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OSS Leftovers

Submitted by Roy Schestowitz on Wednesday 27th of May 2020 04:16:24 PM Filed under
OSS
  • Annual Report 2019: Native Language Projects – events around the world

    Canadian LibreOffice supporter Marc Paré set up LibreWaterloo, to “have a local presence on the Canadian scene with respect to the LibreOffice project and software. We would like to connect with local LibreOffice coders and users, and “to have fun” should be one of the pillars and principles we strive for.”

    He continues: “I spoke at a meeting of the KW Non-Profit Sys Admin (KWNPSA) where I am a co-coordinator, and I announced the creation of the new LibreWaterloo community group. There, I did a two hour presentation on the status of The Document Foundation, along with LibreOffice and the benefits of starting a group. There were approximately 15 people at the meeting, and a couple of people came to trouble-shoot their software; however, the meeting was not to trouble-shoot issues, but to discuss if there was an interest from the Sys Admin group.”

    Marc set up an organizing committee of three people to start with, and has plans for more events and localisation in Canada’s indigenous languages.

  • Mark Rotteveel and documentation team migrated the first documents to asciidoc
  • Open-Source and Closed-Source Monitoring Tools Compared (2020 Edition)

    Some benefits of using free and open-source software include decreased software costs, increased security and stability, protecting privacy, education, and giving users more control over their own hardware. Today, free and open-source software is everywhere. For instance, operating systems such as Linux and descendants of BSD are in widespread use and are powering millions of servers. Free-software licenses and open-source licenses are also used by many software packages. Furthermore, the free-software movement and the open-source software movement are online social movements that are accessory to the widespread adoption of free and open-source software.

  • India’s Aarogya Setu App Goes Open Source

    India has finally released the source code of its coronavirus tracking app, Aarogya Setu, on GitHub, nearly two months after its launch coupled with several privacy-related concerns.

  • Aarogya Setu goes open-source: What it means for the end user
  • Aarogya Setu becomes open source: What does it mean?

    As an answer to that today the government of India has made the Android version of the Aarogya Setu app open source, which means developers will be able to inspect the source code of the app and modify for changes. The source code of the Android version is already available for review and collaboration. All developers and researchers can visit this link to participate: https://github.com/nic-delhi/AarogyaSetu_Android.git

    The government has announced that the iOS version of the application will be released as open-source within the next two weeks and the server code will also be released subsequently. The government has also said that nearly 98 per cent users of Aarogya Setu app use an Android phone. The app is available for both iOS and Android users.

  • Government of India makes Aarogya Setu app open source; here is what it means

    Alderson isn’t the only one to have raised alarm over privacy issues in the Aarogya Setu app. New Delhi-based Software Freedom Law Centre has alleged that the app collects sensitive user data such as a user’s gender and travel history, The Internet Freedom Foundation (IFF) has also alleged that Aarogya Setu lacks transparency.

  • India’s contact tracing app is going open source [Ed: India gives Microsoft control over mass surveillance tool]

    The source code will be published on GitHub at midnight Tuesday.

  • Google Open-Sources AI for Using Tabular Data to Answer Natural Language Questions

    Google open-sourced Table Parser (TAPAS), a deep-learning system that can answer natural-language questions from tabular data. TAPAS was trained on 6.2 million tables extracted from Wikipedia and matches or exceeds state-of-the-art performance on several benchmarks.

    Co-creator Thomas Müller gave an overview of the work in a recent blog post. Given a table of numeric data, such as sports results or financial statistics, TAPAS is designed to answer natural-language questions about facts that can be inferred from the table; for example, given a list of sports championships, TAPAS might be able to answer "which team has won the most championships?" In contrast to previous solutions to this problem, which convert natural-language queries into software query languages such as SQL, which then run on the data table, TAPAS learns to operate directly on the data and outperforms the previous models on common question-answering benchmarks: by more than 12 points on Microsoft's Sequential Question Answering (SQA) and more than 4 points on Stanford's WikiTableQuestions (WTQ).

»

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