About us

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Our mission is to provide researchers high-quality, domain-specific training covering the full lifecycle of data-driven research. The target audience of Data Carpentry is researchers who want to start working with large volumes of data in their projects.

The volume and complexity of data has grown rapidly in every research domain in recent years, and skills for organising, handling, and analysing data have become essential. Data allows us to ask questions that previously could not have been answered, and it changes the impact that science has on society. Although petabytes of data are now available, most scientific disciplines are failing to translate this sea of data into scientific advances. The missing step between data collection and research progress is a lack of training for researchers in crucial skills for effectively managing and analysing large amounts of data.

Data Carpentry has been addressing this gap since 2014 by teaching researchers the fundamental data skills they need to conduct their work. We teach hands-on workshops in data organisation, management, and analysis to increase data literacy and improve research efficiency. Most of our workshops are aimed at learners with little or no previous experience with computational research methods. We create a friendly environment for learning, to empower researchers and enable data driven discovery.

Our domain-specific approach allows us to tailor the data, content, and tools to reflect the specific data and analysis needs of different areas. Domain specificity also allows us to build new skills on knowledge frameworks familiar to learners, and to motivate workshops using real scientific questions and data relevant to the learners’ field of study. This approach allows learners to see immediate value in the skills they are learning and to put new techniques immediately into practice.

A workshop can’t teach a researcher everything they need to know about data management and analysis, however it drastically reduces the barrier to entry and imparts the skills for continued learning and engagement. Our ultimate goal is to enable data-driven research in diverse disciplines by creating strong communities of data scientists and empowering them to conduct more innovative and effective research.