JOSE, pronounced [hoe-zay], is a sibling journal to the Journal of Open Source Software (JOSS), which publishes open-source research software. JOSE relies on the journal management infrastructure and tools developed for JOSS.
JOSE publishes two types of articles that describe:
- open-source educational materials
- open-source educational software tools
Why is this journal needed?
Currently, academia lacks a mechanism for crediting efforts to develop software for assisting teaching and learning or open-source educational content and materials. As a result, beyond personal motivation, there is little incentive to develop and share such material.
The Journal of Open Source Education (JOSE) is a scholarly journal with a formal peer review process designed to improve the quality of the software or content submitted. Upon acceptance into JOSE, a CrossRef DOI is minted and we list your paper on the JOSE website.
Who is behind this journal?
This is an initiative led directly by the Editorial Board on a purely volunteer basis. There is no publisher seeking revenue through the journal. JOSE runs on the efforts of the editors, authors, and reviewers, to communicate scholarly work to the open-source community without intermediaries.
What do you mean by "open-source educational materials"?
"Open-source" implies that there are source files that are converted and rendered into a final learner-presentable form. Examples include Jupyter notebooks or plaintext/markup language documents like LaTeX, Markdown, ReStructuredText, AsciiDoc, and R Markdown. These documents should contain the lesson content and be designed to be reusable by other instructors. Lastly, the course content should make use of computation for learning with embedded or associated code snippets/programs.
We do not mean openly available slides, lecture notes, or YouTube videos, though these may be acceptable as supplementary materials. In addition, course syllabi by themselves are not suitable for submission (Syllabus may be more appropriate).
tl;dr: your course or lesson content must contain or use code to teach. We are not focused exclusively on learning to code, but coding to learn.
What do you mean by "educational software tools"?
Open-source software that serves as educational technology; examples include (but are not limited to) alternatives to learning management systems, autograders, cloud systems for lesson delivery, student collaboration tools. For these tools, peer review will follow a similar process as JOSS.
Scope & submission requirements
We consider submissions from all areas of academia, although our computational focus may result in more natural submissions from STEM fields—but all are welcome!
Submissions must be "feature complete" to the extent that another educator could adopt, reuse, and/or extend for their purposes.
The ideal submission size is a course module, although entire courses are also acceptable.
JOSE submissions must:
- JOSE submissions must be fully open, under the Open Definition. This means that any text content or graphical objects should be under a Creative Commons license (ideally CC-BY) and code components should be under an OSI-approved license.
- Computational learning modules should be complete and immediately usable for self-learning or adoption by other instructors. They should make a clear contribution to teaching and learning of any subject, supported by computing. JOSE is not focused in OER for "learning to code" as much as "coding to learn."
- Software submissions should make a clear contribution to the available open-source software that supports teaching and learning, or makes an educational process better (e.g., faster, easier, simpler). Examples include software to auto-grade student work, learning management systems, and student collaboration frameworks. Software should be feature-complete (no half-baked solutions).
Authors wishing to make a pre-submission enquiry should open an issue on the JOSE repository.
Editorial Board
Lorena Barba (@labarba)
Professor of Mechanical and Aerospace Engineering at the George Washington University, leading a research group in computational fluid dynamics, computational physics and high-performance computing. Past member of the Board (2014-2021) for NumFOCUS, a non-profit in support of open-source scientific software.
Jordan Gorzalski (@jgorzalski)
Design assistant at the University of Michigan and former Library as Research Lab Design Fellow working on projects related to digitization of cultural heritage materials and education (Dig4E). He is also an adjunct librarian at Oakland Community College.
Topic Editors
Yanina Bellini Saibene (@yabellini)
rOpenSci Community Manager. R-Ladies Project Lead. Assistant Professor at Universidad Nacional Guillermo Brown (Argentina). Co-founder of MetaDocencia and LatinR. Member, The Carpentries Executive Council, R Consortium Infrastructure Steering Committee, and Sociedad Argentina de Informática (SADIO). Instructor and trainer for The Carpentries and RStudio Certified Instructor. INTA 's Researcher (since 1998; on leave). Former MetaDocencia Core Team (2020-2022) and RForwards Core Team (2021-2022). She teaches and develops open educational materials about R, remote sensing, and data science. She participates in and leads several translations effort of educational material, including the book Teaching Tech Together, The Carpentries' lessons, and the book R for Data Science.
Alejandro Coca-Castro (@acocac)
Postdoctoral Research Associate at The Alan Turing Institute. His research focuses on modeling earth systems and environmental phenomena using artificial intelligence and data science. He contributes to open science education through software, tutorials, content and events in multiple global community-driven initiatives including the Turing Way (core member), Open Life Science (mentee/mentor) and Pangeo (member). He is also the lead of the Environmental Data Science Book, a computational notebook community promoting open source software, reproducibility and collaborative research in Environmental science.
Renata Diaz (@diazrenata)
Renata is a postdoctoral researcher at the School of Biology and Ecology at the University of Maine. She uses data- and- computationally-intensive methods to study biodiversity change across levels of organization. She develops R packages and teaching materials to help researchers and students develop computational skills and implement new theories and statistical approaches in ecology and evolution. Previously, she completed her PhD in Interdisciplinary Ecology at the University of Florida.
Shannon Ellis (@ShanEllis)
Assistant Teaching Professor in the Department of Cognitive Science and The Halıcıoğlu Data Science Instituteat The University of California San Diego. She develops curriculum and teaches undergraduate courses in programming (Python, R), data science, and genetics, with a particular focus on responsible and ethical approaches to data analysis. Co-author of Tidyverse Skills for Data Science in R (book and course sequence) and Cloud-Based Data Science (course sequence).
Ashlee N. Ford Versypt (@ashleefv)
Associate professor in the Dept. of Chemical & Biological Engineering at the University at Buffalo, The State University of New York. Her research focuses on mathematical modeling for diseases and pharmaceutical treatments. Her teaching interests blend computational science, kinetics, transport, and applied mathematics for engineering education.
Tyler George (@stats-tgeorge)
Assistant Professor of Statistics at Cornell College. He teaches undergraduate courses and collaborates with students on summer research in statistics and data science. His courses use collaborative learning and emphasize communication, reproducibility, and ethics, by integrating them throughout a class. He has started contributing to open source education by utilizing, maintaining, and collaborating, on existing resources, and creating introductory statistics materials.
Allison Horst (@allisonhorst)
Assistant Teaching Professor at the Bren School of Environmental Science and Management, UC Santa Barbara. She teaches math, environmental data science, and statistics courses in R, emphasizing tools and best practices for reproducibility and collaboration. She contributes to open source education through software, open online tutorials and courses, and a library of original artwork for use in data science teaching materials.
Juan Klopper (@juanklopper)
Research Fellow at the School of Data Science and Computational Thinking at the University of Stellenbosch. Attending surgeon at Groote Schuur Hospital, was Head of Postgradute Surgical Research. and Head of Surgical Education in the Department of Surgery at The University of Cape Town. He served as the Health Sciences Faculty member on the University Senate Committee on online education. His research and educational passions include machine learning and data science, open science, open source software, and open educational resource development.
Stefani Langehennig (@steflangehennig)
Stefani is an Assistant Professor of the Practice in the Business Information & Analytics Department at the University of Denver's Daniels College of Business, where she is also the co-director of the Center for Analytics and Innovation with Data (CAID). She teaches courses on Python programming, data mining and visualization, frequentist statistics, and project management. A political scientist by training, Stefani has worked as a data scientist in a public policy consulting firm in London, as well as a teacher in the Texas public school system. She is currently developing an open source textbook on survey methodologies in R for social scientists.
Andrew McCluskey (@arm61)
Instrument Data Scientist at the European Spallation Source. He is passionate about teaching physical scientists programming and data handling skills. He previously held a Visiting Lectureship at the University of Bath where he taught Python for chemistry. Now, he focuses on training users of ESS to reduce and analyse data.
Erin McKiernan (@emckiernan)
Erin McKiernan is a professor in the Department of Physics, Biomedical Physics Program at the National Autonomous University of Mexico, specializing in experimental and theoretical neuroscience and cellular biophysics. She teaches several courses, including biochemistry, cellular and molecular biology, and human physiology. She is currently developing electrophysiology laboratory practicals as open educational resources.
Lorena Mesa (@lorenanicole)
Political scientist turned coder, Lorena Mesa is a GitHub data engineer, Director & Chair of the Python Software Foundation, and University of Chicago lecturer. While at Obama for America and as a graduate researcher, she learned how to transform messy, incomplete data into intelligible analysis on topics like predicting Latinx voter behavior. It's this unique background in research and applied mathematics that drove Lorena to pursue a career in engineering and data science. One part activist, one part Star Wars fanatic, and another part Trekkie, Lorena abides by the motto to "live long and prosper".
Jason Moore (@moorepants)
Jason K. Moore is an assistant professor of BioMechanical Engineering at Delft University of Technology, where he leads the Bicycle Lab and teaches multibody dynamics and engineering computation. He is active in the Scientific Python community where he is a core developer of the SymPy and PyDy projects.
Kyle Niemeyer (@kyleniemeyer)
Mechanical engineer in the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University. Computational researcher in combustion, fluid dynamics, and chemical kinetics, with an interest in numerical methods and GPU computing strategies.
Shannon Quinn (@magsol)
Assistant Professor at the University of Georgia, jointly appointed in the Departments of Computer Science and Cellular Biology. His research focuses on modeling diseases at the cellular level using a variety of imaging and machine learning techniques. He also advocates for best practices in open and reproducible research and education.
Charles Severance (@csev)
Clinical Associate Professor in the School of Information at the University of Michigan. He also works on developing standards for teaching and learning technology. Previously, he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project. He has written several books including Using the Google App Engine, Python for Informatics, High Performance Computing, and Sakai: Free as in Freedom.
Karen Smith (@kls2177)
Assistant Professor, Teaching Stream in the Department of Physical and Environmental Sciences at the University of Toronto Scarborough. She teaches climate science and modeling and environmental data analysis through the development and use of a variety of open-source educational tools, labs and workshops.
Tiffany Timbers (@ttimbers)
Assistant Professor of Teaching in the Department of Statistics and Co-Director for the Master of Data Science program (Vancouver Option) at the University of British Columbia. She develops curriculum and teaches on responsible application of data science, collaborative software development and creating R and Python packages using modern tools and workflows. Co-author of two open textbooks: Data Science: A First Introduction and Python Packages.
Jason J. Williams (@JasonJWilliamsNY)
Assistant Director of External Collaborations at Cold Spring Harbor Laboratory’s DNA Learning Center. He has been the Education, Outreach, and Training lead for CyVerse (a US national life science cyberinfrastructure funded by NSF), and he organizes, instructs, and speaks at a variety of bioinformatics-related events. He is an active Carpentries instructor, and a former Chair of the Software Carpentry foundation (an international organization of researchers that promotes training and education in software development, scientific data management, and open science).
Editors Emeritus
Ian Hawke (@IanHawke)
Kathryn Huff (@katyhuff)
Robert Talbert
Tracy Teal
Rachel Thomas (@racheltho)
Bryan Weber (@bryanwweber)
Carol Willing (@willingc)
Contact JOSE
To suggest a feature, report a bug, or enquire about a possible submission in JOSE, please open a GitHub Issue.
Code of Conduct
Although spaces may feel informal at times, we want to remind authors and reviewers (and anyone else) that this is a professional space. As such, the JOSE community adheres to a code of conduct adapted from the Contributor Covenant code of conduct.
Authors and reviewers will be required to confirm they have read our code of conduct, and are expected to adhere to it in all JOSE spaces and associated interactions.
Ethics Guidelines
We also want to remind authors and reviewers (and anyone else) that we expect and require ethical behavior. Some examples are:
- All authors are obliged to provide retractions or corrections of any mistakes of which they become aware.
- Plagiarism (e.g., violation of another author's copyright), for both software and papers, is not allowed.
- Self-plagiarism (repeated publication of the same work) is not allowed.
- Author lists must be correct and complete. All listed authors must have made a contribution to the work, and all significant contributors should be included in the author list.
- Reviews should be accurate and non-fraudulent. Examples of concerns are: Authors should not suggest reviewers who are not real people or have conflicts. Reviewers and editors must disclose conflicts. Bribes for authors, reviewers, editors are not permitted.
Any potentially unethical behavior should be brought to the attention of the JOSE staff. See Contacting JOSE.
The JOSE Editors will track any concerns and respond to the submitter with a resolution, which will range from doing nothing if the editors disagree about the issue to withdrawing papers and notifying authors' institutions.
JOSE Publication Ethics and Malpractice Statement
Editorial Board- The JOSE editorial board's members are recognized experts in the field. The full names and affiliations of the members are provided on the journal’s website (see editorial board). The individual editors' contact information are provided on that site, via their GitHub pages, and general contact information for the editorial office also on the journal’s website.
- JOSE does not charge any fees for manuscript processing and/or publishing materials, as is stated on the journal's website.
- Authors are obliged to participate in peer review process, as described in submission guidelines.
- All authors have significantly contributed to the research. The submitting author is required to be a major contributor to the software they are submitting and the review process includes a check that ‘the full list of paper authors seems appropriate and complete?’.
- All authors are obliged to provide retractions or corrections of mistakes (see ethics and what should my paper contain?).
- JOSE papers are required to have a list of references, and financial support.
- Forbidden to publish same research in more than one journal (see ethics).
- All of JOSE's content is subjected to peer-review (see about and docs).
- JOSE peer-review is defined as obtaining advice on individual manuscripts from reviewers expert in the field. This advice is public, and is given to both the editor(s) and the author(s), with the aim of pointing out issues the reviewers believe are insufficiently addressed for publication.
- The JOSE review process is clearly described on the journal’s website.
- Judgments should be objective.
- JOSE reviewers should ideally have no conflict of interest. In practice, this is not always possible. If a reviewer has a conflict of interest, it must be declared and recorded, and the editors may choose to waive it if this is in the best interest of the review process.
- Reviewers should point out relevant published work which is not yet cited.
- JOSE reviews are public and non-anonymous while in progress and post-review, as they take place via GitHub issues in a public repository.
- All authors are obliged to provide retractions or corrections of any mistakes of which they become aware.
- Plagiarism (e.g., violation of another author's copyright), for both software and papers, is not allowed.
- Self-plagiarism (repeated publication of the same work) is not allowed.
- Author lists must be correct and complete. All listed authors must have made a contribution to the work, and all significant contributors should be included in the author list.
- Reviews should be accurate and non-fraudulent. Examples of concerns are: Authors should not suggest reviewers who are not real people or have conflicts. Reviewers and editors must disclose conflicts. Bribes for authors, reviewers, editors are not permitted.
- JOSE copyright and licensing information is clearly described on the journal’s website.
- The journal and all individual articles are freely available to all readers.
- JOSE articles, metadata, and reviews are archived with Portico.
- Information about the ownership and/or management of a journal is clearly indicated on the journal’s website (see http://www.theoj.org).
- JOSE and the Open Journals do not use organizational names that would mislead potential authors and editors about the nature of the journal’s owner.
- The JOSE website (see https://jose.theoj.org and https://jose.theoj.org/about), including the text that it contains, demonstrates that care has been taken to ensure high ethical and professional standards.
- JOSE immediately publishes accepted articles; it is not a serial publication.
- As far as we know, the journal name (Journal of Open Source Education (JOSE)) is unique and not one that is easily confused with another journal or that might mislead potential authors and readers about the journal’s origin or association with other journals.
Cost and Sustainability Model
Journal of Open Source Education is an open access journal committed to running at minimal costs, with zero publication fees (article processing charges) or subscription fees.
Under the NumFOCUS nonprofit umbrella, JOSE is now eligible to seek grants for sustaining its future. With an entirely volunteer team, JOSE is seeking to sustain its operations via donations and grants, keeping its low cost of operation and free service for authors.
In the spirit of transparency, below is an outline of our current running costs:
- Annual Crossref membership: $275 / year
- Annual Portico membership: $250 / year
- JOSE paper DOIs: $1 / accepted paper
- JOSE website hosting (Heroku): $19 / month
Assuming a publication rate of 200 papers per year this works out at ~$4.75 per paper ((19*12) + 200 + 275 + 250) / 200.
A more detailed analysis of our running costs is available on our blog.
Content Licensing & Open Access
JOSE is a diamond/platinum open access journal. Copyright of JOSE papers is retained by submitting authors and accepted papers are subject to a Creative Commons Attribution 4.0 International License.
Any code snippets included in JOSE papers are subject to the MIT license regardless of the license of the submitted software package under review.
