The Journal of Open Source Software is a developer friendly, open access journal for research software packages.
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.
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.
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.
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:
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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 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 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.
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 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.
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.
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.
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.
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.
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.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
We also want to remind authors and reviewers (and anyone else) that we expect and require ethical behavior. Some examples are:
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.
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:
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.
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..
Public user content licensed CC BY 4.0 unless otherwise specified.