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 organized by domain.
Workshop materials
Workshop materials under development or consideration
- Digital humanities curriculum
- Image analysis curriculum
- Economics curriculum
- Astronomy curriculum
- Other curriculum
Semester materials
- Biology semester long curriculum
We don’t offer these as a course, but they are freely available for reuse and revision. For more information on these materials, contact team@carpentries.org.
Community-Contributed materials
These are Carpentries style lessons that have been contributed by community members and are not part of Data Carpentry’s official offerings.
Ecology Curriculum
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
| Lección | Sitio web | Repositorio | Referencia | Guía del instructor | Mantenedor(es) |
|---|---|---|---|---|---|
| Análisis y visualización de datos usando Python (Beta) | Paula Andrea Martinez, Heladia Salgado, Rayna Harris |
La plantilla de taller también está disponible en español. Si está interesado en participar con nuestras lecciones, contáctenos en team@carpentries.org.
Genomics Curriculum
The focus of this workshop is on working with genomics data, and data management and analysis for genomics research, including best practices for organization 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.
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
| Lesson | Site | Repository | Reference | Instructor Guide | Maintainer(s) |
|---|---|---|---|---|---|
| Data Analysis and Visualization in R *alpha* | Naupaka Zimmerman, Ahmed Moustafa, Krzysztof Poterlowicz, Jason Williams |
Social Science Curriculum
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 available to prepare Instructors to teach these lessons. After watching this video, please contact team@carpentries.org 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-organized Carpentries workshops.
Please note that workshop materials for working with Social Science data in Python and SQL are under development.
Lessons
Lessons in Development
Geospatial Data Workshop
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 available to prepare Instructors to teach these lessons. After watching this video, please contact team@carpentries.org 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-organized Carpentries workshops.
Lessons
Materials in Early Development
These materials are in early stages of development, and have not yet been incorporated into the official Data Carpentry lesson offerings. If you are interested in being involved in developing one of these lessons, see the information under each lesson description. If you are interested in developing a different curriculum, using The Carpentries lesson templates and pedagogical model, see our Curriculum Development Handbook for information about how to get started.
Digital Humanities Curriculum
Many groups are piloting different versions of this curriculum. There is not yet one set of lessons under active development.
If you are interested in following or being involved in development of this curriculum, please sign up for the dh-curriculum email list
Image analysis Curriculum
With support from an NSF iUSE grant, Dr. Tessa Durham Brooks and Dr. Mark Meysenburg at Doane College, Nebraska, USA have developed a curriculum for teaching image analysis in Python. The materials are available, and are being piloted locally. This pilot phase will be followed by a clean-up phase to incorporate suggestions and feedback from the pilots into the lessons and to make the lessons teachable by the broader community.
If you are interested in contributing to this curriculum, please visit its GitHub repository. For broader discussion about image analysis curriculum development, sign up for the image-analysis-curriculum email list.
Economics Curriculum
A pre-alpha version of a potential Data Carpentry curriculum for Economics is being developed by Dr. Miklos Koren at Central European University. These materials will be piloted in June 2019.
If you are interested in following or being involved in development of this curriculum, please visit the associated GitHub repositories for the Stata and bash shell lessons. For broader discussion about economics curriculum development, sign up for the economics-curriculum email list.
Astronomy Curriculum
Development of a Data Carpentry lesson immediately aimed at astronomy, but which can easily be extended to other physics based disciplines. American Institute of Physics/Member Society Venture Partnership funding is supporting the development and testing of the lesson. Lesson development will begin the AAS hack day and will continue throughout the next two years. If you are interested in contributing in any way, please join the astronomy-curriculum email list. We would especially like to encourage anyone who is part of an AIP member society (Acoustical Society of America, American Association of Physicists in Medicine, American Association of Physics Teachers, American Astronomical Society, American Crystallographic Association, American Meteorological Society, American Physics Society, AVS: Science & Technology of Materials, Interfaces, and Processing, The Optical Society, and the Society of Rheology) to join as we are eager to develop lessons that can be easily extended into these sub-fields.
Other curriculum
If you are interested in developing other lessons or getting updates on other topics, see the lessons ideas github repository for topics under consideration or discussion, or to propose new ideas.
Semester materials
Biology Semester-long Course
The Biology Semester-long Course was developed and piloted at the University of Florida in Fall 2015. Course materials include readings, lectures, exercises, and assignments that expand on the material presented at workshops focusing on SQL and R. The course is accessible to:
Community-contributed materials
Python for Atmosphere and Ocean Scientists
This lesson is currently in the alpha stage. To move it to the beta stage, we are looking for feedback from people interested to teach this material. If you’re a qualified Carpentries instructor and would be interested in teaching the lessons (some experience with the netCDF file format and xarray Python library is useful), please get in touch with either Damien Irving or Francois Michonneau. You can also request a workshop at your institution by contacting us and we’ll reach out to instructors. There is no fee for a pilot workshop, but you would need to cover travel expenses for instructors.