Following the trend on this blog to highlight uses of data and analytics, I thought I’d share some of the recent developments in our platform for collecting and analyzing BIM data – Minecart.
For the last two years, we have been deploying Minecart as a data “aggregator” for studying underlying model quality and portfolio metrics. As consultants, we use Minecart to support our ability to advise our clients on ways they can improve their digital transformation with BIM as a data resource to improve business operations. Our clients here have included architects as well as owners – each of whom have a variety of specific business and data needs.
We use Minecart to support our ability to advise our clients on ways they can improve their digital transformation with BIM as a data resource to improve business operations.
To date, Minecart has been used primarily for data harvesting – we have made Revit and IFC-based tools for doing a complete model exports to centralized databases. This has afforded us the ability to perform analysis of model elements, areas, and general data quality.
More recently, we have invested in developing a number of new approaches focused on leveraging BIM data as a business resource with a focus on improving quality and productivity. Here are three capabilities are currently under development (and waiting to be customized!)
BIM-based authoring and coordination is still primarily a file-based management paradigm. While cloud platforms have created new opportunities for collaboration and eased the burden of file management, files still remain drive the data storage approach. From a data collection perspective, our challenge has been how to perform data harvesting across many files at once. We have developed a number of approaches and interfaces for accomplishing this.
Revit is challenging from an automation standpoint. Firstly, Autodesk does not allow access to the underlying data of the proprietary RVT file without a running version of Revit and its API (at least not without investing in reverse engineering the file). Secondly, Revit disallows remote control access and operation in a “headless” state which makes it challenging to process multiple files without some level of user interaction.
To overcome this, we have created a method for running Revit as a pseudo-remote controlled application that listens for external instruction files containing a file queue – it’s a bit of a workaround, but functions quite well and has improved the ability to rapidly harvest multiple files. Using this method, we can batch process many files in a single pass and in a fraction of the time.
We have also created batch harvesters for IFC files – which is much easier to accomplish since they are an open format and do not require the presence of an proprietary BIM application. These tools allow users to specific lists of files and use open source libraries, like xBIM, to rapidly collect data and organize it into a single database.
Performing complete model data harvests can be computationally expensive and time consuming. We usually recommend that this activity be positioned as a milestone-based or archival-based activity. However, we also recognize that there is plenty of data that can be gathered over time that can be used to gain insight into production trends. As a result, we have created methods for collecting real-time data from an active session of Revit and piping it into centralized databases.
Document modifications, warnings, file sizes, and save times are recorded in the background as users perform modeling tasks. Records are then logged to the database when users save or sync to their central models. From this data, we can begin to understand production trends and identify ways to improve the modeling process.
In-App Model Analysis
Model data need not be harvested and exported externally to be valuable or insightful. Sometimes a designer or manager needs to be able to review their model data as they are working on their model. To that end, we have created a prototype for visualizing model data as an in-app dockable utility. Users can access interactive charts that communicate important model statistics.
This approach has numerous potential applications. It could be used as QA/QC check to help a user understand if there are model quality issues to address. It could also be used to visualize important metrics such as space program or environmental performance.
We are actively developing Minecart implementations to clients – each of whom has different objectives and needs for their data. With these three new developments, we are expanding our ability to deliver custom solutions that take advantage of BIM assets as a data resource.
We anticipate that these tools and ideas will rapidly evolve as we engage our clients to solve real-world business and project problems with data
We anticipate that these tools and ideas will rapidly evolve as we engage our clients to solve real-world business and project problems with data. If you have an idea for how you would like to implement these ideas in your business, please reach out!
How we can help…
- Define your data innovation strategy
- Create tailored solutions with software customization
- Support the digital workflow with project consulting