An image processing tool developed at CD3 helped biologists Yuling Jiao and Elliot Meyerowitz discover that a signaling molecule departs from the primordial to the meristem to promote robustness in leaf patterning in the Arabidopsis thaliana plant. The tool accurately separated co-localized signals (shown in red and green in the image) allowing for the clear visualization of polarity in each cell toward the meristem center.Image Credit: Alexandre Cunha/Caltech and Jiyan Qi and Yuling Jiao/Chinese Academy of SciencesA kickoff event for the collaboration was held at the end of April at Caltech's Cahill Center for Astronomy and Astrophysics.

"This is a wonderful example of a deep cooperation between Caltech and JPL that we think will serve to strengthen connections between the campus and the lab," says George Djorgovski, professor of astronomy and director of CD³. "We believe the joint venture will enable and stimulate new projects and give both campus and JPL researchers a new competitive advantage."

Individually, each center strives to provide the intellectual infrastructure, including expertise and advanced computational tools, to help researchers and companies from around the world analyze and interpret the massive amounts of information they now collect using computer technologies, in order to make data-driven discoveries more efficient and timely.

"We've found a lot of synergy across disciplines and an opportunity to apply emerging capabilities in data science to more effectively capture, process, manage, integrate, and analyze data," says Daniel Crichton, manager of the CDST. " JPL's work in building observational systems can be applied to several disciplines from planetary science and Earth science to biological research."

The Caltech center is also interested in this kind of methodology transfer—the application of data tools and techniques developed for one field to another. The CD³ recently collaborated on one such project with Ralph Adolphs, Bren Professor of Psychology and Neuroscience and professor of biology at Caltech. They used tools based on machine learning that were originally developed to analyze data from astronomical sky surveys to process neurobiological data from a study of autism.

"We're getting some promising results," says Djorgovski. "We think this kind of work will help researchers not only publish important papers but also create tools to be used across disciplines. They will be able to say, 'We've got these powerful new tools for knowledge discovery in large and complex data sets. With a combination of big data and novel methodologies, we can do things that we never could before.'"

Both the CD³ and the CDST began operations last fall. The Joint Initiative already has a few projects under way in the areas of Earth science, cancer research, health care informatics, and data visualization.

"Working together, we believe we are strengthening both of our centers," says Djorgovski. "The hope is that we can accumulate experience and solutions and that we will see more and more ways in which we can reuse them to help people make new discoveries. We really do feel like we're one big family, and we are trying to help each other however we can."