Data Carpentry Lessons

We facilitate and develop lessons for Data Carpentry workshops. These lessons are distributed under the CC-BY license and are free for re-use or adaptation, with attribution. We’ve had people use the lessons in courses, to build new lessons, or use them for self-guided learning.

Data Carpentry workshops are domain-specific, so that we are teaching researchers the skills most relevant to their domain and using examples from their type of work. Therefore we have several types of workshops and curriculum is organised by domain.

Curriculum Advisors are part of a team that provides the oversight, vision, and leadership for a particular set of lessons. More information about the role of the Curriculum Advisory Committee can be found in the Carpentries Handbook.

Astronomy

The Foundations of Astronomical Data Science curriculum covers a range of core concepts necessary to efficiently study the ever-growing datasets developed in modern astronomy. This curriculum teaches learners to perform database operations (SQL queries, joins, filtering) and to create publication-quality data visualisations. This curriculum assumes some prior knowledge of Python and exposure to the Bash shell, equivalent to that taught in a Software Carpentry workshop.

Lessons

Ecology

This workshop uses a tabular ecology dataset from the Portal Project Teaching Database and teaches data cleaning, management, analysis, and visualization. There are no pre-requisites, and the materials assume no prior knowledge about the tools. We use a single dataset throughout the workshop to model the data management and analysis workflow that a researcher would use.

The Ecology workshop can be taught using R or Python as the base language.

Lessons in English

Lecciones en español

Genomics

The focus of this workshop is on working with genomics data, and data management and analysis for genomics research, including best practices for organisation of bioinformatics projects and data, use of command line utilities, use of command line tools to analyze sequence quality and perform variant calling, and connecting to and using cloud computing.

More information about hosting and teaching a Genomics workshop can be found on our FAQ page.

Interested in teaching these materials? We have an onboarding video and accompanying slides available to prepare Instructors to teach these lessons. After watching this video, please contact [email protected] so that we can record your status as an onboarded Instructor. Instructors who have completed onboarding will be given priority status for teaching at Centrally-Organised Data Carpentry Genomics workshops.

Please note that workshop materials for working with Genomics data in R in “alpha” development. These lessons are available for review and for informal teaching experiences, but are not yet part of The Carpentries’ official lesson offerings.

Lessons

Lessons in Development

Geospatial

This workshop is co-developed with the National Ecological Observatory Network (NEON). It focuses on working with geospatial data - managing and understanding spatial data formats, understanding coordinate reference systems, and working with raster and vector data in R for analysis and visualization.

Join the geospatial curriculum email list to get updates and be involved in conversations about this curriculum.

Interested in teaching these materials? We have an onboarding video and accompanying slides available to prepare Instructors to teach these lessons. After watching this video, please contact [email protected] so that we can record your status as an onboarded Instructor. Instructors who have completed onboarding will be given priority status for teaching at Centrally-Organised Data Carpentry Geospatial workshops.

Image processing

This workshop uses Python and a variety of example images to teach the foundational concepts of image processing, and the skills needed to programmatically extract information from image data. The current version of the curriculum was developed from material originally created by Dr. Tessa Durham Brooks and Dr. Mark Meysenburg at Doane College, Nebraska, USA, with support from an NSF iUSE grant. Further development of the curriculum was supported by a grant from the Sloan Foundation.

Join the image processing curriculum email list and/or the dc-image-processing channel on The Carpentries Slack workspace to get updates and be involved in conversations about this curriculum.

Social Science

This workshop uses a tabular interview dataset from the SAFI Teaching Database and teaches data cleaning, management, analysis and visualization. There are no pre-requisites, and the materials assume no prior knowledge about the tools. We use a single dataset throughout the workshop to model the data management and analysis workflow that a researcher would use.

The Social Sciences workshop can be taught using R as the base language. Interested in teaching these materials? We have an onboarding video and accompanying slides available to prepare Instructors to teach these lessons. After watching this video, please contact [email protected] so that we can record your status as an onboarded Instructor. Instructors who have completed onboarding will be given priority status for teaching at Centrally-Organised Data Carpentry Social Sciences workshops.

Please note that workshop materials for working with Social Science data in Python and SQL are under development.

Lessons

Lessons in development