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:
Authors wishing to make a pre-submission enquiry should open an issue on the JOSS repository.
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.
Gabriela is a data Scientist focused on building open, fair, and diverse Ecosystems on software platforms including GitHub and most recently Atlassian. Throughout Gabriela’s career, she has helped product teams empower users by advocating for the inclusion of multicultural perspectives in technology. A member of Codeando Mexico Gabriela’s has aided in disaster relief and develops open data from the public sector. It is her passion to use education as a way to bring minorities into the tech industry.
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 at the U.S. Geological Survey Landslide Hazards Program. 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.
Sebastian Benthall is an interdisciplinary researcher working on the economics of privacy and security at NYU School of Law. He received his PhD in Information Management and Systems from the University of California, Berkeley. His research has focused on how privacy and security depends on data flow and digital supply chain networks. More recently, he has become a contributing Research Engineer on Econ-ARK, an open source toolkit for structural modeling of heterogeneous agents.
Computational physicist at IBM Research Europe, with interests in gravitational physics, high-energy physics, and fluid dynamics, as well as large-scale Scientific Computing in general.
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.
Fred is a biostatistician with research interests in statistical genetics and quantitative trait locus mapping in model organisms. He maintains the qtl2pleio R package. As a postdoctoral researcher at the University of Massachusetts Medical School, he collaborates with microbiologists to study the genetics of tuberculosis susceptibility.
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.
My research focuses on automated, quantitative methods of processing large amounts of textual and other forms of unstructured data – mainly political texts and social media – and the methodology of text mining. I have published on applications of measurement and the analysis of text as data on machine learning methods and deep learning. I am also applying machine learning and natural language processing techniques to the analysis of public policy. My substantive research interests centre on resilience and the role of public policies and institutions at different levels of governance in shaping it. I have worked as an evaluation and digital transformation scientific advisor with local authorities and voluntary sector organisations in the UK and have delivered training to policy makers on evaluation practices, text analytics and data enabling transformation.
Postdoc at the KU Leuven's Institute for Theoretical Physics. Pierre de Buyl studies active particles and soft matter using statistical physics and numerical simulations. He is one of the editors of the SciPy Lecture Notes.
Patrick is an applied mathematician at the Center of Computation and Technology at Louisiana State University. His research interests arenon-local models, e.g. peridynamics; asynchronous many-task systems; and high performance computing. He is the co-host of the FLOSS for science podcast. Patrick received his PhD from the University of Bonn in Germany.
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.
Associate Professor in Chemical Engineering at the University of Waterloo, runs the Porous Materials Engineering & Analysis Lab with a research focus on the transport phenomena in porous materials, especially electrodes. Lead developer of OpenPNM a pore network modeling package, PoreSpy a quantitative image analysis toolkit for tomograms.
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.
Experimental atmospheric chemist and software engineer at QuantAQ. He has spent much of his academic career building and maintaining a number of open source projects related to air quality and air quality sensors.
Alice Harpole is a postdoc in the Department of Physics & Astronomy at Stony Brook University. Her research focuses on using hydrodynamics simulations to better understand the interiors of stars and flows on neutron stars. She is a fellow of the Software Sustainability Institute and core developer of the AMReX-Astro codes.
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.
Associate-professor at the Delft University of Technology in the Netherlands. Particularly interested in combining the fields of geographical information systems (GIS) and computational geometry, with an emphasis on 3D modelling.
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.
Brian McFee is Assistant Professor of Music Technology and Data Science New York University. His work lies at the intersection of machine learning and audio analysis. He is an active open source software developer, and the principal maintainer of the librosa package for audio analysis.
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.
Political scientist turned data engineer and data scientist, Lorena Mesa is a GitHub data engineer and a Director and Vice-Chair, Elect on the Python Software Foundation. Lorena's passion for ethical and accountable open source and reproducible science has led her to be a supporter of the FAIR movement and champion of FATE - fair, accountable, and transparent - algorithms. One part activist, one part space enthusiast, and another part Trekkie, Lorena abides by the motto to "live long and prosper".
Associate Professor at Department of Mathematical Sciences, Aalborg University, Denmark. Research interests include statistics for forensic genetics (mainly lineage markers like Y chromosomal DNA profiles) and open source research software. Teaches statistics and data science at BSc, MSc and PhD level. Involved in multiple software projects (e.g. for infrastructure and computer algebra).
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 Calliope to 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).
Scientific programmer in the DIgital Agriculture Group at the University of Arizona, Kristina maintains and promotes open software and datasets, provides computational training, and runs ecosystem models. She is interested in building open, inclusive, interdisciplinary scientific communities.
Amy Roberts is an Assistant Professor of Physics at the University of Colorado Denver, where she leads a research group focused on dark matter detection. She is particularly interested in building accessible analysis tools for the dark matter community and reproducible analysis infrastructure for large data sets.
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.
Works in computational applied mathematics at the Faculty of Sciences, Universidad Nacional Autónoma de México (National University of Mexico, UNAM). Research and teaching interests in the areas of scientific computing, nonlinear dynamics, and interval analysis. Currently a visiting professor at MIT. Co-author of the JuliaIntervals suite of packages for interval arithmetic and applications.
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.
Ben develops open source data science software that is used by transportation planning agencies to help prioritize infrastructure investments. He is active in several initiatives of the Transportation Research Board of the National Academies of Sciences, Engineering, and Medicine.
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.
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.
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 ~$4.75 per paper ((19*12) + 200 + 275 + 250) / 200.
A more detailed analysis of our running costs is available on our blog.
JOSS has an experimental collaboration with AAS publishing where authors submitting to one of the AAS journals can also publish a companion software paper in JOSS, thereby receviving a review of their software. For this service, JOSS receives a small donation from AAS publishing. In 2019, JOSS received $200 as a result of this collaboration.
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.