In a new article in PNAS, BIDS Research Scientist Karthik Ram and his co-authors explore the new concept of Hack weeks as a model for data science education and collaboration, and their successes in implementing it as a platform for improving participant engagement in interdisciplinary research.
In this new article in Significance magazine, BIDS Senior Fellow Philip B. Stark and co-author Andrea Saltelli (an adjunct professor in the Centre for the Study of the Sciences and the Humanities at the University of Bergen) comment on the poor practices that result in the failure of scientific results to be reproducible and replicable, and offer an historical account of how these issues may have originated.
Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneouscells. It can be applied to stem cells and their descendants in order to chart the progression from multipotentprogenitors to fully differentiated cells. While a variety of statistical and computational methods have been proposedfor inferring cell lineages, the problem of accurately characterizing multiple branching lineages remains difficultto solve.
Career Paths and Prospects in Academic Data Science: Report of the Moore-Sloan Data Science Environments (MSDSE) Survey
"Instead of arguing about whether results hold up, let’s push to provide enough information for others to repeat the experiments." This article by BIDS Senior Fellow Philip B. Stark appeared in the journal Nature on May 31, 2018.
The Types, Roles, and Practices of Documentation in Data Analytics Open Source Software Libraries; A Collaborative Ethnography of Documentation Work
Data analytics increasingly relies on open source software (OSS) libraries that extend scripted languages like python and R. Software documentation for these libraries is crucial for people across all experience levels, but documentation work raises many challenges, particularly in open source communities. In this collaboration between ethnographers and data scientists, we discuss the types, roles, practices, and motivations around documentation in data analytics OSS libraries.