Jupyter Notebooks: Content Management Contributions

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There has been a growing interest in open source technologies associated with data processing and analytics within the mainstream business marketplace. Our clients seek more than the timely discovery of insights, they desire to quickly and easily communicate their findings through visualizations and narration while also having the option to share their results as reproducible research. In response, we have been incubating the IBM Knowledge Anyhow Workbench, a walk-up-and-use cloud environment for doing ad-hoc analytics and creating data products in interactive Jupyter notebooks. Our technology incubation efforts have yielded several content management features that have helped us create analytical solutions that are just-in-time for a growing constituency of data scientists in industry verticals such as finance, healthcare, and retail.

As IBM product teams have begun to embrace Jupyter technologies as well as our features in their offerings, we believe it will be beneficial to both them and the broader Jupyter community to have these features upstream, in open source. To that end, we’ve ported key Knowledge Anyhow Workbench features such as full text search, importable Python cookbooks, and drag/drop upload to a pip installable Jupyter extension which we wish to contribute to the community.

Here’s a preview of a few of our content management features:


Click to play.


We have made it possible to add a Search button on any or all of the user views (notebook, file-tree, text editor).







Click to play.


Analogous to include directives which enable code reuse, we have made it possible for the contents of a secondary notebook to be included by reference into the another notebook.






Click to play.


Since notebooks are often used as a report that provides a narrative around a specific data exploration exercise, we have provided a complimentary table of contents button that allows notebook users to easily navigate the contents of a notebook.




Pending community feedback, we’d like to port more of our Knowledge Anyhow Workbench features such as:

  • Download file bundles (.zips) from the Jupyter dashboard
  • Import any web-accessible notebook via an omnibox
  • Share notebooks from one Jupyter instance to another via share links
  • Examples of cookbooks
  • Dashboard creation
  • Upload files easily from any Jupyter Notebook page

Click to play.

Interested in learning more?

If you’re interested in more information about IBM Emerging Technology and Jupyter Notebooks, please contact Dan Gisolfi (info@ibmjstart.com).

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Dan Gisolfi
As CTO for Trusted Identity, Dan is focused on the development and execution of a trusted identity strategy for both citizen and corporate identity interactions using blockchain technologies. This endeavor includes the development of a formal IBM Mobile Identity offering, the definition and development of a trusted identity reference architecture, and the creation of devops tools that streamline the delivery of trusted identity solutions for clients.
Dan Gisolfi
Dan Gisolfi