IBM Watson projects

There are two types of projects:

  • Legacy projects are older style projects that were created with Object Storage OpenStack Swift. This option is no longer available.
  • IBM Watson projects that are created with IBM Cloud Object Storage.

You can see the object storage type on the project Settings page.

IBM Watson projects have new features for Watson Studio and work with the Watson Knowledge Catalog app and new tools.

IBM Watson projects have these differences from legacy projects:

Object storage

The object storage associated with IBM Watson projects is IBM Cloud Object Storage. Files in IBM Cloud Object Storage are encrypted on disk. All files that are added to the project are stored in object storage, including notebook files.


You can preview the contents of an asset by clicking its name on the Assets page.

If you have the Watson Knowledge Catalog app, you can create a profile of any data asset to view the data classes that are inferred for each column. From the asset preview, click the Profile tab and then click Create Profile.

You can perform an action on multiple assets.


You create connections within the project. Choose Add to project > Connection. Your existing IBM Cloud services appear automatically, with your credentials prefilled. See Create a connection in a project.

You can edit a connection by clicking its name on the Assets page.

Viewer permissions

Project collaborators with the Viewer role can now see credentials and other code that’s marked as hidden in notebooks.

If you want to share a notebook with someone and hide sensitive code cells, share a link to the notebook instead of adding the person to the project as a collaborator. See Share notebooks.

Watson Knowledge Catalog

If you have the Watson Knowledge Catalog app, you’ll see a Catalog tab in the Find Data panel on the Assets page. If the project restricts collaborators to members of the IBM Cloud account or company, you can copy assets from the catalog into the project. See Adding catalog assets to a project. You can also publish assets from the project into the catalog. See Publish an asset from a project to a catalog.

Data Refinery

Data Refinery is a self-service data preparation tool that you can use to quickly transform large amounts of raw data into consumable, quality information that’s ready for analysis. For example, you can use the qualified data produced by Data Refinery in notebooks that you create with Watson Studio.

The following features of Data Refinery make it easy to explore, prepare, and deliver data that people across your organization can trust.

  • Powerful operations to clean, organize, fix, and validate your data
  • Scripting support for the efficient and flexible manipulation of data
  • Scheduling and monitoring of data preparation flows
  • Profiles for validating your data and visualizations for gaining insight into your data
  • Automatic enforcement of policies by masking sensitive and protected information
  • Support for unstructured data

Get started with Data Refinery from the Data assets page of your project. Select Refine from the ACTIONS menu of the data asset you want to refine.

Streams flows

Use streams flows to collect, curate, analyze, and act on massive amounts of changing data in real time. By using out-of-the-box examples, a wizard, or sample data that we provide, your streams flow can be running in a matter of minutes. The streams flow will be deployed to the industry-leading IBM Streaming Analytics service, which offers best-in-class analytics and optimization.

You can get started with streams flows by creating a streams flow asset. See Get started with streams flows.

Project readme file

The project Overview page has a readme file where you can document your project using standard Markdown. See Overview page.