Call for Reproducibility Workflows

Cyrus Dioun / April 26, 2016

BIDS fellows Cyrus Dioun and Garret Christensen are seeking reproducibility workflows from social scientists throughout academia. 

Call for Posters and Exhibits | BIDS Spring 2016 Data Science Faire

/ March 31, 2016

This year’s Data Science Faire (May 3) will feature poster/demo exhibits from students and researchers on campus. If you have been doing work related to data science (e.g., conducting a data-intensive project, running an open source meetup on campus, developing tools to enable reproducible science, etc.) and would like to showcase your efforts at the Data Science Faire, we'd love to have you.

With Data, Bigger Might Not Always Be Better

Jasmine Nirody / March 21, 2016

Every conversation I’ve heard about what it means to be a data scientist consists of tons of ideas but no consensus. While it seems like nobody can agree on the sufficient conditions for obtaining this illustrious title, a lot of people are vehement about a necessary one: being a data scientist means you work with big data.

Computational Thinking: I Do Not Think It Means What You Think It Means

Lorena Barba / March 8, 2016

BIDS visiting scholar Lorena Barba posted a great blog post on computational thinking and was kindly willing to let us cross-post on our blog. Check it out below.

The Joy of Code Refactoring

Kyle Barbary / February 29, 2016

If you write software for your research, you have most likely had the experience of looking at your code and realizing it has become a tangled mess. Perhaps it has even gotten to the point where you, the original author, have a hard time remembering how all the pieces fit together. Don’t despair! This is perfectly natural in research software; it is just time to refactor.

Call for Fellows—Spring 2016

Kevin Koy / February 25, 2016

We are excited to invite applications for our next cohort in the BIDS Data Science Fellow Program.  Successful applicants will join our current cohort of fellows in helping make data analysis easier in the research sciences. BIDS data science fellows are postdoctoral scholars, graduate student researchers, or staff with excellent credentials in their fields as well as strong interests in advancing data-analysis approaches with a community of like-minded individuals from across campus. 

Berkeley Lab, UC Berkeley Scientists to Participate in New NASA Space Telescope Project

/ February 19, 2016

BIDS senior fellow and faculty director Saul Perlmutter will lead a team of 29 scientists from 15 institutions for the Department of Energy's space telescope project. The team will "explore mysteries of dark energy, hunt for distant planets, [and] retrace universe's history." Read the full story below.   WFIRST will explore mysteries of dark energy, hunt for distant planets, retrace universe's history during 6-year mission News Release Glenn Roberts Jr. 510-486-5582 

Sociologists Bring a Digital Approach to Text Analysis

/ February 18, 2016

BIDS Data Science Fellow Laura Nelson is featured in this article in Northwester Research News.  For decades, content analysis has relied on a laborious approach of scouring text and manually labeling passages. A new study advanced scholarship by evaluating three types of computer-assisted text analysis techniques, which produced substantively similar results in a fraction of the time. _________

Bringing Data Science Back to Statistics

Kellie Ottoboni / February 16, 2016

One of the sessions that I attended at the 2015 Moore-Sloan Data Science Environment Summit was titled "Isn't Statistics Part of Data Science?" It is a niggling question I often consider, especially given how few statisticians there are at BIDS. A group of about forty people from statistics, computer science, and applied domains convened to discuss differences in practice and culture that divide statistics from data science. I am an applied statistician and a fellow at BIDS straddling these two worlds. I find it difficult to identify the line dividing these roles.