#scientificsoftware — Public Fediverse posts

#paperOfTheDay is "Lips: p-adic and singular phase space" from 2023. This article is quite different from the ones I usually read, in that it is not about a computation, but rather it describes a software. It is normal for research projects in theoretical #physics to involve large amounts of programming and computer use. Almost all of these operations rely on purpose-built #scientificSoftware , and there is a great number of open source libraries for all kinds of specialist physics computations.
The present article describes the package "Lips" (short for "Lorentz invariant phase space"), whose primary purpose is to generate valid sets of momenta for scattering amplitudes: A scattering amplitude is a function of masses and momenta of a set of particles, and it usually implies various constraints to these (e.g. masses should be positive, momenta should be conserved, individual momenta should square to given values, etc.). This makes it a non-trivial task to produce concrete numerical values of momenta that satisfy these constraints. Beyond that, one might also require specific types of numbers (rational, complex, p-adic, etc), or represent the momenta as spinors. The package can also do further calculations that arise in this context, such as evaluating spin-helicity expressions.
https://arxiv.org/abs/2305.14075

@nicholdav @astrojuanlu I think maybe the most important law of software architecture is Conway's Law - the structure of the program will tend to reflect the structure of the organization. Most scientific apps will probably reflect the very simple structure of the lab that supports them.

#rse #ScientificSoftware

Interested in #MPI and #OpenMP parallel programming to speed up your scientific applications written in #C, #Cpp, #Fortran or #Python (with #numpy)?

Attend our course in #Mainz at the Johannes Gutenberg University (#JGU) for a 4-day course from 1. April to 4. April 2025!

See our announcement page for further details and to register: https://indico.zdv.uni-mainz.de/event/34/

Note, it is an on-site course.

#RSE #HPC #scientificsoftware

The #Energy #Climate & #Environment program at #IIASAVienna had its quarterly meeting last Friday (~100 researchers), so I had to reflect on our role as community data hub and what to present on behalf of the #ScenarioServices & #ScientificSoftware team.

We developed a new #ScenarioExplorer front-end last year, and we made a lot of progress with our #opensource packages for scenario analysis, validation & data-management.

Step by step towards #OpenScience and reusable, reproducible analysis...

The #Energy #Climate & #Environment program at #IIASAVienna had its quarterly meeting last Friday (~100 researchers), so I had to reflect on our role as community data hub and what to present on behalf of the #ScenarioServices & #ScientificSoftware team.

We developed a new #ScenarioExplorer front-end last year, and we made a lot of progress with our #opensource packages for scenario analysis, validation & data-management.

Step by step towards #OpenScience and reusable, reproducible analysis...

The #Energy #Climate & #Environment program at #IIASAVienna had its quarterly meeting last Friday (~100 researchers), so I had to reflect on our role as community data hub and what to present on behalf of the #ScenarioServices & #ScientificSoftware team.

We developed a new #ScenarioExplorer front-end last year, and we made a lot of progress with our #opensource packages for scenario analysis, validation & data-management.

Step by step towards #OpenScience and reusable, reproducible analysis...

The #Energy #Climate & #Environment program at #IIASAVienna had its quarterly meeting last Friday (~100 researchers), so I had to reflect on our role as community data hub and what to present on behalf of the #ScenarioServices & #ScientificSoftware team.

We developed a new #ScenarioExplorer front-end last year, and we made a lot of progress with our #opensource packages for scenario analysis, validation & data-management.

Step by step towards #OpenScience and reusable, reproducible analysis...

The #Energy #Climate & #Environment program at #IIASAVienna had its quarterly meeting last Friday (~100 researchers), so I had to reflect on our role as community data hub and what to present on behalf of the #ScenarioServices & #ScientificSoftware team.

We developed a new #ScenarioExplorer front-end last year, and we made a lot of progress with our #opensource packages for scenario analysis, validation & data-management.

Step by step towards #OpenScience and reusable, reproducible analysis...

Working with #NUTS administrative EU 🇪🇺 regions is one of the little nuisances in #energysystems modelling and scenario analysis.

So the #IIASA #ScenarioServices team put together a little #opensource #python utility package so that modelers can focus on #freethemodels and don’t have to spend too much time on data-wrangling…
#pysquirrel #ScientificSoftware
https://github.com/iiasa/pysquirrel

Working with #NUTS administrative EU 🇪🇺 regions is one of the little nuisances in #energysystems modelling and scenario analysis.

So the #IIASA #ScenarioServices team put together a little #opensource #python utility package so that modelers can focus on #freethemodels and don’t have to spend too much time on data-wrangling…
#pysquirrel #ScientificSoftware
https://github.com/iiasa/pysquirrel

Working with #NUTS administrative EU 🇪🇺 regions is one of the little nuisances in #energysystems modelling and scenario analysis.

So the #IIASA #ScenarioServices team put together a little #opensource #python utility package so that modelers can focus on #freethemodels and don’t have to spend too much time on data-wrangling…
#pysquirrel #ScientificSoftware
https://github.com/iiasa/pysquirrel

Working with #NUTS administrative EU 🇪🇺 regions is one of the little nuisances in #energysystems modelling and scenario analysis.

So the #IIASA #ScenarioServices team put together a little #opensource #python utility package so that modelers can focus on #freethemodels and don’t have to spend too much time on data-wrangling…
#pysquirrel #ScientificSoftware
https://github.com/iiasa/pysquirrel

Working with #NUTS administrative EU 🇪🇺 regions is one of the little nuisances in #energysystems modelling and scenario analysis.

So the #IIASA #ScenarioServices team put together a little #opensource #python utility package so that modelers can focus on #freethemodels and don’t have to spend too much time on data-wrangling…
#pysquirrel #ScientificSoftware
https://github.com/iiasa/pysquirrel

Here's an ~ official ~ release announcement for #numpydantic

repo: https://github.com/p2p-ld/numpydantic
docs: https://numpydantic.readthedocs.io

Problems: @pydantic is great for modeling data!! but at the moment it doesn't support array data out of the box. Often array shape and dtype are as important as whether something is an array at all, but there isn't a good way to specify and validate that with the Python type system. Many data formats and standards couple their implementation very tightly with their schema, making them less flexible, less interoperable, and more difficult to maintain than they could be. The existing tools for parameterized array types like nptyping and jaxtyping tie their annotations to a specific array library, rather than allowing array specifications that can be abstract across implementations.

numpydantic is a super small, few-dep, and well-tested package that provides generic array annotations for pydantic models. Specify an array along with its shape and dtype and then use that model with any array library you'd like! Extending support for new array libraries is just subclassing - no PRs or monkeypatching needed. The type has some magic under the hood that uses pydantic validators to give a uniform array interface to things that don't usually behave like arrays - pass a path to a video file, that's an array. pass a path to an HDF5 file and a nested array within it, that's an array. We take advantage of the rest of pydantic's features too, including generating rich JSON schema and smart array dumping.

This is a standalone part of my work with @linkml arrays and rearchitecting neurobio data formats like NWB to be dead simple to use and extend, integrating with the tools you already use and across the experimental process - specify your data in a simple yaml format, and get back high quality data modeling code that is standards-compliant out of the box and can be used with arbitrary backends. One step towards the wild exuberance of FAIR data that is just as comfortable in the scattered scripts of real experimental work as it is in carefully curated archives and high performance computing clusters. Longer term I'm trying to abstract away data store implementations to bring content-addressed p2p data stores right into the python interpreter as simply as if something was born in local memory.

plenty of todos, but hope ya like it.

#linkml #python #NewWork #pydantic #ScientificSoftware

Here's an ~ official ~ release announcement for #numpydantic

repo: https://github.com/p2p-ld/numpydantic
docs: https://numpydantic.readthedocs.io

Problems: @pydantic is great for modeling data!! but at the moment it doesn't support array data out of the box. Often array shape and dtype are as important as whether something is an array at all, but there isn't a good way to specify and validate that with the Python type system. Many data formats and standards couple their implementation very tightly with their schema, making them less flexible, less interoperable, and more difficult to maintain than they could be. The existing tools for parameterized array types like nptyping and jaxtyping tie their annotations to a specific array library, rather than allowing array specifications that can be abstract across implementations.

numpydantic is a super small, few-dep, and well-tested package that provides generic array annotations for pydantic models. Specify an array along with its shape and dtype and then use that model with any array library you'd like! Extending support for new array libraries is just subclassing - no PRs or monkeypatching needed. The type has some magic under the hood that uses pydantic validators to give a uniform array interface to things that don't usually behave like arrays - pass a path to a video file, that's an array. pass a path to an HDF5 file and a nested array within it, that's an array. We take advantage of the rest of pydantic's features too, including generating rich JSON schema and smart array dumping.

This is a standalone part of my work with @linkml arrays and rearchitecting neurobio data formats like NWB to be dead simple to use and extend, integrating with the tools you already use and across the experimental process - specify your data in a simple yaml format, and get back high quality data modeling code that is standards-compliant out of the box and can be used with arbitrary backends. One step towards the wild exuberance of FAIR data that is just as comfortable in the scattered scripts of real experimental work as it is in carefully curated archives and high performance computing clusters. Longer term I'm trying to abstract away data store implementations to bring content-addressed p2p data stores right into the python interpreter as simply as if something was born in local memory.

plenty of todos, but hope ya like it.

#linkml #python #NewWork #pydantic #ScientificSoftware

Here's an ~ official ~ release announcement for #numpydantic

repo: https://github.com/p2p-ld/numpydantic
docs: https://numpydantic.readthedocs.io

Problems: @pydantic is great for modeling data!! but at the moment it doesn't support array data out of the box. Often array shape and dtype are as important as whether something is an array at all, but there isn't a good way to specify and validate that with the Python type system. Many data formats and standards couple their implementation very tightly with their schema, making them less flexible, less interoperable, and more difficult to maintain than they could be. The existing tools for parameterized array types like nptyping and jaxtyping tie their annotations to a specific array library, rather than allowing array specifications that can be abstract across implementations.

numpydantic is a super small, few-dep, and well-tested package that provides generic array annotations for pydantic models. Specify an array along with its shape and dtype and then use that model with any array library you'd like! Extending support for new array libraries is just subclassing - no PRs or monkeypatching needed. The type has some magic under the hood that uses pydantic validators to give a uniform array interface to things that don't usually behave like arrays - pass a path to a video file, that's an array. pass a path to an HDF5 file and a nested array within it, that's an array. We take advantage of the rest of pydantic's features too, including generating rich JSON schema and smart array dumping.

This is a standalone part of my work with @linkml arrays and rearchitecting neurobio data formats like NWB to be dead simple to use and extend, integrating with the tools you already use and across the experimental process - specify your data in a simple yaml format, and get back high quality data modeling code that is standards-compliant out of the box and can be used with arbitrary backends. One step towards the wild exuberance of FAIR data that is just as comfortable in the scattered scripts of real experimental work as it is in carefully curated archives and high performance computing clusters. Longer term I'm trying to abstract away data store implementations to bring content-addressed p2p data stores right into the python interpreter as simply as if something was born in local memory.

plenty of todos, but hope ya like it.

#linkml #python #NewWork #pydantic #ScientificSoftware

Here's an ~ official ~ release announcement for #numpydantic

repo: https://github.com/p2p-ld/numpydantic
docs: https://numpydantic.readthedocs.io

Problems: @pydantic is great for modeling data!! but at the moment it doesn't support array data out of the box. Often array shape and dtype are as important as whether something is an array at all, but there isn't a good way to specify and validate that with the Python type system. Many data formats and standards couple their implementation very tightly with their schema, making them less flexible, less interoperable, and more difficult to maintain than they could be. The existing tools for parameterized array types like nptyping and jaxtyping tie their annotations to a specific array library, rather than allowing array specifications that can be abstract across implementations.

numpydantic is a super small, few-dep, and well-tested package that provides generic array annotations for pydantic models. Specify an array along with its shape and dtype and then use that model with any array library you'd like! Extending support for new array libraries is just subclassing - no PRs or monkeypatching needed. The type has some magic under the hood that uses pydantic validators to give a uniform array interface to things that don't usually behave like arrays - pass a path to a video file, that's an array. pass a path to an HDF5 file and a nested array within it, that's an array. We take advantage of the rest of pydantic's features too, including generating rich JSON schema and smart array dumping.

This is a standalone part of my work with @linkml arrays and rearchitecting neurobio data formats like NWB to be dead simple to use and extend, integrating with the tools you already use and across the experimental process - specify your data in a simple yaml format, and get back high quality data modeling code that is standards-compliant out of the box and can be used with arbitrary backends. One step towards the wild exuberance of FAIR data that is just as comfortable in the scattered scripts of real experimental work as it is in carefully curated archives and high performance computing clusters. Longer term I'm trying to abstract away data store implementations to bring content-addressed p2p data stores right into the python interpreter as simply as if something was born in local memory.

plenty of todos, but hope ya like it.

#linkml #python #NewWork #pydantic #ScientificSoftware

Here's an ~ official ~ release announcement for #numpydantic

repo: https://github.com/p2p-ld/numpydantic
docs: https://numpydantic.readthedocs.io

Problems: @pydantic is great for modeling data!! but at the moment it doesn't support array data out of the box. Often array shape and dtype are as important as whether something is an array at all, but there isn't a good way to specify and validate that with the Python type system. Many data formats and standards couple their implementation very tightly with their schema, making them less flexible, less interoperable, and more difficult to maintain than they could be. The existing tools for parameterized array types like nptyping and jaxtyping tie their annotations to a specific array library, rather than allowing array specifications that can be abstract across implementations.

numpydantic is a super small, few-dep, and well-tested package that provides generic array annotations for pydantic models. Specify an array along with its shape and dtype and then use that model with any array library you'd like! Extending support for new array libraries is just subclassing - no PRs or monkeypatching needed. The type has some magic under the hood that uses pydantic validators to give a uniform array interface to things that don't usually behave like arrays - pass a path to a video file, that's an array. pass a path to an HDF5 file and a nested array within it, that's an array. We take advantage of the rest of pydantic's features too, including generating rich JSON schema and smart array dumping.

This is a standalone part of my work with @linkml arrays and rearchitecting neurobio data formats like NWB to be dead simple to use and extend, integrating with the tools you already use and across the experimental process - specify your data in a simple yaml format, and get back high quality data modeling code that is standards-compliant out of the box and can be used with arbitrary backends. One step towards the wild exuberance of FAIR data that is just as comfortable in the scattered scripts of real experimental work as it is in carefully curated archives and high performance computing clusters. Longer term I'm trying to abstract away data store implementations to bring content-addressed p2p data stores right into the python interpreter as simply as if something was born in local memory.

plenty of todos, but hope ya like it.

#linkml #python #NewWork #pydantic #ScientificSoftware

The Chapel team at HPE is looking for scientists to collaborate with.

Are you doing computation for science using #python or similar tools? Interested in trying something different, to run faster or scale further?

Let's make the world a better place together!

See this #blog post for details:
https://chapel-lang.org/blog/posts/python-science-collabs/

Boosts / reposts / etc greatly appreciated.

#ScientificSoftware #OpenSource #OpenScience #science #hpc

Time for a re-#introduction !

I'm a #scicomm enthusiast and board member of #Fediscience. My background is in #Biophysics, done a Postdoc in #GeneticEpidemiology, industry detour, now working in #HPC for some years.

Interested in #HPC, #bioinformatics, #OpenScience, #workflows (#snakemake), #RDM, #scientificsoftware and #sciencecommunication

My blog can be found here: blogs.fediscience.org and my more political me can be found at @[email protected].

Time for a re-#introduction !

I'm a #scicomm enthusiast and board member of #Fediscience. My background is in #Biophysics, done a Postdoc in #GeneticEpidemiology, industry detour, now working in #HPC for some years.

Interested in #HPC, #bioinformatics, #OpenScience, #workflows (#snakemake), #RDM, #scientificsoftware and #sciencecommunication

My blog can be found here: blogs.fediscience.org and my more political me can be found at @[email protected].

Time for a re-#introduction !

I'm a #scicomm enthusiast and board member of #Fediscience. My background is in #Biophysics, done a Postdoc in #GeneticEpidemiology, industry detour, now working in #HPC for some years.

Interested in #HPC, #bioinformatics, #OpenScience, #workflows (#snakemake), #RDM, #scientificsoftware and #sciencecommunication

My blog can be found here: blogs.fediscience.org and my more political me can be found at @[email protected].

Time for a re-#introduction !

I'm a #scicomm enthusiast and board member of #Fediscience. My background is in #Biophysics, done a Postdoc in #GeneticEpidemiology, industry detour, now working in #HPC for some years.

Interested in #HPC, #bioinformatics, #OpenScience, #workflows (#snakemake), #RDM, #scientificsoftware and #sciencecommunication

My blog can be found here: blogs.fediscience.org and my more political me can be found at @[email protected].

Time for a re-#introduction !

I'm a #scicomm enthusiast and board member of #Fediscience. My background is in #Biophysics, done a Postdoc in #GeneticEpidemiology, industry detour, now working in #HPC for some years.

Interested in #HPC, #bioinformatics, #OpenScience, #workflows (#snakemake), #RDM, #scientificsoftware and #sciencecommunication

My blog can be found here: blogs.fediscience.org and my more political me can be found at @[email protected].

The #Energy #Climate & #Environment program at #IIASA is looking for an #IntegratedAssessment modeler to join the #MESSAGEix team!

Come work with us on policy-relevant scenarios and state-of-the-art #opensource #ScientificSoftware tools...
📝 https://iiasa.ac.at/employment/job-openings?jh=9vvlm7a64e2n7qejcxg3n0dhyqx528y

It's so nice when #code that you have written more than a year ago just works 🎇 ☺️

#scientificsoftware #tdd

Niche interest news: today, after about 3 years of development, we tagged PyCPL 1.0.0 for release.

If writing data reduction pipeline software for European Southern Observatory astronomical instruments is for you, and you'd like to do it in Python, then maybe PyCPL is right up your alley. Look out for the new stable release on the ESO webpages in the next few weeks: https://www.eso.org/sci/software/pycpl/

I've decided to mark the occasion with a Bavarian beer, in honour of our colleagues at ESO HQ in Garching bei München.

#Astrodon #ESO #ScientificSoftware #ScientificPython

Why does most academic software, at least in medical centers, still look like Windows 95?

#science #software #windows95 #gui #aesthetics #researchlife #research #scientificsoftware

You have spent countless hours on your code. It is time for your hard work to pay off.
Document and publish your code as a software report with Seismica and let it shine!

Find out more at:

https://seismica.library.mcgill.ca/author-guidelines/#publication-types

#Seismology #EarthquakeScience #OpenAcces #Scientificjournals #DiamondOpenAccess #scientificsoftware #peerreviewed

Are your a #SoftwareDeveloper that would like to work on #Climate-related #opensource tools & #dataviz solutions?

Or are your an #EarlyCareer #Researcher that prefers programming to paper-writing?

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.

👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

Are your a #SoftwareDeveloper that would like to work on #Climate-related #opensource tools & #dataviz solutions?

Or are your an #EarlyCareer #Researcher that prefers programming to paper-writing?

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.

👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

Are your a #SoftwareDeveloper that would like to work on #Climate-related #opensource tools & #dataviz solutions?

Or are your an #EarlyCareer #Researcher that prefers programming to paper-writing?

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.

👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

Are your a #SoftwareDeveloper that would like to work on #Climate-related #opensource tools & #dataviz solutions?

Or are your an #EarlyCareer #Researcher that prefers programming to paper-writing?

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.

👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

Are your a #SoftwareDeveloper that would like to work on #Climate-related #opensource tools & #dataviz solutions?

Or are your an #EarlyCareer #Researcher that prefers programming to paper-writing?

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.

👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

On an (un)related topic, does anybody have recommendations on a journal whose primary scope is #HPC #scientificSoftware? Preference for #CFD, but more generalist recommendation are welcome too. This manuscript looking for a home is more focused on the actual code (programming strategies etc) than the physics, which makes it a poor fit for journals like CPC and JCP.

🚨Job alert🚨

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.
👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

🚨Job alert🚨

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.
👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

🚨Job alert🚨

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.
👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

🚨Job alert🚨

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.
👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

🚨Job alert🚨

The #ScenarioServices team at the #IIASA #Energy #Climate & #Environment program is hiring a #ScientificSoftware developer to implement new (#opensource) user interfaces & #dataviz features for our #ScenarioExplorer infrastructure.
👉https://iiasa.ac.at/employment/job-openings?jh=oj8uz8mtiehwnwyhls5u7b355mdre6b

🎉 We just released the #python package #ixmp4, an #opensource reimplementation of the #scientificsoftware database management behind the #IIASA #ScenarioExplorer infrastructure & the #MESSAGEix #IntegratedAssessment modelling framework.
https://github.com/iiasa/ixmp4

🎉 We just released the #python package #ixmp4, an #opensource reimplementation of the #scientificsoftware database management behind the #IIASA #ScenarioExplorer infrastructure & the #MESSAGEix #IntegratedAssessment modelling framework.
https://github.com/iiasa/ixmp4

🎉 We just released the #python package #ixmp4, an #opensource reimplementation of the #scientificsoftware database management behind the #IIASA #ScenarioExplorer infrastructure & the #MESSAGEix #IntegratedAssessment modelling framework.
https://github.com/iiasa/ixmp4

🎉 We just released the #python package #ixmp4, an #opensource reimplementation of the #scientificsoftware database management behind the #IIASA #ScenarioExplorer infrastructure & the #MESSAGEix #IntegratedAssessment modelling framework.
https://github.com/iiasa/ixmp4

🎉 We just released the #python package #ixmp4, an #opensource reimplementation of the #scientificsoftware database management behind the #IIASA #ScenarioExplorer infrastructure & the #MESSAGEix #IntegratedAssessment modelling framework.
https://github.com/iiasa/ixmp4

@danielskatz FWIW, here‘s a non-paywalled link: https://rdcu.be/c6uMN

I think it‘s great to emphasise the lack of incentives for #scientificsoftware development and #openscience more generally), but I believe that the solutions proposed by the authors are too narrow… We need to focus on an incentive structure that focuses on the usability of the tools!

And yet, the authors fail to imagine incentives & structures for #ScientificSoftware development that go beyond the current (ineffective) status quo.

Software shouldn't be coerced into an article format or a new journal; instead, we need proper #funding & dedicated #career paths for the foundation of #OpenScience.

More and more scientific disciplines realize the importance of (#opensource) #ScientificSoftware fore excellent research - and the lack of recognition & incentives to ensure maintenance of crucial pillars of our work. Commentary in #Nature #ecology & #evolution https://rdcu.be/c6uMN

@bjenquist

And yet...

The main work body of my #PhD was to develop and employ a lattice Boltzmann method for thin film flows (#LBM, #scientificsoftware).
Some of our reviewers first thoughts were: "Why should one use the #LBM for the evolution of a scalar field (the film thickness) 🙄 ?"

This is honestly a good question, because there are several good solvers for the thin film equation, e.g. @oomph-lib. One argument that I often used was, "well at least the #LBM lattice (mesh) is trivial". 😎

I just found an interesting paper on #ScientificSoftware:

Diane Kelly
Scientific software development viewed as knowledge acquisition: Towards understanding the development of risk-averse scientific software

https://doi.org/10.1016/j.jss.2015.07.027