Introduction to Building Data Management (BDM) Concept and Workflow
This document looks to discuss what professionals are using today to manage data then offer an alternative which will revolutionise workflow from inception through construction to operation.
Data What are we specifically talking about?
Scale How much and what are the volumes?
Capture How and when do we collect the data?
Management Having collected the data what do we do with it?
Validation How do verify what’s in the brief is in the drawing and actually physically in the room, space or zone?
Interoperability How do we ensure the data easily available in the different places users want to access it?
BIM has been a hot topic in the AEC sector now for over 10 years and much has happened over that period and progress has been patchy depending on the type of building and its location.
Many Software solutions have come to market claiming to be the single answer to successful implementing BIM. Let’s be clear BIM isn’t just software nor is it delivery using software from single software vendor. It’s a process which requires a number of different interlocking software solutions to manage all the graphical and non-graphical data along with its associated Meta Data.
Governments around the world have become involved in BIM because they see as way to control their massive Capex and Opex budgets. Consequently there have been many Government led BIM initiatives launched such as the GSA in the US, BCA in Singapore and UK BIM Task Group in the UK
Credit has to be given to the work of the UK Government’s BIM Task Group who’s been instrumental in developing and formalising a clear, structured and workable BIM process. There process has outlined what needs to be achieved and what order but it hasn’t stated what tools need to be used to achieve BIM. Detailed below is a Dutch take on the UK Government’s BIM Strategy which makes the process even more straightforward and clear.
The question is where are you on this road map, how do you move forward to the next stage and part of this is clearly understanding and recognising the importance of defining your data management strategy?
Without structure, rationalization and management anarchy prevails which ensures you’re unable to verify or validate leading to mistakes, poor quality, low productivity and increased cost. This is true whatever sector you’re working in and building design, construction and operations is no different.
Building Data Management is bringing order to data and information captured from inception to handover and into operations and which should be captured once wherever possible. This is achieved by centralising the captured data in database where it’s structured and rationalised allowing the data to be verified, validated, analysis and reported on. Managing building data significantly reduces mistakes and rework, improves and increases quality and improves productivity and profitability whilst reducing costs.
When we are talking about data we need to be very specific about what aspect of data within design, construction and operations is being referred to. In this case we are talking about the non-graphical data associated with the room, space or zone at its highest level such as room name, description, area, volume etc. and again with equipment such as name, description, size etc. It needs to be emphasised the meta data goes well beyond those just highlighted is only the almost minimum meta data need to clearly identify the room, space or zone or piece of equipment.
The purpose of this exercise is not to scare you more to ensure you understand the challenges faced when embracing the BIM process and grasp the volume of data need to be captured, managed and reported on – “just to show you there’s an elephant in the room”
We have taken this from typical office type room rather a more complex building such as a hospital.
Room, Zone or Space
We estimate this room, space or zone contains at least 3,000 pieces of Meta data to describe the room and the equipment it contains. It would probably be at least double this if the MEP equipment was included.
These are just some of the Meta data:
- Room Name
- Room Number
- Room Description
- Room Function
- Department Name
- Department Number
- Floor Number
- Building Number
- Required Area
- Height – Floor to Floor
- Height – Floor to ceiling
- Wall Type – North, South, East , West
- Wall Colour – North, South, East , West
- Floor Covering
- Ceiling Type
- Circulation Heat
- Lighting Lux
Now shifting our attention to the equipment contained in this room, space or zone. It contains a about 20 pieces of equipment including tables, chairs etc.
Using the AIA’s LOD system which LOD schema what is the right level Meta data required? Being honest each is right depending on the whether you are in the design, engineering, construction or operations because data is added incrementally at each stage.
We can quite confidentially advise LOD 500 is only the basic data we are seeing being captured and it’s much more.
- Manufacturer Model Number
- Equipment Code
- Fix Height
- Services Required
- Purchase Information
- Facilities Information
- O&M Information
And this is again only high level
Let’s place what we have discussed into a practical and on-going project we are working on in North America. It’s an Uber hospital called the CHUM 3.5 SqFt in Montreal with 15,000 rooms and over 500,000 pieces of equipment, 27,000 doors, 100,000 electrical wall sockets spread across a multiple building campus and the data is spread across multiple Revit models for architecture, FFE and MEP.
Equals at least 50 million pieces of data! Try managing this volume in Excel!
What you need to manage could be less or more depending on the type and scale of project your working and what the owners demands as a requirement to be captured.
This is the typical workflow we find in place where Excel is being used in almost electronic paper way where the information contained in the spreadsheet is given as a Schedule of Accommodation (SoA) along with the assocated Schedule of Equipment (SoE) to the archirect and interior designer to be place into Revit.
We call this the “many to many” workflow where the brief is created in Excel and comprises Room, FFE, Door and MEP data.
In this situation every piece of data for the room, equipment, door or MEP is managed in isolation. Any amendment or additional information such adding a change a wall outlet from a single outlet to a double or adding or removing a chair from a number of rooms would manually changed at room level. This is a massive undetaking across even a small project nevermind a large campus with 15,000 rooms. Manually manipulating the data in this manner is not efficient and is a task which could lead to errors creeping into the project which might not be spotted until a much later stage where the cost implication potentially could be very high.
Examing this workflow methodologly in more detail you can see the worflow like this with the Excel being the reference point for what needs to be placed in the model.
The only practical way to verify and validate what’s in the brief has been placed in the model(s) is by the “old fashioned” way of sitting around a table and completing manually and visual check and marking up the differences.
Now image doing this across multiple models!
It will also come apparent as we step through the Building Data Management workflow data once captured is knowledge it can be used again and again. A really significant advantage to those involved in the process from inception to operations, the ability to analysis design and performance from past projects to include accumulated learnings into new projects making them better designed and optimised operations.
Data is captured throughout the design, construction and operational phases. In many cases the same piece of data is recaptured many times over as the parties don’t trust the accuracy of the data captured by the other parties. And worst data which could be quite easily captured by one party, without much additional cost, for use by another is not.
Not the optimal way to work
This way of working is highly inefficient, leads to costly mistakes and to the loss of large amounts of useful data and knowledge across the program as this diagram below from buildingSMART illustrate.
Now taking pausing for a moment to think about one common and / or standard item used across a whole campus in every room, zone or space? Now consider the number of these items in one of your projects. How do you manage it?
CodeBook Building Data Management
Putting CodeBook into context with the development of Building Data Management, we have been developing software to manage this process for over 20 years. Starting from the digitisation of room data sheets (RDS) to where we are today with intelligent room data management (iRDM) where we are well beyond the production of simple Room Data Sheets (RDS) of the past.
In terms of the UK Government BIM strategy CodeBook provides the data management capabilities from Level 0 to Level 3 today.
CodeBook is about linking data from inception to operations. From the data contained in the brief i.e. what you want to be designed and built, verifying and validating brief and design whilst capturing the incremental data generated during engineering and construction and then finally verifying and validation the design against what’s in the rooms for post occupancy compliance and handing this over to operators of the building as the starting point for their FM system.
Our workflow is based on the concept a “few to many” relationship where data is captured, structured, sanitized and rationalised into a centralised project database.
Briefing data whether it’s held in Excel, Access, SQL or imported directly from a briefing package for your sector or extracting data from an existing Revit Model all these can be simply and quickly imported. Where the import process for equipment recognises duplicate items and rationalises them into an equipment library where the individual items are linked to thousands of rooms.
Once the room and equipment data is stored in CodeBook Pro it’s linked to the rooms and equipment in Revit and allowing the data to be verify and validate between brief with the design and then between design and what’s physically in the room.
Data can be bi directionally synchronised from and across all the major CAD / BIM platforms across multiple models.
Captured data stored in the database allows deliverables to be quickly and easily produced such room data sheets (RDS), c-sheets, quantity and costs reports by room, department, building or whole campus and there’s report for everybody with almost 90 standard reports available within CodeBook.
Using an external Building Data Management solution with Revit ensures the data content is kept light, should users store significant amounts of data inside Revit users will experience performance degradation. Given CodeBook Pro’s bi directionally capabilities data can be imported from CodeBook Pro into Revit to run reports and removed when not required.
Initial Program Workflow
Taking what has been described above many users start the workflow like this illustrated below:
In Program Workflow
The workflow illustrated below where in reality you will with a number of Revit Models CodeBook Pro manages all the information across all models from one single CodeBook Pro project database. In addition data can be extracted from CodeBook Pro into Excel for those professionals who don’t have or need CodeBook that will provide new and amended data. This can be easily imported and blended into the existing information.
Future Program Workflow
Having used CodeBook on previous similar projects a new workflow where the brief could come from Excel, an existing CodeBook project and / or a Revit Model (s).
We have worked through the topics listed below:
Data We have clearly defined data as Meta Data associated with Non Graphical items
Scale We have illustrated the volumes of data likely to be encounter
Capture We have shown capturing data once is the most efficient workflow
Management We have illustrated the power of managing data from a centralised database is much more efficient and improves quality control
Validation We have clearly shown how to automate the validation process ensuring mistakes don’t creep into the design
Interoperability We have shown data can be easily used by all parties irrespective of what BIM or CAD Solution utilized on the project