Collaboration is key in every industry, whether that’s architects working with contractors and sub-contractors, industrial designers working with fabricators and process engineers, or entertainment producers working with creative and technical professionals.
In today’s era of digitized workflows, collaboration requires sharing digital models and data. But because each discipline has traditionally worked in its own siloed desktop applications, that’s often been easier said than done. Translating data was time consuming and laborious, and involved bespoke applications and plugins and often multiple workarounds. What’s more, it required you to share a copy of the entire file. That can quickly become out-of-date and can include proprietary IP, such as custom families, that you may not want to share with outside partners.
Data Exchange is an Autodesk Platform Services API that lets you select and share a subset of your model data and set permissions to control its use. It facilitates collaboration by making it easy for the partner to get the data they need without having to download and sort through the whole file, and by updating all changes on the shared cloud information model, so everyone always has the most recent version at their fingertips.
“Each collaborator can access just the data that they need when they need it, share it with the right stakeholders, and move it between solutions critical to your operations, whether that's an Autodesk tool or other products you rely on.”
—Andrew Anagnost, CEO, Autodesk in the General Session Day 1, AU 2022
The Data Exchange API is in public beta through mid-2023. At AU 2022, a number of industry professionals led classes about their experience putting the API to work.
Explore new approaches to data sharing and build your skills and with these sessions:
Not sure how to get started? Nem Kumar explains the challenges that industry faces when it comes to sharing data, discusses how the Data Exchange API can help to solve these problems, then shows you how to create connectors between two desktop or web applications, sharing best practices for security and performance.
Structural and environmental analysis
Frode Tørresdal shows how to use the Data Exchange API for automated structural analysis and for analysis related to cost and environmental impact. Each partner gets a different subset of the model data that’s relevant for their purpose.
Solar arrays on a new building are an excellent example of the need for this kind of “granular” data—meaning model data that’s broken into meaningful, discrete units. Solar arrays themselves are manufactured products, but they need to fit into the architecture and engineering systems of the building underneath. Vivek Mahajan and Sandip Jadhav share how they used the Data Exchange API to streamline the process. For the building designers, they created a Revit plugin, in which they could enter the solar load requirements to the BIM model to automatically create a view that consists only of the roof elements. For the product designer, meanwhile, they created an Inventor plugin that automatically creates an assembly relative to the solar load required.
An open ecosystem
The Data Exchange API doesn’t only facilitate data sharing between Autodesk products—it also enables you to work with third-party software. Nauman Mysorewala walks through the process to automate data sharing between Revit and Microsoft PowerBI. This enabled them to share geometry data with fabrication partners and share 5D and 6D BIM data related to costs and the building lifecycle with the owners and other stakeholders.
Standardizing data extraction
The team from Stantec has been tackling the challenge of granular data exchange for years. In the past, they solved the problems by doing their own C# coding using the Revit APIs. These plugins were highly specific to the two applications, with no ability to repurpose the work. And because they often ended up sharing entire Revit files, they ran the risk of sharing custom families and other proprietary content. With the Data Exchange API, they standardized their processes, so that the tools can be modified for different collaborations, and they used generic data that stripped away their valuable IP. Robert Manna and James Mazza share the work.
Interoperability has long been an important goal, but the reality is that getting data from one desktop application into another often took significant work. As Nem Kumar points out, it’s common to hear professionals say that they spend as much as 30% of their time focused on data management. By moving to a platform approach and using the Data Exchange API, the dream of interoperability finally becomes not only achievable, it becomes predictable, scalable, and secure.