Рисунок 14
032 CAD data from design to data storage
10 June 2025
image113
034 Filling systems with data in the construction industry
10 June 2025

033 The emergence of the BIM (BOM) concept and the use of CAD in processes

The concept of Building Information Modeling (BIM), first outlined in the 2002 BIM Whitepaper (“Building Information Modeling Whitepaper site,” 2003), originated from the marketing initiatives of CAD software manufacturers. It emerged from the marketing initiatives of CAD software developers and was an attempt to adapt the principles already well established in mechanical engineering to the needs of the construction industry.

The inspiration for BIM came from the concept of BOM (Bill of Materials), a product composition specification that has been used extensively in industry since the late 1980s. In mechanical engineering, BOM allowed linking data from CAD systems with PDM (Product Data Management), PLM (Product Lifecycle Management) and ERP systems, providing holistic management of engineering information throughout the entire product lifecycle (Fig. 3.1-8).

Рисунок 4
Fig. 3.1-18 Evolution of specifications (BOM), information modeling (BIM), and digital formats in the engineering construction industry.

The modern development of the BOM concept has led to the emergence of an extended framework – XBOM (Extended BOM), which includes not only product composition, but also behavioral scenarios, operational requirements, sustainability parameters and data for predictive analytics. XBOM essentially fulfills the same role as BIM in construction: both approaches strive to turn the digital model into a Single Source of Truth for all project participants throughout the entire lifecycle of an object.

A key milestone in the emergence of BOM in construction was the introduction of the first parametric CAD (MCAD) specifically adapted for the construction industry in 2002. It was developed by the team that had previously created Pro-E®, a revolutionary MCAD system for mechanical engineering that appeared in the late 1980s and became an industry standard (А. Boiko, “Lobbying wars and BIM development. Part 5: BlackRock is the master of all technologies. How corporations control open source code,” 2024).

Already in the late 1980s, the goal was to eliminate the limitations (D. Ushakov, “Direct Modeling – Who and Why Needs It? A Review of Competitive Technologies,” 14 11 2011) of the then existing CAD -programs. The main objective was to reduce the labor required to make changes to the parameters of design elements and to make it possible to update the model based on data outside CAD programs via a database (C. Eastman and A. Cthers, “Eastman, Charles; And Cthers,” September 1974).The most important role in this was to be played by parametrization: automatic retrieval of characteristics from the database and using them to update the model inside CAD-systems.

Pro-E and the concept of elemental parametric modeling c BOM underlying it have had a significant impact on the development of the CAD – and MCAD– market (D. Ushakov, “Direct Modeling – Who and Why Needs It? A Review of Competitive Technologies,” November 11, 2011). For 25 years this model has been in the industry and many modern systems have become its conceptual successors.

.

The goal is to create a system that is flexible enough to encourage the engineer to easily consider different designs. And the cost of making changes to the design should be as close to zero as possible. Traditional CAD / CAMsoftware unrealistically restricts making inexpensive changes only at the very beginning of the design process (D. Weisberg, “History of CAD,” 12 Dec. 2022).

– Samuel Geisberg, founder of Parametric Technology Corporation®, developer of MCAD -product Pro-E and teacher of the creator of a CAD product using the RVT format

In mechanical engineering, PDM, PLM, MRP and ERP systems have become key platforms. They play a central role in data and process management, gathering information from CAx systems (CAD, CAM, CAE) and organizing design activities based on the product structure (BOM: eBOM, pBOM, mBOM) (Fig. 3.1-18). This integration reduces errors, avoids data duplication and ensures end-to-end traceability from design to production.

image22
Fig. 3.1-19 Historically, BOM emerged in the 1960s as a way to structure data from CAx systems and pass it to control systems.

The purchase by one of the leading vendors of a CAD solution developed by the former Pro-E team and based on the BOM approach was marked by the almost immediate publication of the BIM Whitepaper series (2002-2003) (https://web.archive.org/web/20060512180953/http:/images.adsk.com/apac_sapac_main/files/4525081_BIM_WP_Rev5.pdf#expand. [Date of address: 15 March 2025])(ADSK, “White Paper Building Information Modeling in Practice,”). As early as the mid-2000s, the BIM concept began to be actively promoted in the construction industry, which markedly increased interest in parametric software. The popularity grew so rapidly that the construction fork of mechanical engineering Pro-E – parametric CAD promoted by this vendor – has actually displaced competitors in the architectural and structural design segment(Fig. 3.1-20). By the early 2020s, it has de facto consolidated global dominance in the BIM (CAD) market (А. Boiko, “Lobbying wars and BIM development. Part 2: open BIM VS closed BIM. Europe VS the rest of the world,” 2024).

image21
Fig. 3.1-20 Google search query popularity (RVT versus IFC): parametric CAD created by the former Pro-E team with BOM support -BIM has gained popularity in almost most countries of the world.

Over the past 20 years, the abbreviation BIM has acquired a multitude of interpretations, the polysemy of which has its roots in the initial marketing concepts that emerged in the early 2000s. The ISO 19650 standard, which played an important role in popularizing the term, actually secured the status of BIM as a “scientifically based” approach to information management. However, in the text of the standard itself, which is dedicated to data management throughout the life cycle of objects using BIM, the abbreviation BIM is mentioned, but never clearly defined

The vendor’s original website, which published a series of Whitepaper on BIMin 2002  (ADSK, “White Paper Building Information Modeling,” 2002. https://web.archive.org/web/20060512180953/http:/images.adsk.com/apac_sapac_main/files/4525081_BIM_WP_Rev5.pdf#expand. [Date of address: 15 March 2025]) and 2003 (ADSK, “White Paper Building Information Modeling in Practice,”), actually reproduced marketing materials on the BOM (Bills of Materials) and PLM (Product Lifecycle Management) concepts previously used in Pro-E mechanical engineering software back in the 1990s (А. Boiko, “Lobbykriege um Daten im Bauwesen | Techno-Feudalismus und die Geschichte von BIMs,” 2024).

Building Information Modeling, an innovative new approach to building design, construction, and management introduced by…… [CAD vendor company name] in 2002, has changed the way industry professionals around the world think about how technology can be applied to the design, construction, and management of buildings.

– BIM Whitepaper,2003 (ADSK, “White Paper Building Information Modeling in Practice,”)

These early publications linked BIM directly to the concept of a centralized integrated database. As stated in the 2003 Whitepaper, BIM is building information management where all updates occur in a single repository, keeping all drawings, cuts and specifications (BOM – Bills of Materials) synchronized.

BIM is described as building information management, where all updates and all changes take place in a database. So whether you are dealing with schematics, sections or sheet drawings, everything is always coordinated, consistent and up to date.

– CAD company websitevendor with BIM Whitepaper, 2003 (“Building Information Modeling Whitepaper site,” 2003)

The idea of managing design through a single integrated database has been widely discussed as early as in the studies of the 1980s. For example, Charles Eastman’s BDS concept (C. Eastman and A. Cthers, “Eastman, Charles; And Cthers,” September 1974)included 43 references to the term “database” (Fig. 6.1-2). By 2004, this number had almost halved to 23 in the 2002 Whitepaper on BIM (ADSK, “Whitepaper BIM,” 2002. [On the Internet]. Available: https://web.archive.org/web/20060512180953/http:/images.autodesk.com/apac_sapac_main/files/4525081_BIM_WP_Rev5.pdf#expand. [Date of address: 15 March 2025]). And by the mid-2000s, the topic of databases had virtually disappeared from vendors’ marketing materials and the digitalization agenda in general.

Although it was the database and access to it that was originally conceived as the core of the BIM -system, over time the emphasis shifted to geometry, visualization and 3D. The very registrar of the IFC standard in 1994, who published the BIM Whitepaper in 2002 – the same vendor – in the Whitepaper of the early 2000s explicitly pointed out the limitations of neutral formats such as IGES, STEP and IFC and the need for direct access to CAD databases:

Different applications may be incompatible and re-entered data may be inaccurate […]. The result of traditional computer-aided design [CAD]: higher costs, longer time-to-market, and lower product quality. Today, all major applications use industry standard interfaces for low-level data exchange. By using the old IGES standards or the new STEP [IFC is a de facto and de jure copy of the STEP/IGES format] to exchange data between applications from different vendors, users can achieve some data compatibility between best-of-breed products. But IGES and STEP only work at low levels, and they cannot exchange data as rich as the information generated by today’s leading applications […]. And while these and other standards are improving almost daily, they will always lag behind today’s vendor products in terms of data richness. […] programs within an application must be able to share and preserve data richness without resorting to neutral translators such as IGES, STEP [IFC] or PATRAN. Instead, framework applications should be able to directly access the underlying CAD database so that the detail and accuracy of the information is not lost.

– CAD vendor Whitepaper (IFC, BIM) “Integrated Design and Manufacturing: Benefits and Rationale,” 2000 (ADSK, “Integrated Design-Through-Manufacturing: Benefits and Rationale,”)

Thus, already in the 1980s and early 2000s, the key element of digital design in the CAD environment was considered to be the database rather than the format-file or the neutral IFC format. It was suggested that translators should be abandoned and applications should have direct access to the data. However, in reality, by the mid-2020s, the concept of BIM began to resemble a “divide and conquer” strategy, where the interests of software vendors using closed geometric kernels are prioritized over the development of open information exchange.

Today, BIM is perceived as an integral part of the construction industry. But over the past two decades, the promise of simplified collaboration and data integration has largely gone unrealized. Most solutions are still tied to closed formats or neutral formats and specialized tools. We will look in detail at the history of BIM, open BIM and IFC, as well as the issues of interoperability and geometric kernels in Part 6 of the book “CAD and BIM: Marketing, Reality and the Future of Design Data in Construction”.

Today, the industry faces a key challenge to move from the traditional understanding of CAD (BIM) as a modeling tool to its use as a full-fledged database. This requires new approaches to working with information, abandoning the dependence on closed ecosystems and implementing open solutions.

With the development of reverse engineering tools that allow access to CAD databases and the proliferation of Open Source and LLM technologies, users and developers in the construction industry are increasingly moving away from the vague terms of software vendors. Instead, the focus is shifting to what really matters: data (databases) and processes.

Behind the trendy acronyms and visualizations are standard data management practices: storage, transfer and transformation – i.e. the classic ETL process (Extract, Transform, Load). As in other industries, the digitalization of construction requires not only exchange standards, but also clearly structured handling of heterogeneous information.

In order to fully utilize the potential of CAD (BIM) data, companies need to rethink their approach to information management. This will inevitably lead to a key element of digital transformation – unification, standardization and meaningful structuring of the data that construction professionals work with on a daily basis.

.

.

Leave a Reply

Change language

Post's Highlights

Stay updated: news and insights



We’re Here to Help

Fresh solutions are released through our social channels

UNLOCK THE POWER OF DATA
 IN CONSTRUCTION

Dive into the world of data-driven construction with this accessible guide, perfect for professionals and novices alike.
From the basics of data management to cutting-edge trends in digital transformation, this book
will be your comprehensive guide to using data in the construction industry.

Related posts 

Focus Areas

navigate
  • ALL THE CHAPTERS IN THIS PART
  • A PRACTICAL GUIDE TO IMPLEMENTING A DATA-DRIVEN APPROACH (8)
  • CLASSIFICATION AND INTEGRATION: A COMMON LANGUAGE FOR CONSTRUCTION DATA (8)
  • DATA FLOW WITHOUT MANUAL EFFORT: WHY ETL (8)
  • DATA INFRASTRUCTURE: FROM STORAGE FORMATS TO DIGITAL REPOSITORIES (8)
  • DATA UNIFICATION AND STRUCTURING (7)
  • SYSTEMATIZATION OF REQUIREMENTS AND VALIDATION OF INFORMATION (7)
  • COST CALCULATIONS AND ESTIMATES FOR CONSTRUCTION PROJECTS (6)
  • EMERGENCE OF BIM-CONCEPTS IN THE CONSTRUCTION INDUSTRY (6)
  • MACHINE LEARNING AND PREDICTIONS (6)
  • BIG DATA AND ITS ANALYSIS (5)
  • DATA ANALYTICS AND DATA-DRIVEN DECISION-MAKING (5)
  • DATA CONVERSION INTO A STRUCTURED FORM (5)
  • DESIGN PARAMETERIZATION AND USE OF LLM FOR CAD OPERATION (5)
  • GEOMETRY IN CONSTRUCTION: FROM LINES TO CUBIC METERS (5)
  • LLM AND THEIR ROLE IN DATA PROCESSING AND BUSINESS PROCESSES (5)
  • ORCHESTRATION OF ETL AND WORKFLOWS: PRACTICAL SOLUTIONS (5)
  • SURVIVAL STRATEGIES: BUILDING COMPETITIVE ADVANTAGE (5)
  • 4D-6D and Calculation of Carbon Dioxide Emissions (4)
  • CONSTRUCTION ERP AND PMIS SYSTEMS (4)
  • COST AND SCHEDULE FORECASTING USING MACHINE LEARNING (4)
  • DATA WAREHOUSE MANAGEMENT AND CHAOS PREVENTION (4)
  • EVOLUTION OF DATA USE IN THE CONSTRUCTION INDUSTRY (4)
  • IDE WITH LLM SUPPORT AND FUTURE PROGRAMMING CHANGES (4)
  • QUANTITY TAKE-OFF AND AUTOMATIC CREATION OF ESTIMATES AND SCHEDULES (4)
  • THE DIGITAL REVOLUTION AND THE EXPLOSION OF DATA (4)
  • Uncategorized (4)
  • CLOSED PROJECT FORMATS AND INTEROPERABILITY ISSUES (3)
  • MANAGEMENT SYSTEMS IN CONSTRUCTION (3)
  • AUTOMATIC ETL CONVEYOR (PIPELINE) (2)

Search

Search

057 Speed of decision making depends on data quality

Today’s design data architecture is undergoing fundamental changes. The industry is moving away from bulky, isolated models and closed formats towards more flexible, machine-readable structures focused on analytics, integration and process automation. However, the transition...

060 A common language of construction the role of classifiers in digital transformation

In the context of digitalization and automation of inspection and processing processes, a special role is played by classification systems elements – a kind of “digital dictionaries” that ensure uniformity in the description and parameterization...

061 Masterformat, OmniClass, Uniclass and CoClass the evolution of classification systems

Historically, construction element and work classifiers have evolved in three generations, each reflecting the level of available technology and the current needs of the industry in a particular time period (Fig. 4.2-8): First generation (early...

Don't miss the new solutions

 

 

Linux

macOS

Looking for the Linux or MAC version? Send us a quick message using the button below, and we’ll guide you through the process!


📥 Download OnePager

Welcome to DataDrivenConstruction—where data meets innovation in the construction industry. Our One-Pager offers a concise overview of how our data-driven solutions can transform your projects, enhance efficiency, and drive sustainable growth. 

🚀 Welcome to the future of data in construction!

You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

By downloading, you agree to the DataDrivenConstruction terms of use 

Stay ahead with the latest updates on converters, tools, AI, LLM
and data analytics in construction — Subscribe now!

🚀 Welcome to the future of data in construction!

You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

By downloading, you agree to the DataDrivenConstruction terms of use 

Stay ahead with the latest updates on converters, tools, AI, LLM
and data analytics in construction — Subscribe now!

🚀 Welcome to the future of data in construction!

You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

By downloading, you agree to the DataDrivenConstruction terms of use 

Stay ahead with the latest updates on converters, tools, AI, LLM
and data analytics in construction — Subscribe now!

🚀 Welcome to the future of data in construction!

You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

By downloading, you agree to the DataDrivenConstruction terms of use 

Stay ahead with the latest updates on converters, tools, AI, LLM
and data analytics in construction — Subscribe now!

🚀 Welcome to the future of data in construction!

You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

By downloading, you agree to the DDC terms of use 

🚀 Welcome to the future of data in construction!

You're taking your first step into the world of open data, working with normalized, structured data—the foundation of data analytics and modern automation tools.

By downloading, you agree to the DataDrivenConstruction terms of use 

Stay ahead with the latest updates on converters, tools, AI, LLM
and data analytics in construction — Subscribe now!

DataDrivenConstruction offers workshops tested and practiced on global leaders in the construction industry to help your team navigate and leverage the power of data and artificial intelligence in your company's decision making.

Reserve your spot now to rethink your
approach to decision making!

Please enable JavaScript in your browser to complete this form.

 

🚀 Welcome to the future of data in construction!

By downloading, you agree to the DataDrivenConstruction terms of use 

Stay ahead with the latest updates on converters, tools, AI, LLM
and data analytics in construction — Subscribe now!

Have a question or need more information? Reach out to us directly!
Schedule a time to discuss your needs with our team.
Tailored sessions to help your team grow — let's plan together!
Have you attended one of our workshops, read our book, or used our solutions? Share your thoughts with us!
Please enable JavaScript in your browser to complete this form.
Name
Data Maturity Diagnostics

🧰 Data-Driven Readiness Check

This short assessment will help you identify your company's data management pain points and offer solutions to improve project efficiency. It takes only 1–2 minutes to complete and you will receive personalized recommendations tailored to your needs.

🚀 Goals and Pain Points

What are your biggest obstacles today — and your goals for the next 6 months? We’ll use your answers to build a personalized roadmap.

Build your automation pipeline

 Understand and organize your data

Automate your key process

Define a digital strategy

Move from CAD (BIM) to databases and analytics

Combine BIM, ERP and Excel

Convince leadership to invest in data

📘  What to Read in Data-Driven Construction Guidebook

Chapters 1.2, 4.1–4.3 – Technologies, Data Conversion, Structuring, Modeling:

  • Centralized vs fragmented data

  • Principles of data structure

  • Roles of Excel, DWH, and databases

Chapters 5.2, 7.2 – QTO Automation, ETL with Python:

  • Data filtering and grouping

  • Automating QTO and quantity takeoff

  • Python scripts and ETL logic

Chapter 10.2 – Roadmap for Digital Transformation:

  • Strategic stages of digital change

  • Organizational setup

  • Prioritization and execution paths

Chapters 4.1, 8.1–8.2 – From CAD (BIM) to Storage & Analytics:

  • Translating Revit/IFC to structured tables

  • BIM as a database

  • Building analytical backends

Chapters 7.3, 10.2 – Building ETL Pipelines + Strategic Integration:

  • Combining Excel, BIM, ERP

  • Automating flows between tools

  • Connecting scattered data sources

Chapters 7.3, 7.4 – ETL Pipelines and Orchestration (Airflow, n8n):

  • Building pipelines

  • Scheduling jobs

  • Using tools like Airflow or n8n to control the flow 

Chapters 2.1, 10.1 – Fragmentation, ROI, Survival Strategy:

  • Hidden costs of bad data

  • Risk of inaction

  • ROI of data initiatives

  • Convincing stakeholders

Download the DDC Guidebook for Free

 

 

🎯 DDC Workshop That Solves Your Puzzle

Module 1 – Data Automation and Workflows in Construction:
  • Overview of data sources
  • Excel vs systems
  • Typical data flows in construction
  • Foundational data logic

Module 3 – Automated Data Processing Workflow:
  • Setting up ETL workflows
  • CAD/BIM extraction
  • Automation in Excel/PDF reporting

Module 8 – Converting Unstructured CAD into Structured Formats 
  • From IFC/Revit to tables
  • Geometric vs semantic data
  • Tools for parsing and transforming CAD models

Module 13 – Key Stages of Transformation 
  • Transformation roadmap
  • Change management
  • Roles and responsibilities
  • KPIs and success metrics

Module 8 – Integrating Diverse Data Systems and Formats
  • Excel, ERP, BIM integration
  • Data connection and file exchange
  • Structuring hybrid pipelines

Module 7 – Automating Data Quality Assurance Processes 
  • Rules and checks
  • Dashboards
  • Report validation
  • Automated exception handling

Module 10 – Challenges of Digitalization in the Industry 
  • How to justify investment in data
  • Stakeholder concerns
  • ROI examples
  • Failure risks

💬 Individual Consultation – What We'll Discuss

Audit of your data landscape 

We'll review how data is stored and shared in your company and identify key improvement areas.

Select a process for automation 

We'll pick one process in your company that can be automated and outline a step-by-step plan.

Strategic roadmap planning 

Together we’ll map your digital transformation priorities and build a realistic roadmap.

CAD (BIM) - IFC/Revit model review 

We'll review your Revit/IFC/DWG data and show how to convert it into clean, structured datasets.

Mapping integrations across tools 

We’ll identify your main data sources and define how they could be connected into one workflow.

Plan a pilot pipeline (PoC) 

We'll plan a pilot pipeline: where to start, what tools to use, and what benefits to expect.

ROI and stakeholder alignment 

📬 Get Your Personalized Report and Next Steps

You’ve just taken the first step toward clarity. But here’s the uncomfortable truth: 🚨 Most companies lose time and money every week because they don't know what their data is hiding. Missed deadlines, incorrect reports, disconnected teams — all symptoms of a silent data chaos that gets worse the longer it's ignored.

Please enter your contact details so we can send you your customized recommendations and next-step options tailored to your goals.

💡 What you’ll get next:

  • A tailored action plan based on your answers

  • A list of tools and strategies to fix what’s slowing you down

  • An invite to a free 1:1 session to discuss your case

  • And if you choose: a prototype (PoC) to show how your process could be automated — fast.

Clean & Organized Data

Theoretical Chapters:

Practical Chapters:

What You'll Find on
DDC Solutions:

  • CAD/BIM to spreadsheet/database converters (Revit, AutoCAD, IFC, Microstation)
  • Ready-to-deploy n8n workflows for construction processes
  • ETL pipelines for data synchronization between systems
  • Customizable Python scripts for repetitive tasks
  • Intelligent data validation and error detection
  • Real-time dashboard connectors
  • Automated reporting systems

Connect Everything

Theoretical Chapters:

Practical Chapters:

What You'll Find on
DDC Solutions:

  • CAD/BIM to spreadsheet/database converters (Revit, AutoCAD, IFC, Microstation)
  • Ready-to-deploy n8n workflows for construction processes
  • ETL pipelines for data synchronization between systems
  • Customizable Python scripts for repetitive tasks
  • Intelligent data validation and error detection
  • Real-time dashboard connectors
  • Automated reporting systems

Add AI & LLM Brain

Theoretical Chapters:

Practical Chapters:

What You'll Find on
DDC Solutions:

  • CAD/BIM to spreadsheet/database converters (Revit, AutoCAD, IFC, Microstation)
  • Ready-to-deploy n8n workflows for construction processes
  • ETL pipelines for data synchronization between systems
  • Customizable Python scripts for repetitive tasks
  • Intelligent data validation and error detection
  • Real-time dashboard connectors
  • Automated reporting systems
033 The emergence of the BIM (BOM) concept and the use of CAD in processes
This website uses cookies to improve your experience. By using this website you agree to our Data Protection Policy.
Read more
×