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 * DATA CARPENTRY

   
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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 organized 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.


CURRICULUM MATERIALS

 * Astronomy curriculum
 * Ecology curriculum
 * Genomics curriculum
 * Geospatial data curriculum
 * Image Processing curriculum
 * Social Sciences curriculum


CURRICULUM MATERIALS UNDER DEVELOPMENT

 * Economics curriculum
 * Other curricula


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

The Carpentries also shares The Carpentries Community Developed Lessons. This
includes The Carpentries Incubator (lessons under development and seeking peer
review), and The CarpentriesLab (lessons that have been vetted by The
Carpentries but are not part of our standard offerings).

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ASTRONOMY CURRICULUM

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

Lesson Site Repository Reference Instructor Notes Maintainer(s) Foundations of
Astronomical Data Science Ralf Kotulla, Rodolfo Montez Jr.

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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.

The Ecology Curriculum Advisory Committee is currently calling for Instructors
to pilot an alternative version of the Data Analysis and Visualization in R for
Ecologists lesson, and provide feedback on their experience. Read the
announcement blog post to learn more about this redesigned lesson and how you
can get involved with testing it.

LESSONS IN ENGLISH

Lesson Site Repository Reference Instructor Notes Maintainer(s) Ecology Workshop
Overview     Fabrice Rwasimitana, Juan Ugalde, Ethan White Data Organization in
Spreadsheets for Ecologists TBD Data Cleaning with OpenRefine for Ecologists
Luis J Villanueva Data Management with SQL for Ecologists James Foster, Adam
Mansur Data Analysis and Visualization in R for Ecologists James Azam, Jay Lee
Data Analysis and Visualization in Python for Ecologists Sarah Pohl, David
Palmquist

LECCIONES EN ESPAÑOL

Lección Sitio web Repositorio Referencia Guía del instructor Mantenedor(es)
Análisis y visualización de datos usando Python (Beta) Irene Ramos Pérez,
Agustina Pesce, Vini Salazar, Heladia Salgado

La plantilla de taller también está disponible en español. Si está interesado en
participar con nuestras lecciones, contáctenos en team@carpentries.org.

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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.

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 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-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

Lesson Site Repository Reference Instructor Notes Maintainer(s) Genomics
Workshop Overview Anuj Guruacharya, Travis Wrightsman Project Organization and
Management for Genomics Heidi Steiner, Jake Szamosi Introduction to the Command
Line for Genomics Valentina Hurtado-McCormick, Paul Smith Data Wrangling and
Processing for Genomics Josh Herr Introduction to Cloud Computing for Genomics
TBD

LESSONS IN DEVELOPMENT

Lesson Site Repository Reference Instructor Notes Maintainer(s) Data Analysis
and Visualization in R *beta* Yuka Takemon, Jason Williams, Naupaka Zimmerman

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GEOSPATIAL DATA CURRICULUM

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 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-Organised
Data Carpentry Geospatial workshops.

LESSONS

Lesson Site Repository Reference Instructor Notes Maintainer(s) Geospatial
Workshop Overview   Introduction to Geospatial Concepts   Marissa Block, Rohit
Goswami, Girmaye Misgna, Aditya Ranganath Introduction to R for Geospatial Data
Johanna Bayer, Mike Mahoney, Alber Sánchez Introduction to Geospatial Raster and
Vector Data with R Ivo Arrey, Drake Asberry

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IMAGE PROCESSING CURRICULUM

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.

LESSONS

Lesson Site Repository Reference Instructor Notes Maintainer(s) Image Processing
with Python Jacob Deppen, Toby Hodges, Kimberly Meechan, Ulf Schiller, Robert
Turner


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 and
accompanying slides 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-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

Lesson Site Repository Reference Instructor Notes Maintainer(s) Social Science
Workshop Overview     Johanna Bayer, Jean Baptiste Fankam Fankam, Jesse Sadler
Data Organization in Spreadsheets for Social Scientists April Moreno, Bernard
Kwame Solodzi Data Cleaning with OpenRefine for Social Scientists Ben Companjen
Data Analysis and Visualization with R for Social Scientists Juan Fung, Jesse
Sadler, Eirini Zormpa

LESSONS IN DEVELOPMENT

Lesson Site Repository Reference Instructor Notes Maintainer(s) Data Analysis
and Visualization with Python for Social Scientists *alpha* Data Management with
SQL for Social Scientists *alpha*

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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. If you are interested in contributing to the development of Data
Carpentry lessons in general, visit the Help Wanted page on the Carpentries
website to find a list of issues in need of attention.


ECONOMICS CURRICULUM

A Data Carpentry curriculum for Economics is being developed by Dr. Miklos Koren
at Central European University. These materials are being piloted locally.
Development for these lessons has been supported by a grant from the Sloan
Foundation/

LESSONS

Lesson Site Repository Reference Instructor Notes Maintainer(s) Introduction to
Stata for Economics Miklós Koren, Arieda Muço, Andras Vereckei Introduction to
the Command Line for Economics Miklós Koren, Arieda Muço, Andras Vereckei


OTHER CURRICULA

If you are interested in developing other lessons, please visit The Carpentries
Incubator.


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:

 * Self-guided Students
 * Instructors


COMMUNITY-CONTRIBUTED MATERIALS


PYTHON FOR ATMOSPHERE AND OCEAN SCIENTISTS

This lesson in The Carpentries Lab has been peer-reviewed and published in JOSE,
and is ready to be taught by any certified Carpentries instructor (some
experience with the netCDF file format and xarray Python library is useful). It
is aimed at learners with some prior experience of Python and the Unix Shell,
who want to learn how to work with with raster or “gridded” data in Python. As a
community-developed lesson, it is currently only available for self-organised
workshops. If you have questions about the lesson, please contact the
Maintainers listed on the lesson README.

 * Python for Atmosphere and Ocean Scientists

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