Our world is whirling in data. So much so, there is now an entire field (data science), and a new profession (data scientist), that is expected to make sense of it all.

As a field, data science obtains, scrubs, explores, models and interprets data. And the data scientist, called the “Sexiest Job of the 21st Century” by Harvard Business Review, is to help interpret and manage the data and solve problems. Data scientists build algorithms, write code and visualize data, which can get difficult to manage.

The partner to the data scientist is Jupyter Notebooks - a free, open-source software designed as a computational notebook, to document, visualize and run complex code with data.

Project Jupyter was recently given the 2017 Software System Award from the Association of Computing Machinery, the world’s largest society of educational and academic computer scientists. The 15-member Jupyter Steering Committee, led by two physics professors Brian Granger at Cal Poly San Luis Obispo and Fernando Pérez at UC Berkeley, is the largest team ever to win this top honor. Past award recipients include the inventors of the World Wide Web, TCP/IP networking, the UNIX operating system and the Java programming language.

From the commercial to the cosmic and beyond

Tech giants Microsoft, Google and IBM use Jupyter Notebooks to help analyze, store and make available data sets. The companies have created entire commercial data science platforms based on the software system. Jupyter has even contributed to the scientific collaboration that discovered gravitational waves. The LIGO observatory, whose discovery was recognized with the 2017 Nobel Prize in Physics, publishes Jupyter Notebooks that allow anyone to replicate their original analyses of the colliding black holes and colliding neutron stars that generate gravitational ripples in spacetime.

“One of the big ideas of Jupyter is a human-centered approach to computational research,” said Brian Granger.

“Jupyter lets people write code in a way that creates a narrative, or story, around the code and data. When these narratives are shared with other people, they are able to better understand and visualize the results, make decisions and connect the code and data to their own situations.”

That big idea is thriving, and not just in the business world. Students across the country – from college to high school campuses – use the software tool. At UC Berkeley, the fastest-growing course is Foundations of Data Science, offered as part of its new data science major, which uses Jupyter Notebooks for thousands of students a semester. Many other universities, and even high schools, also employ Jupyter Notebooks to teach data science. The system is a partner, used to teach aerodynamics, computer science, statistics, physics and cognitive science, among other subjects.

Fernando Perez shares in The Atlantic that computational notebooks “bring that idea of live narrative out ... You can think through the process, and you’re effectively using the computer, if you will, as a computational partner, and as a thinking partner.”

Scaling the idea

In 2015, our foundation, along with the Leona M. and Harry B. Helmsley Charitable Trust and Alfred P. Sloan Foundation, partnered to help expand and improve the capabilities of the Jupyter Notebook with $6 million in grants. The grant from the Moore Foundation is part of our Data-Driven Discovery Initiative and is an example of our strategy that focuses on the creation and dissemination of innovative tools for engaging in data-driven scientific research.

“Jupyter is the kind of innovative technology that supports groundbreaking new research. Software is the core instrument for data-driven scientists, and it is becoming increasingly critical for making new discoveries in most every discipline. Unfortunately, technology like Jupyter is often under-supported and not sufficiently recognized for its contribution to research results,” said Chris Mentzel, program director at the Moore Foundation. “We believe that research software will continue to accelerate new science and we are excited to see Jupyter gain such broad adoption.”

Learn more about foundation-supported work in Data-Driven Discovery

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