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).
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. Jupyter Distinguished Contributor 2020.
Topic Editors
Ellen Bledsoe (@bleds22e)
Associate Professor of Practice in the University of Arizona’s School of Natural Resources and the Environment. Trained as a community ecologist, she teaches courses in the department with data science components, often introducing students to computer programming in R for the first time. She both utilizes and creates open-educational resources for her courses, which range from general education courses in data literacy to graduate level courses in scientific reproducibility; she has also been a member of the BEDE Network steering committee since 2019.
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.
Shannon Ellis (@ShanEllis)
Associate Teaching Professor in the Department of Cognitive Science and The Halıcıoğlu Data Science Institute at 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.
Nicolas Guarin-Zapata (@nicoguaro)
Assistant Professor, Universidad EAFIT, Medellin, Colombia. BSc in Physics Engineering, MSc in Engineering and PhD in Computational Engineering. Research interests and experience in simulation-based engineering, numerical methods, biomimetics, mechanics of solids, design of materials, and wave propagation.
Juan Klopper (@juanklopper)
Associate Professor in the Department of Biostatistics and Bioinformatics in the Milken Institute School of Public Health at The George Washington University, Washington DC. Previously, was a Research Fellow at the School of Data Science and Computational Thinking at the University of Stellenbosch, attending surgeon at Groote Schuur Hospital, 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)
Lecturer in Chemistry at the University of Bristol. 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 and worked at the European Spallation Source. Now, he leads the SCAMs@bristol research group, focusing on physics-informed modelling and analysis.
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.
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.
Nicolas Rougier (@rougier)
Research director at Inria, working at the Institute of Neurodegenerative Diseases in Bordeaux (France), leading the computational neuroscience group, strongly committed to open science and reproducible science. He has extensive experience in computational modelling, software engineering (Python) and data visualization.
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.
Ethan White (@ethanwhite)
Professor of Wildlife Ecology and Conservation and member of the UF Artificial Intelligence and Informatics Research Institute at the University of Florida. He leads a research group studying data-intensive problems in ecology including ecological forecasting and using remote sensing to monitor and understand forests and wildlife at large scales. He develops open educational resources and teaches courses in R for environmental scientists and ecological forecasting. He has served on the boards/steering committees of OurResearch (2014-present), EarthLife Consortium (2018-2025), Ecological Forecasting Initiative (2018-2021), Biology and Environmental Data Education Network (2018-2020), The Carpentries (2018-2019), and Data Carpentry(2014-2017).
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
Yanina Bellini Saibene, Jordan Gorzalski, Ian Hawke, Allison Horst, Kathryn Huff, Jason Moore, Kyle Niemeyer, Robert Talbert, Tracy Teal, Rachel Thomas, Bryan Weber, Carol Willing
Contact JOSE
If you need to contact JOSE privately then you can email us.
You can also find JOSE at Twitter
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 (see conflict of interest policy for details). Reviewers and editors must disclose conflicts. Bribes for authors, reviewers, editors are not permitted.
Allegations of research misconduct associated with a JOSE submission (either during review, or post-publication) are handled by the Open Journals ethics team. Reports should be sent privately to our editorial team at which point the report will be triaged by the Open Journals ethics officer to determine the nature and severity of the case. Options available to the Open Journals ethics officer range from recommending no action to instigating a full investigation by the Open Journals ethics team which may result in researchers' institutions and funders being notified and the JOSE being retracted.
Although JOSE is not yet a member of COPE (application pending), our processes are modeled on the COPE guideline procedures for ethics complaints.
Complaints processComplaints about the conduct or decision making of the JOSE editorial team can be sent to the Open Journals governance team.
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.
- Minor fixes are processed by the Editors in Chief (EiCs), and are publicly handled based on requests from the original authors (managed in the GitHub review linked from the paper).
- Major corrections will be reviewed by the EiC and ethics team. If accepted, the paper will be re-published with an editorial note on the GitHub review (linked from the paper page).
- Retractions: EiC team and the ethics team review. If we deem that a retraction is warranted, we will update the paper and leave a retraction notice (see an example retraction for the linked paper)
- 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.
