in which product data is needed for operations and maintenance (O&M) over long spans of time (facility and asset management). We present the current concepts, methods, and tools required to understand the rest of the chapters of this book.

1.1 Introduction

The architecture, engineering, construction, and operations (AECO) industry has seen great advancements in technology, both in hardware and software, used in various tasks required during the life cycle of a project, from design to delivery and through its operational life span. Artificial intelligence (AI) and machine learning (ML), virtual and augmented realities (VR & AR), and computational design methodologies are striving to make the delivery faster and safer, as well as more economically and environmentally sustainable. Primary methods and technologies include Computer-Aided Design (CAD) or Computer-Aided Design and Drafting (CADD) and Building Information Modelling (BIM), which enable a wide variety of digital representations of physical products and building elements, sometimes referred to as building product models. A building product model is a digital information structure of objects making up a building, capturing the form, behavior and relations of the parts and assemblies within the building [115].

As one of the pioneers in BIM, Charles “Chuck” Eastman envisioned computers being able to capture more than just the details of typical 2D design drawings but also 3D geometry and spatial information analogous to a real, physical construct, being further manipulated to allow a wide range of views. These views would enable a multitude of digitally-based workflows for design, construction, and operational analysis. This early vision has come into reality, and we are currently witnessing further digital advancements with integrating real-time sensors into buildings and connecting them to BIM-based views, effectively creating a dynamic virtual representation of the physical elements of a building, also known as a Digital Twin (DT).

It is important to note that processes and requirements in the design and construction phases of the building life cycle are different from those in the operations phase. Thus, we hereby distinguish between product modelling in the AECO industry for (1) the design and construction of buildings (AEC), which typically needs to support continuous updates between a wide variety of stakeholders; and (2) the operational phase (O) of buildings, in which product data is needed for maintenance operations over long span of time (facility and asset management). This chapter provides an overview of the concepts, methods, and tools needed to create and utilise building product models for the design and construction of a building. The information is presented through the perspective of product modelling, which includes structured vocabularies, object-type libraries (OTLs), and data exchange.

1.1.1 A brief history of CAD/BIM

The idea of using computers to digitise the design and manufacturing of products began in the 1950s during the early days of computing. In 1957, Pronto was the first commercial computer-aided manufacturing (CAM) software, developed only a few years after the first automated robots were used in assembly lines. Soon, this use was extended to computer-aided design (CAD), a term coined by Douglas T. Ross around 1959 at Massachusetts Institute of Technology (MIT), as part of the earliest stages of what ultimately became the MIT Computer-Aided Design Project [80]. This concept for object-based design and parametric manipulation was published in Douglas C. Englebart’s 1962 paper Augmenting Human Intellect [120]. Cognitive design was also a popular topic of research for architecture, thus the combination of the two seemed destined. In 1963, Ivan Sutherland’s SketchPad (a.k.a. Robot Draftsman) was a breakthrough CAD program to show the benefits of using computer graphics for designing.

From his 1975 article, The Use of Computers Instead of Drawings in Building Design, Eastman writes:

A building can be conceived, though, as a collection of three-dimensional elements arranged in space... A detailed building representation might be provided by a computer, if it could s...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Figures
• Tables
• About the authors
• Contributors
• Foreword
• Preface
• Acronyms
• Part I Semantics and data
• Part II Algorithms and applications
• Bibliography
• Index