What exactly do you mean by 'journal'
The Journal of Open Source Software (JOSS) is an academic journal (ISSN 2475-9066) with a formal peer review process that is designed to improve the quality of the software submitted. Upon acceptance into JOSS, a Crossref DOI is minted and we list your paper on the JOSS website.
Don't we have enough journals already?
Perhaps, and in a perfect world we'd rather papers about software weren't necessary but we recognize that for most researchers, papers and not software are the currency of academic research and that citations are required for a good career.
We built this journal because we believe that after you've done the hard work of writing great software, it shouldn't take weeks and months to write a paper about your work.
You said developer friendly, what do you mean?
We have a simple submission workflow and extensive documentation to help you prepare your submission. If your software is already well documented then paper preparation should take no more than an hour.
You can read more about our motivations to build JOSS in our announcement blog post.
Scope & submission requirements
Not all software is eligible to be published in JOSS.
JOSS publishes articles about research software. This definition includes software that: solves complex modeling problems in a scientific context (physics, mathematics, biology, medicine, social science, neuroscience, engineering); supports the functioning of research instruments or the execution of research experiments; extracts knowledge from large data sets; offers a mathematical library; or similar.
JOSS submissions must:
- Be open source (i.e., have an OSD-compliant license).
- Have an obvious research application.
- Be feature-complete (no half-baked solutions) and be designed for maintainable extension (not one-off modifications).
- Not be minor 'utility' packages, such as 'thin' API clients.
Authors wishing to make a pre-submission enquiry can email us or open an issue.
Editorial Board
Lorena A 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. Member of the Board of Directors for NumFOCUS, a non-profit in support of open-source scientific software.
Daniel S. Katz (@danielskatz)
Works on computer, computational, and data research at NCSA, CS, ECE, and the iSchool at the University of Illinois at Urbana-Champaign, and has a strong interest in studying common elements of how research is done by people using software and data.
Kevin M. Moerman (@Kevin-Mattheus-Moerman)
Lecturer Biomedical Engineering, College of Engineering & Informatics NUI Galway, Research Affiliate MIT Media lab, Senior Member IEEE, Developer for the GIBBON computational biomechanics project.
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.
Arfon Smith (@arfon)
A lapsed academic with a passion for new models of scientific collaboration, he's used big telescopes to study dust in space, built sequencing pipelines in Cambridge, engaged millions of people in online citizen science by co-founding the Zooniverse, and led science at GitHub. These days he's running the Data Science Mission Office at STScI in Baltimore, the science operations center for the Hubble Space Telescope, James Webb Space Telescope, Kepler, TESS, and more.
Kristen Thyng (@kthyng)
Physical oceanographer at Texas A&M University. Researches coastal ocean dynamics, transport of material in the ocean, and tidal turbines as a renewable energy source.
Topic Editors
Tania Allard (@trallard)
Research Software Engineer and data engineer, contributor and maintainer of a number of open source projects, mentor and community builder. She is particularly interested in reproducibility, sustainability, openness and FAIR principles in research software and data as well as bias an ethics in data science.
Katy Barnhart (@kbarnhart)
Research scientist in Earth surface dynamics at the University of Colorado Department of Geological Sciences and Cooperative Institute for Research in Environmental Sciences. Her research focuses on integrating observations, model development, and model analysis to understand the evolution of the Earth's surface. She is a core developer of the Landlab toolkit.
Juanjo Bazán (@xuanxu)
Astrophysics researcher at CIEMAT, mathematician and software engineer currently developing chemical evolution models for galaxies. Juanjo has worked as advisor on open source policies and contributed code to many popular libraries like Rails or Astropy. He is member of the founder team of Consul, the more widely used open sourced citizen participation software.
Monica Bobra (@mbobra)
Research scientist at Stanford University in the W. W. Hansen Experimental Physics Laboratory who studies the Sun and space weather as a member of the NASA Solar Dynamics Observatory science team and contributes to Heliopython and SunPy.
Jed Brown (@jedbrown)
Assistant Professor of Computer Science at the University of Colorado Boulder leading a research group developing scalable algorithms and sustainable software for prediction, inference, and design via high-fidelity and multiscale physically-based models. He is a core developer of PETSc.
Dan Foreman-Mackey (@dfm)
Dan Foreman-Mackey is an Associate Research Scientist at the Flatiron Institute in the Center for Computational Astrophysics. His research program focuses on the development and application of probabilistic data analysis techniques to make novel discoveries and solve fundamental problems in astrophysics.
Olivia Guest (@oliviaguest)
Olivia Guest is a computational modeler in cognitive science and neuroscience. She creates and evaluates computational accounts for categorization and conceptual representation in healthy adults, patient groups, infants, and animals. She is also interested in using computational modeling and data science broadly in theoretical as well as applied contexts.
Alex Hanna (@alexhanna)
Alex Hanna is a computational social scientist working on machine learning curriculum at Google. She received her PhD in sociology from the University of Wisconsin-Madison. Her research has focused on how new and social media has changed social movement mobilization and political participation. More recently, she has been interested in issues of fairness, accountability, and transparency in sociotechnical systems.
Kathryn Huff (@katyhuff)
Kathryn Huff is an Assistant Professor in Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign. Her research focuses on modeling and simulation of advanced nuclear reactors and fuel cycles. She also advocates for best practices in open, reproducible scientific computing.
Mark A. Jensen (@majensen)
Director of Data Management and Interoperability at the Frederick National Laboratory for Cancer Research, he leads efforts to design, build and maintain scientist-friendly research data systems that integrate clinical and multiomic data across thousands of cancer patient-donors. He is active in open source software development and a supporter of the FAIR (Findable, Accessible, Interoperable, Reusable) movement in scientific data management. A molecular evolutionary biologist by training, he served as an Associate Editor for the Journal of Molecular Evolution from 2008-2013.
Anisha Keshavan (@akeshavan)
Anisha Keshavan was trained in Bioengineering (PhD, UC-Berkeley & UCSF, 2017), data science, and neuroengineering (Postdoc, University of Washington eScience Institute and Institute for Neuroengineering, 2017-2019). She is now a data scientist at Octave Biosciences, where she designs data science methods to improve treatment of neurodegenerative diseases. She is passionate about open, collaborative science and data visualization.
Vincent Knight (@drvinceknight)
Vince is a mathematician at Cardiff University. He is a maintainer and contributor to a number of open source software packages and a contributor to the UK python community. His research interests are in the field of game theory and stochastic processes and also has a keen interest in pedagogy. Vince is a fellow of the Software Sustainability Institute and is interested in reproducibility and sustainability of scientific/mathematical research.
Christopher R. Madan (@cMadan)
Assistant Professor in the School of Psychology at the University of Nottingham. Studying human memory and decision making using cognitive psychology and neuroimaging approaches, and developing novel computational methods along the way.
Melissa Weber Mendonça (@melissawm)
Applied mathematician, working with numerical optimization and numerical linear algebra at the Federal University of Santa Catarina, in Brazil. Interested in open science, open research, and teaching practices in mathematics and computer science.
Lorena Pantano (@lpantano)
Research scientist at Harvard T.H. Chan School of Public Health. She is focused on genomic regulation and data integration, and has 12 years of experience in biological data analysis and contributing to novel algorithms to improve the quantification and visualization of genomic data.
Stefan Pfenninger (@sjpfenninger)
Interdisciplinary researcher in renewable energy and environmental science. My group's research is on the global transition to a 100% clean and renewable energy system, and the technical, economic and policy barriers on the way to that goal. We develop software like Calliopeto help us do so.
Viviane Pons (@VivianePons)
Associate professor at Université Paris-Sud. Mathematician, computer scientist and strong defender of open-source and open science in general. Contributor and user of the SageMath software. Member of the OpenDreamKit European project for open-source development in Mathematics.
Jack Poulson (@poulson)
Independent computational scientist running Tech Inquiry and Hodge Star Scientific Computing. Previously, research scientist at Google and assistant professor of mathematics at Stanford. His research interests: software engineering of high-performance mathematical libraries (e.g., conic optimization, lattice reduction, determinantal point processes, numerical PDEs), their connections to pure mathematics (e.g., differential geometry, conic analysis, representation theory).
Karthik Ram (@karthik)
A quantitative ecologist and data scientist at UC Berkeley' Institute for Data Science, his research focuses on food web dynamics, open science, open data, and reproducible research.
Marie E. Rognes (@meg-simula)
Marie E. Rognes is Chief Research Scientist at Simula Research Laboratory, Oslo, Norway. Her research focuses on numerical methods for partial differential equations, software for scientific computing, with applications in biomechanics and neuroscience. She is a core member of the FEniCS and Dolfin-adjoint Projects.
Ariel Rokem (@arokem)
Trained in cognitive neuroscience (PhD: UC Berkeley, 2010) and computational neuroimaging (Postdoc, Stanford, 2011-2015), Ariel Rokem is now a data scientist at the University of Washington eScience Institute, where he continues to develop software for the analysis of human neuroimaging data, develops tools for reproducible and open research practices, and collaborates with researchers from a variety of fields to advance data-intensive research.
William Rowe (@will-rowe)
Bioinformatician working at the University of Birmingham, UK. Research areas include data sketching for genomics, variation graphs and metagenome profiling. Currently working on long-read sequencing applications for real-time genomic epidemiology.
Charlotte Soneson (@csoneson)
Research Associate at the Friedrich Miescher Institute for Biomedical Research in Basel, Switzerland, with a research background mainly in development and evaluation of analysis methods for transcriptomics data. Developer and maintainer of several open-source R packages for analysis, quality assessment and interactive visualization of high-throughput biological data.
Matthew Sottile (@mjsottile)
Research scientist working on program synthesis tools for high performance computing at Noddle.io, and adjunct faculty at the Washington State University Department of Mathematics and Statistics. His PhD work in computer engineering focused on measurement and analysis methods for performance analysis of high performance systems. He believes that open and reproducible research software artifacts are critical to the advancement of computational science.
Yuan Tang (@terrytangyuan)
Senior software engineer at Ant Financial, building AI infrastructure and AutoML platform. He's a committer of TensorFlow, XGBoost, and Apache MXNet, maintainer of several Kubeflow projects, and author of numerous open source software projects. He's also the author of the best-selling book TensorFlow in Practice which is the first book teaching TensorFlow in Chinese and has been translated to several other languages such as traditional Chinese and Korean.
George K. Thiruvathukal (@gkthiruvathukal)
Professor of computer science at Loyola University, Chicago, and visiting faculty at the Argonne National Laboratory Leadership Computing Facility. Research interests: high-performance & distributed computing, cyber-physical systems, software engineering, programming languages and systems, history of computing, computational and data science, computing education, and ethical/legal/social issues in computing. Past editor-in-chief of IEEE Computing in Science and Engineering.
Leonardo Uieda (@leouieda)
Geophysicist researching methods for determining the inner structure of the Earth from geophysical observations, mainly disturbances in the Earth's gravity and magnetic fields. Developer of open-source software for processing, modeling, and visualizing geophysical data. Currently Visiting Research Scholar at the University of Hawai'i at Mānoa working on the Generic Mapping Tools.
Marcos Vital (@marcosvital)
Biologist, quantitative ecologist and open science enthusiast at Universidade Federal de Alagoas, Brazil, where he coordinates the Quantitative Ecology Lab. He is interested in a wide range of topics related to evolutionary ecology and conservation biology, but also in other fields such as active learning methods and digital games in education.
Editors Emeritus
Jason Clark (@jasonclark)
Associate Professor, Librarian, and Head of Archival Informatics and Special Collections at Montana State University (MSU) Library, specializing in software development, metadata and data modeling, linked and structured data, search engine optimization, and interface design. You can find him on ORCID at http://orcid.org/0000-0002-3588-6257 and as @jaclark on Twitter.
George Githinji (@george-githinji)
Bioinformatician and researcher at the KEMRI-Wellcome Trust Research Programme one of the Major Wellcome-Trust Overseas Programmes. George works with the Virus Epidemiology and Control group and develops bioinformatics methods for understanding virus transmission patterns and evolution. He undertook his education in Kenya and is one of East-Africa's open source software developers with an keen interest in bioinformatics and reproducible research.
Roman Valls Guimera (@brainstorm)
Research software engineer working at the UMCCR in Melbourne, Australia. Taps into many fields of science and computing including deployable and reproducible scientific software in both HPC and cloud-computing environments for scientific workflows and data analysis. Enacted NeuroStars a Q&A site for its growing neuroscience community and also mentored students via the Google Summer of Code program. Self-taught embedded systems design and RF engineering, among other hobbies.
Melissa Gymrek (@mgymrek)
Assistant professor in Computer Science and Engineering and Medicine at UC San Diego with a research background in population genetics and bioinformatics. Interested in best practices for reproducible and open computational science and in how to take advantage of online media to change the face of scientific publishing.
Lindsey Heagy (@lheagy)
Postdoctoral Researcher at the University of California Berkeley working on interactive computing with Jupyter for the geosciences. Her research background is in computational geophysics and inverse problems. She contributes to geoscience-focused Python packages and open-source educational resources.
Thomas J. Leeper (@leeper)
A survey and experimental methodologist currently working as Associate Professor in Political Behaviour at the London School of Economics and Political Science. His research focuses on the effects of information on public opinion, as well as techniques and tools for analyzing quantitative survey and experimental data. He has published more than thirty R packages on CRAN, and has authored and contributed to numerous other open source projects.
Abigail Cabunoc Mayes (@acabunoc)
Lead Developer at the Mozilla Science Lab. Abby has led development on various open source projects for science including Contributorship Badges for Science and WormBase. With a background in bioinformatics and computer science, she builds tools that use the web to move science forward.
Pjotr Prins (@pjotrp)
Bioinformatician at large and director of Genenetwork.org and a visiting research fellow of The University of Tennessee Health Science Center and the Personal genomics and bioinformatics Department of Human Genetics of the University Medical Centre Utrecht. Writing software is Pjotr's core business in academia. He loves programming languages and he is involved in a wide range of free and open source software projects. He guides students to write software and, every year, he is a mentor and organisation administrator in the Google Summer of Code.
Tracy Teal (@tracykteal)
Executive Director of Data Carpentry and Adjunct Professor in the BEACON Center for the Study of Evolution in Action at Michigan State University. Her research background in is microbial metagenomics and bioinformatics, and she has been a developer and contributor to several open source bioinformatics projects. She also focuses on best practices in data analysis software development.
Jake Vanderplas (@jakevdp)
An astronomer, previously exploring the role of data science in academia as director of Open Software at University of Washington's eScience Institute. Google developer working on Colab. Core contributor to scikit-learn and other science-focused Python packages.
Bruce E. Wilson (@usethedata)
Manager for the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics (ORNL DAAC) and Adjunct Professor of Information Sciences at the University of Tennessee, Knoxville. Originally trained as a chemist and statistician. Spent a few years as an Enterprise Architect. Research interests in citations, linked data, reproducible science, identity, cybersecurity, data reuse, and long-term data preservation.
Yo Yehudi (@yochannah)
Software engineer at InterMine, an open source biological data warehouse based at the Department of Genetics in the University of Cambridge. Founder of Code Is Science, fellow of the Software Sustainability Institute, board member of the Open Bioinformatics Foundation, and an enthusiastic cohort host for the Mozilla Open Leaders program.
Contact JOSS
- To suggest a feature or report a bug in JOSS, please open a GitHub Issue
- To contact the JOSS staff, please email us
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 JOSS 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 JOSS 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 JOSS staff. See Contacting JOSS.
The JOSS 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.
JOSS Publication Ethics and Malpractice Statement
Editorial Board- The JOSS 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.
- JOSS 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?).
- JOSS 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 JOSS's content is subjected to peer-review (see about and docs).
- JOSS 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 JOSS review process is clearly described on the journal’s website.
- Judgments should be objective.
- JOSS 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.
- JOSS 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.
- JOSS copyright and licensing information is clearly described on the journal’s website.
- The journal and all individual articles are freely available to all readers.
- JOSS 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).
- JOSS 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 JOSS website (see https://joss.theoj.org and https://joss.theoj.org/about), including the text that it contains, demonstrates that care has been taken to ensure high ethical and professional standards.
- JOSS immediately publishes accepted articles; it is not a serial publication.
- As far as we know, the journal name (Journal of Open Source Software (JOSS)) 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 Software 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, JOSS is now eligible to seek grants for sustaining its future. With an entirely volunteer team, JOSS 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
- JOSS paper DOIs: $1 / accepted paper
- JOSS website hosting (Heroku): $19 / month
Assuming a publication rate of 200 papers per year this works out at ~$3.50 per paper ((19*12) + 200 + 275) / 200.
A more detailed analysis of our running costs is available on our blog.
Content Licensing & Open Access
JOSS is an open access journal. Copyright of JOSS 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 JOSS papers are subject to the MIT license regardless of the license of the submitted software package under review.
Any use of the JOSS logo is licensed CC BY 4.0. See the joss/logo directory in the digital-assets repository for more information about it.
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