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:
Dan Foreman-Mackey is a 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 is an Assistant Professor of Computational Cognitive Science at the Donders Institute and the School of Artificial Intelligence at the Radboud in the Netherlands. She is a computational modeler and theoretician; more about her here.
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.
Lecturer Mechanical Engineering NUI Galway, Adjunct Senior Lecturer Griffith University, Senior Member IEEE, Developer for the GIBBON computational biomechanics project.
Associate Professor of Mechancial Engineering 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.
Professor and Chairperson of the Computer Science department at Loyola University Chicago, and visiting computer scientist at the Argonne National Laboratory Leadership Computing Facility. Research interests: programming languages, computer systems, computational science, digital humanities, parallel and distributed computing, software engineering, machine learning, computer vision, robotics, and interdisciplinary applications. Past editor-in-chief of IEEE Computing in Science and Engineering.
MetOcean Data Scientist at Axiom Data Science. Researches coastal ocean dynamics, transport of material in the ocean, and tidal turbines as a renewable energy source.
Gabriela is a Data Scientist interested in building open, fair, and diverse Ecosystems on software platforms. She has worked towards this goal at several companies, including GitHub and Atlassian. Currently, she works on making localization of digital content more accessible and inclusive at Netflix. Throughout Gabriela’s career, she has helped product teams empower users by advocating for the inclusion of multicultural perspectives in technology and creating synergies across different groups with diverse resources.
Research Software Engineer (RSE) at the University of Birmingham since 2023. Everyday user of Fortran and Python; increasingly dabbling in various languages and tools as a part of being an RSE.
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.
Monica Bobra serves as the Principal Data Scientist for the State of California. She previously studied the Sun and space weather at Stanford University and the Harvard-Smithsonian Center for Astrophysics.
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 Michigan, he develops statistical methods for genomewide polygenic scores.
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.
Associate Professor in the School of Mechanical and Materials Engineering (https://www.ucd.ie/mecheng/) at University College Dublin (https://www.ucd.ie/). Interested in novel numerical methods for solving mechanics problems in engineering.
Pierre de Buyl works at the Royal Meteorological Institute of Belgium, where he processes remote sensing data for the earth radiation budget. He is a former researcher in statistical physics and 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 are non-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.
I'm a Postdoc researcher at Center for Astrophysics Harvard | Smithsonian. I'm interested in the Galactic population of gamma-ray and X-ray sources. I I also work on statistical methods for analysis of low counts astronomical data and enjoy leading and contributing to open source software projects.
Elizabeth is a cognitive neuroscientist at Stanford University working to model individual brain activity using high-dimensional, naturalistic data sets. She is a strong advocate for the role of community-driven science to improve the generalizability of inferences in human brain mapping.
Matthew is a postdoctoral researcher in experimental high energy physics and data science at the Data Science Institute at the University of Wisconsin-Madison. He works as a member of the ATLAS collaboration on searches for physics beyond the Standard Model with experiments performed at CERN's Large Hadron Collider (LHC) in Geneva, Switzerland. He also serves on the executive board of the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) where he is a researcher and the Analysis Systems Area lead.
Conducting research on high-dimensional geometric computing, statistics, optimization and their applications. Coordinator of the GeomScale project. Affiliated with the Department of Informatics and Telecommunications, NKUA. Scientific collaborator at Ouragan team, INRIA.
Martin is currently a Research Associate in the Geographic Data Science Lab at the University of Liverpool. Researcher in urban morphology and geographic data science focusing on quantitative analysis and classification of urban form, remote sensing, and AI. He is the author of momepy, the open-source urban morphology measuring toolkit for Python, and a member of the development teams of GeoPandas, the open-source Python package for geographic data, and PySAL, the Python library for spatial analysis.
Samuel Forbes is a developmental psychologist, who specialises in infant cognitive development. His research has a particular focus on methods, developing pipelines in eye-tracking, pupillometry and fNIRS.
Expert knowledge in Julia, C, Python. Familiar with Fortran, Octave/Matlab. Strong domain knowledge in Physics (particularly solid-state, condensed matter, electronic structure theory), Chemistry (particularly quantum-chemistry, molecular-dynamics, cheminformatics) and Material science (particularly functional materials), and Machine-Learning (particularly as applied to the previous areas). Expertise in Photovoltaics and general device physics. Software that I'm deeply familiar with: Gaussian, GROMACS, LAMMPS, VASP, GPAW, NWCHEM, ASE, Pymol.
A game theorist, a research software developer and a postdoc at the research group Dynamics of Social Behavior at the Max Planck Institute for Evolutionary Biology. Nikoleta's primary research interest is mathematical modelling and its applications to biology, ecology and sociology. She is a fellow of the Software Sustainability Institute, a core developer of the Axelrod-Python library and an advocate for open source.
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.
Lead software scientist at OMSF
Evolutionary Biologist turned Research Software Engineer in Epidemiology. My main interests today revolve around integration of software in its ecosystem, with a focus on community, sustainability, interoperability, etc.
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.
Jay is an engineer-turned-geomorphologist. He creates and applies numerical models and remote sensing workflows to understand how rivers and coastal environments evolve over time.
CEO of Liberate Science GmbH, focused on repairing knowledge distribution. Research interests include modes of modular publishing, forensic statistics, and providing researchers with easier ways to do more rigorous science. PhD (2020) from Tilburg University in methodology and statistics.
Professor of Statistics at Stanford, strong supporter of reproducible research, recently stepped off @twitter, now https://fosstodon.org/@SherlockpHolmes Moderator for the stat.AP arXiv. My lab works on developing statistical methods for multi domain data with applications to women's health, immunology and the microbiome.
Aoife is a data scientist in the Research Engineering Group at the Alan Turing institute. She has a PhD in computational biology from the John Innes Centre. Her research interests include: data science, image analysis, plant science and climate change. She is always happy to discuss diversity initiatives and making research more accessible.
Postdoc at the Lab for Data Intensive Biology at University of California Davis studying the formation and maintenance of online communities, and also working on indexing, searching and scaling data analysis in large public sequencing databases using data sketches, Python, Rust and decentralizing technologies.
Director of Data Science 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.
I am a Research Associate at the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin. I received a Ph.D. from Civil and Environmental Engineering, Carnegie Mellon University, in August 2016. After finishing my Ph.D., I joined the Department of Mathematics at Louisiana State University as a Postdoctoral Fellow and worked on numerical methods and analysis of the peridynamics theory of fracture. I moved to UT Austin in August 2019 to further expand my expertise and knowledge in computational mechanics. My research interests include solids and granular media mechanics, computational oncology, uncertainty quantification, and multiscale modeling.
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.
Lecturer in the School of Computer Science at the University of St Andrews. Contributor to the computational algebra system GAP. Instructor/Trainer for The Carpentries. Fellow of the Software Sustainability Institute.
Rachel is an assistant research professor of Materials Science and Engineering at Carnegie Mellon. She has expertise in first-principles modeling (DFT) of solids, particularly point defects, as well as device-level modeling for energy applications such as photovoltaics and electrochemical systems. Her primary programming language is Julia, but she also works in Python.
Paul La Plante is a professor in the Department of Computer Science at the University of Nevada, Las Vegas. His research interests are primarily in astrophysics and cosmology, where he runs cosmological simulations and develops novel data analysis techniques for processing telescope data. He is also interested in applying machine learning methods to astronomy problems.
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, I have worked with numerical optimization and numerical linear algebra at the Federal University of Santa Catarina, in Brazil. Now I am a software engineer at Quansight, working on NumPy and other open-source software. Interested in open science, open research, and teaching practices in mathematics and computer science.
I am a statistical physicist working on biomolecular problems using machine learning.
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.
Assistant Professor in the Centre for Human Brain Health, School of Psychology, University of Birmingham. Develops methods and software for quantifying oscillatory systems and applies them to NeuroImaging data (MEG/EEG).
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.
Kelly L. Rowland is a Computer Systems Engineer in the Data Science Engagement Group at NERSC at LBNL, supporting the work of the JGI as well as other program efforts. She obtained her Ph.D. in Nuclear Engineering with a Designated Emphasis in Computational Science and Engineering from the University of California, Berkeley.
Professor, working at Istanbul University. Lectures on operations research, quantitative techniques, and computer programming. Research in computational statistics, optimization, algorithms, and data analysis. Developer and maintainer of many open source projects in several languages including Julia, R, Python, and Java. Author of three books on R programming and genetic algorithms.
Statistician, R developer. Expertise in supervised learning (statistical modelling, machine learning), Bayesian methods, dimension reduction/representation learning. Research focus on functional data.
Jacob Schreiber is a post-doctoral researcher at Stanford University. His research primarily involves answering questions in genomics by applying, or developing, machine learning methodologies to large amounts of data. In the course of this work, he has served as a core developer for scikit-learn and has written several machine learning packages for Python.
As an Atmospheric Scientist at the University of Washington and NOAA PMEL, and a postdoctoral fellow at CICOES, Hauke is focusing on advancing our understanding of atmospheric convection. His research integrates various methods including ground-based lidar/radar observations, satellite observations, large-eddy simulations, and machine learning techniques.
Adi is Senior Prototyping Architect for Robotics and AI at Amazon, where he creates very early iterations of products that break new technical grounds in cloud robotics and AI. His core expertise lies in autonomous behavior design of UAVs (drones) and robot arms. Previously, Adi led the robotics development program at Canonical and the UAV research program at Ford. Adi holds two degrees from Stanford University.
Assistant professor in the faculty of Mechanical Engineering at Technion - Israel Institute of Technology. Former research scientist at MIT. Conducting research in biomechanics and biomedical engineering, developing code for digital image correlation, finite element analysis, and various biomechanical problems.
I am an assistant professor at the Wisconsin Institute for Discovery and the Department of Plant Pathology at the University of Wisconsin-Madison. Originally from Mexico City, I did my Undergraduate degrees in Actuarial Sciences and Applied Mathematics at ITAM. Then, I did a MA in Mathematics and a PhD in Statistics at the University of Wisconsin-Madison. I work to develop statistical models to answer biological questions, balancing biological interpretability, theoretical guarantees, and computational tractability.
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.
Associate Professor in Statistics at the Center for Lifespan Changes in Brain Cogntion, Department of Psychology, University of Oslo. Research interests include development of statistical and machine learning methods with applications in cognitive neuroscience. Developer and maintainer of several R packages.
I am a researcher in the Earth System Observations group at Los Alamos National Laboratory.
Professor of Cognitive Science, Head of the Department of Computer Science, and Institutional Lead for Open and Reproducible Research at the University of Manchester. His research interests include open and reproducible research, eye-movements during written language comprehension, the processing of data visualisations, and conditional reasoning.
I am a (Software) Research Engineer at Sorbonne University, working on tools for computational neuroscience. My main development work revolves around the Brian simulator, a simulator for biological spiking neural networks. Apart from numerical modeling, I am also very interested in data visualization and, of course, Open Science and Free and Open Source. I am also a certified instructor for Software Carpentry.
Research Scientist in Audio-ML. His main research interest is in audio processing for music and speech. He recently also became involved in ecoacoustics and cognitive sciences and is a strong advocate for open and reproducible research. Fabian received his Ph.D. in Electrical Engineering from the University of Erlangen-Nuremberg in Germany.
Fei TAO is a Solution Consultant at Dassault Systèmes. He received his Ph.D. in Aeronautics and Astronautics Engineering from Purdue University, West Lafayette. His research focused on computational mechanics, mechanics of composites, finite element method, and machine learning.
Research Associate at Harvard University. Her work focuses on research reproducibility, data engineering, big data workflows, and research data and software sharing and preservation. Before this role, she was a postdoctoral scholar at the University of Chicago. She completed her Ph.D. from the University of Cambridge and CERN in 2018.
Interdisciplinary scientist analysing future energy systems and the hurdles of a transition towards decarbonised energy supply. I am a system scientist by training and have been working as a software and research software engineer in the past.
Chris is a data scientist specializing in all things geospatial who spends a lot of time developing open-source software ecosystems and mentoring. His research at the US DOE's Pacific Northwest National Laboratory focuses on MultiSector Dynamics, multi-model integration, exploratory modeling, natural language processing, graph and other ML, geospatial solutions, etc.
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.
Britta Westner is a post-doctoral researcher at the Donders Institute at the Radboud University Nijmegen. Her research is focusing on visual processing as well as the intersection of vision, memory, and language, using electrophysiological methods. She is enthusiastic about data analysis methods and is a core developer of MNE-Python, an open source analysis package for neurophysiological data.
Assistant Professor at Northumbria University (Newcastle upon Tyne, UK), using atomistic modelling to study materials for renewable energy technologies. Developing software for pre- and post-processing large-scale electronic-structure calculations and spreading the "better software, better research" message as a fellow of the Software Sustainability Institute. Happy to edit papers in the following fields: materials science, quantum chemistry, electronic structure, solid state physics, thermodynamics, RSE tooling.
Associate professor for the transition of energy systems at the Europa-Universität Flensburg. Her junior research groups focuses on pathways to climate neutral and sustainable energy systems with a foucs on sufficiency, thus an absolute reduction of energy demand. Different energy and sector models support her research for reaching sustainable energy, building, industry and transport sectors.
Computational material scientist working on material discovery using electronic structure theory, crystal structure prediction, high-throughput screening and multiscale modelling toolkits. Expertise in Python/Julia and has some Fortran knowledge. Experienced user of CASTEP, VASP, LAMMPS, GULP, ase, pymatgen.
Tania Allard, Mikkel Meyer Andersen, Lorena A Barba, Katy Barnhart, Kakia Chatsiou, Jason Clark, George Githinji, Roman Valls Guimera, Melissa Gymrek, Alex Hanna, Alice Harpole, Bita Hasheminezhad, Lindsey Heagy, Christina Hedges, Kathryn Huff, Anisha Keshavan, Thomas J. Leeper, Abigail Cabunoc Mayes, Lorena Mesa, Juan Nunez-Iglesias, Stefan Pfenninger, Viviane Pons, Jack Poulson, Pjotr Prins, Karthik Ram, Kristina Riemer, Marie E. Rognes, Ariel Rokem, Will Rowe, David P. Sanders, Matthew Sottile, Ben Stabler, Yuan Tang, Tracy Teal, Leonardo Uieda, Jake Vanderplas, Bruce E. Wilson, Yo Yehudi
If you need to contact JOSS privately then you can email us.
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:
Allegations of research misconduct associated with a JOSS 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 JOSS being retracted.
Complaints about the conduct or decision making of the JOSS editorial team can be sent to the Open Journals governance team.
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 receiving 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 a diamond/platinum 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..