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How Tekla Model Sharing uses the sharing service

Last updated March 6, 2017 by Tekla User Assistance tekla.documentation@trimble.com

Software version: 
2017

How Tekla Model Sharing uses the sharing service

How Tekla Model Sharing uses the sharing service

When you start to share a model using Tekla Model Sharingcloud service for collaboration and for storing and sharing a model

Tekla Model Sharing is one of the Tekla online services.

, the model is connected to the cloud-based sharing service.

  • To send model changes to the sharing service, you need to write out.

  • To fetch other users' model changes from the sharing service, you need to read in.

When you read in other users' changes, the updates to your local version of the shared modelmodel used for collaboration over the Tekla Model Sharing service

With a shared model, each user works with their own model and the changes are shared through Tekla Model Sharing. A shared model requires the use of a single-user model. The same model cannot be a shared model and a multi-user model.

are delivered to you as incremental packets. This means that when you read in, the data that is fetched from the sharing service is merged with the data on your computer. You need to read in all shared changes before you can write out your own changes to the sharing service.

Note that there is no central model in the sharing service as such, only a model instance that consists of a model baseline and incremental updates. You cannot open the model in the sharing service or access any files.

The image below shows how the model data is stored to the sharing service. Each user fetches the model data from the sharing service to their local versions of the model when they read in. User authentication is based on Trimble Identity.

Note:

If there are several Tekla Model Sharing users in the same office, we recommend you to install a separate cache service. The cache service is recommended especially in regions where the download speed may be limited. The use of cache service reduces the download effort and enables faster download times.

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