JOSSCast: Open Source for Researchers

著者: The Journal of Open Source Software
  • サマリー

  • Supercharge your research with the latest scientific software showcased in the Journal of Open Source Software (JOSS). Hear directly from authors on their work, their motivations, and new ways open source software can accelerate your work. Hosted by editor-in-chief Arfon Smith and founding editor Abby Cabunoc Mayes, each episode features an interview with different authors of published papers in JOSS. Tune in to learn about the latest developments in research software engineering and open science, and how they are changing the way research is conducted. New episodes every other Thursday.
    The Journal of Open Source Software
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あらすじ・解説

Supercharge your research with the latest scientific software showcased in the Journal of Open Source Software (JOSS). Hear directly from authors on their work, their motivations, and new ways open source software can accelerate your work. Hosted by editor-in-chief Arfon Smith and founding editor Abby Cabunoc Mayes, each episode features an interview with different authors of published papers in JOSS. Tune in to learn about the latest developments in research software engineering and open science, and how they are changing the way research is conducted. New episodes every other Thursday.
The Journal of Open Source Software
エピソード
  • Modernizing Weather Forecasting with Julia – Milan Klöwer on SpeedyWeather.jl
    2024/10/03
    #20: Milan Klöwer joins Arfon and Abby to discuss SpeedyWeather.jl, its development, and its role in climate science. Milan is a Schmidt AI in Science Fellow at the University of Oxford. You can follow Milan on X/Twitter: https://twitter.com/milankloewer bsky: https://bsky.app/profile/milank.bsky.social and at his website milankl.github.io Episode highlights: [01:10] - Introducing Milan Clover[01:56] - Understanding Atmospheric General Circulation Models[05:15] - The Evolution of Weather Prediction[07:23] - SpeedyWeather.jl: A New Approach[20:05] - The Legacy of Fortran in Climate Science[20:51] - Why Julia?[25:35] - Building SpeedyWeather.jl[26:11] - Interactive Modeling with SpeedyWeather.jl[34:07] - The Importance of Open Source in Climate Science[35:29] - Call for Contributors[40:53] - Final Thoughts and Future Plans Links: JOSS paper: https://joss.theoj.org/papers/10.21105/joss.06323 SpeedyWeather.jl repository: https://github.com/SpeedyWeather/SpeedyWeather.jlMilan’s website: milankl.github.io Milan social media: X/Twitter: https://twitter.com/milankloewer bsky: https://bsky.app/profile/milank.bsky.socialThe Journal of Open Source Software (Twitter/X, blog)@arfon on (fosstodon, Linkedin, GitHub, website)@abbycabs on (Twitter/X, hachyderm, bsky, Linkedin, GitHub, website)Donate to JOSS Supercharge your research with the latest scientific software showcased in the Journal of Open Source Software (JOSS). Hear directly from authors on their work, their motivations, and new ways open source software can accelerate your work. Hosted by editor-in-chief Arfon Smith and founding editor Abby Cabunoc Mayes, each episode features an interview with different authors of published papers in JOSS. Tune in to learn about the latest developments in research software engineering and open science, and how they are changing the way research is conducted. New episodes every other Thursday.
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    42 分
  • Tackling the Machine Learning Reproducibility Crisis – KJ Schmidt & Aristana Scourtas on Foundry-ML
    2024/09/19

    #19: KJ Schmidt & Aristana Scourtas join Arfon and Abby to discuss Foundry-ML, a platform designed to simplify using machine learning datasets, highlighting its development, impacts, and their career advancements post-project.

    KJ just started a position at the Institute for Genomic Medicine within Nationwide Children's Hospital. Aristana is a Product and Research Manager at The Library Innovation Lab at Harvard Law School. KJ and Aristana both worked on Foundry-ML during their time working at UChicago and Globus.

    You can follow Aristana on LinkedIn https://www.linkedin.com/in/aristana/ and Twitter/X @aristana_s. You can follow KJ on Twitter/X @kj_schmidt or LinkedIn https://www.linkedin.com/in/schmidtkj/.

    Episode highlights:

    [01:54] Beginning of Interview with KJ Schmidt and Aristana Scourtas [02:02] What is Foundry-ML? [04:02] The Role of Globus in Foundry-ML [05:29] Reproducibility in Machine Learning [06:45] Applications and Collaborations [09:15] New Roles and Future Plans [11:01] Maintaining Foundry-ML [12:37] Sustainability in Open Source [13:12] Community Building in Open Source [21:49] Challenges and Lessons Learned [24:28] Publishing in JOSS [25:38] Closing Remarks and Contact Information

    Links:
    • JOSS paper: https://joss.theoj.org/papers/10.21105/joss.05467
    • Foundry repository: https://github.com/MLMI2-CSSI/foundry
    • Website: https://foundry-ml.org/
    • Movement Building from Home
    • KJ on Twitter/X @kj_schmidt or LinkedIn https://www.linkedin.com/in/schmidtkj/
    • Aristana on LinkedIn https://www.linkedin.com/in/aristana/ and Twitter/X @aristana_s
    • The Journal of Open Source Software (Twitter/X, blog)
    • @arfon on (fosstodon, Linkedin, GitHub, website)
    • @abbycabs on (Twitter/X, hachyderm, bsky, Linkedin, GitHub, website)
    • Donate to JOSS

    Supercharge your research with the latest scientific software showcased in the Journal of Open Source Software (JOSS). Hear directly from authors on their work, their motivations, and new ways open source software can accelerate your work.

    Hosted by editor-in-chief Arfon Smith and founding editor Abby Cabunoc Mayes, each episode features an interview with different authors of published papers in JOSS. Tune in to learn about the latest developments in research software engineering and open science, and how they are changing the way research is conducted.

    New episodes every other Thursday.

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    28 分
  • Visualize Hypergraphs with Open Source – Brenda Praggastis on HyperNetX
    2024/09/05

    #18: Brenda Praggastis joins Arfon and Abby to discuss HyperNetX, a Python package for modeling complex network data as hypergraphs. Brenda discusses the distinctions between graphs and hypergraphs, their real-world applications, and the collaborative nature of the hypergraph community. She also delves into the open-source development process, the capabilities and limitations of HyperNetX, and the importance of community contribution in advancing hypergraph research. Tune in to learn more about hypergraphs and their growing significance in various research fields.

    Brenda is a mathematician and data scientist at the Pacific Northwest National Laboratory.

    You can follow HyperNetX on GitHub https://github.com/pnnl/HyperNetX.

    Episode highlights:

    [01:59] - Interview Begins: Welcome Brenda!

    [02:05] - Understanding Hypergraphs

    [04:57] - Brenda's Journey to Hypergraphs

    [06:03] - Visualizing Hypergraphs

    [11:31] - Deep Dive into HyperNetX

    [19:58] - Applications of Hypergraphs

    [22:25] - Scalability and Performance of HyperNetX

    [24:54] - Publishing in JOSS

    [26:16] - Contributing to HyperNetX

    Links:

      • JOSS paper: https://joss.theoj.org/papers/10.21105/joss.06016

      • HyperNetX repository: https://github.com/pnnl/HyperNetX

      • Docs: https://hypernetx.readthedocs.io/en/latest/

      • The Journal of Open Source Software (Twitter/X, blog)

      • @arfon on (fosstodon, Linkedin, GitHub, website)

      • @abbycabs on (Twitter/X, hachyderm, bsky, Linkedin, GitHub, website)

      • Donate to JOSS

    Supercharge your research with the latest scientific software showcased in the Journal of Open Source Software (JOSS). Hear directly from authors on their work, their motivations, and new ways open source software can accelerate your work.

    Hosted by editor-in-chief Arfon Smith and founding editor Abby Cabunoc Mayes, each episode features an interview with different authors of published papers in JOSS. Tune in to learn about the latest developments in research software engineering and open science, and how they are changing the way research is conducted.

    New episodes every other Thursday.


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    31 分

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