Often modern science researchers find themselves lacking in the relatively new computational skills needed to conduct data-driven research. Researchers trained as neuroscientists, ecologists, astronomers and nuclear physicists don’t often learn the data handling skills required for managing the large volumes of data now available. The Moore Foundation-supported Data Carpentry project, part of our Data-Driven Discovery Initiative, is working to remedy this situation.
The Data Carpentry project is an effort to provide researchers with domain-specific skills for conducting data-driven research via hands-on workshops in data organization, management, and analysis. The first year of funding from the foundation has just ended, and the group has exceeded expectations for the number of researchers trained, the number of workshops conducted and the number of domain-specific curricula developed. You can read their full report here.
One of the many undertakings in the organization’s first year was to determine how best to assess their progress towards goals. They hired an assessment coordinator, Dr. Kari Jordan, who produced a Data Carpentry Assessment Report in October (read more here). This report detailed Jordan’s analysis of participant surveys conducted pre- and post- workshop. The results point to the overall success of the project in helping researchers better cope with big data in their daily work. Here are some highlights:
- 95% of those surveyed would recommend a workshop to a colleague
- 92% agreed that the workshop was worth their time
- 92% learned some (36%) or a great deal (56%) of practical knowledge
The Data-Driven Discovery team is thrilled with the progress of Data Carpentry thus far. Their efforts are contributing to our “practices” strategy, which focuses on creation, transfer and dissemination of readily usable innovative tools, knowledge and techniques for engaging in data-driven scientific research.