opensource &mdash; naclscrg https://naclscrg.writeas.com/tag:opensource Various notes from my research. For some context, see: [https://www.penonek.com/](https://www.penonek.com/) Sun, 06 Sep 2026 14:16:06 +0000 If you're considering CC BY-NC, consider CC BY-SA instead https://naclscrg.writeas.com/if-youre-considering-cc-by-nc-consider-cc-by-sa-instead?pk_campaign=rss-feed <![CDATA[I recently wrote an email to a colleague suggesting that they publish a piece of work under the Creative Commons Attribution-ShareAlike (CC BY-SA) license instead of the Attribution-NonCommercial (CC BY-NC) license. I often find myself making this case, so I've generalised that email into this post so I can refer back to it later. !--more-- I received a certificate from Creative Commons on copyright and open licensing, and respectfully suggest that the material be published with the Creative Commons Attribution ShareAlike 4.0 (CC BY-SA 4.0) license instead of the Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0) license. As authors and creators, the primary audience of our work are likely fellow academics or professional staff like librarians. And we might not always want - for example - big companies like academic publishers profiting off of our work without giving anything back. However, the NonCommercial clause is very ambiguous about exactly what counts as "commercial" uses of a work, and interpretations vary greatly by jurisdiction. For example, there could be a teacher or lecturer who wants to incorporate a piece of CC BY-NC licensed work in their education materials, but hesitates to do so because they work in a private school that technically makes a "profit". It's unclear if the fact that their school makes money would run afoul of the NonCommercial clause. In another example, a non-profit organisation might seek to incorporate CC BY-NC licensed work into their fundraising materials. Again, they might hesitate to do so because while they are a non-profit group, the specific use involves "making money". In other words, the CC BY-NC license often creates unintended chilling effects on otherwise valuable and desirable uses of a work. In contrast, the Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0) license takes a "pay it forward" approach, where downstream uses are allowed as long as users continue to share the work or any of its derivatives under the same CC BY-SA license. This means the CC BY-SA licensed work and all derivatives will be kept open. This works around the NC clause's chilling effects while providing the side benefit of deterring undesirable uses by big companies, because those entities typically seek to close and lock things down instead of opening them. I'd go as far as to say that if someone comes up with a commercial use of CC BY-SA licensed works, this is something we should encourage anyway! Therefore, unless there is a very specific and well-defined commercial use that we are certain can be, and must be, deterred by the CC BY-NC license, we should instead use the CC BY-SA license. The latter fosters a culture of not only openly sharing our creative works, but also encourages good citizenship where everyone pays it forward. Here is a grab bag of relevant further readings: https://zookeys.pensoft.net/article/3036/list/1/ https://wiki.creativecommons.org/wiki/NonCommercialinterpretation https://en.wikipedia.org/wiki/CreativeCommonsNonCommerciallicense https://creativecommons.org/faq/#does-my-use-violate-the-noncommercial-clause-of-the-licenses #openresearch #opensource #licensing ---------- p xmlns:cc="http://creativecommons.org/ns#" Unless otherwise stated, all original content in this post is shared under the a href="https://creativecommons.org/licenses/by-sa/4.0/" target="blank" rel="license noopener noreferrer" style="display:inline-block;"Creative Commons Attribution-ShareAlike 4.0 International/a licensea href="https://creativecommons.org/licenses/by-sa/4.0/" target="blank" rel="license noopener noreferrer" style="display:inline-block;"img style="height:22px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/cc.svg?ref=chooser-v1" alt=""img style="height:22px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/by.svg?ref=chooser-v1" alt=""img style="height:22px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/sa.svg?ref=chooser-v1" alt=""/a/p ]]> I recently wrote an email to a colleague suggesting that they publish a piece of work under the Creative Commons Attribution-ShareAlike (CC BY-SA) license instead of the Attribution-NonCommercial (CC BY-NC) license. I often find myself making this case, so I've generalised that email into this post so I can refer back to it later. I received a certificate from Creative Commons on copyright and open licensing, and respectfully suggest that the material be published with the Creative Commons Attribution ShareAlike 4.0 (CC BY-SA 4.0) license instead of the Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0) license.

As authors and creators, the primary audience of our work are likely fellow academics or professional staff like librarians. And we might not always want – for example – big companies like academic publishers profiting off of our work without giving anything back.

However, the NonCommercial clause is very ambiguous about exactly what counts as “commercial” uses of a work, and interpretations vary greatly by jurisdiction. For example, there could be a teacher or lecturer who wants to incorporate a piece of CC BY-NC licensed work in their education materials, but hesitates to do so because they work in a private school that technically makes a “profit”. It's unclear if the fact that their school makes money would run afoul of the NonCommercial clause. In another example, a non-profit organisation might seek to incorporate CC BY-NC licensed work into their fundraising materials. Again, they might hesitate to do so because while they are a non-profit group, the specific use involves “making money”. In other words, the CC BY-NC license often creates unintended chilling effects on otherwise valuable and desirable uses of a work.

In contrast, the Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0) license takes a “pay it forward” approach, where downstream uses are allowed as long as users continue to share the work or any of its derivatives under the same CC BY-SA license. This means the CC BY-SA licensed work and all derivatives will be kept open.

This works around the NC clause's chilling effects while providing the side benefit of deterring undesirable uses by big companies, because those entities typically seek to close and lock things down instead of opening them. I'd go as far as to say that if someone comes up with a commercial use of CC BY-SA licensed works, this is something we should encourage anyway!

Therefore, unless there is a very specific and well-defined commercial use that we are certain can be, and must be, deterred by the CC BY-NC license, we should instead use the CC BY-SA license. The latter fosters a culture of not only openly sharing our creative works, but also encourages good citizenship where everyone pays it forward.

Here is a grab bag of relevant further readings:

https://zookeys.pensoft.net/article/3036/list/1/

https://wiki.creativecommons.org/wiki/NonCommercial_interpretation

https://en.wikipedia.org/wiki/Creative_Commons_NonCommercial_license

https://creativecommons.org/faq/#does-my-use-violate-the-noncommercial-clause-of-the-licenses

#openresearch #opensource #licensing

Unless otherwise stated, all original content in this post is shared under the Creative Commons Attribution-ShareAlike 4.0 International license

]]> https://naclscrg.writeas.com/if-youre-considering-cc-by-nc-consider-cc-by-sa-instead Mon, 10 Aug 2026 16:25:52 +0000 Talk - Open source hardware for more equitable open science https://naclscrg.writeas.com/talk-open-source-hardware-for-more-equitable-open-science?pk_campaign=rss-feed <![CDATA[Since 2023, I've given several variations of my talk about open source hardware as a key component of open science. Here, I will share extra notes on what didn't fit in the talk, a transcript, further reading/resources, and a recording of the talk. !--more-- This note is structured as follows, please scroll down to the section you're looking for. Recording Transcript Further reading/resources Recording I've given several variations of this talk with multiple recordings. For now, here is the recording of an early iteration I gave at the Edinburgh Open Research Conference in mid-2023 (click on the "Presentation Video" link on the page): https://doi.org/10.2218/eor.2023.8112 I will try to put other recordings here on a best effort basis. Transcript I will put a transcript of the talk here as soon as I can. Further reading/resources The official Open Source Hardware Definition: https://www.oshwa.org/definition/ OreSat open source cubesats: https://www.oresat.org/ Public Lab is the group which developed the open source balloon mapping platform in response to the 2010 Deepwater Horizon oil spill: https://publiclab.org/ Story about capturing photographic evidence of dumping toxic waste in the Mississippi River: https://publiclab.org/notes/eustatic/05-28-2013/kite-photos-of-ongoing-coal-pollution-in-plaquemines-parish-la Claudia Martinez Mansell is a humanitarian worker and independent researcher who worked at the Bourj Al Shamali refugee camp in Lebanon. It's the community there that remixed the Public Lab balloon mapping platform for use in their camp. Relevant reading: https://placesjournal.org/article/camp-code/ https://publiclab.org/notes/clauds/04-28-2016/camp-code-how-to-navigate-a-refugee-settlement Peer-reviewed papers Arancio, J. (2023). From inequalities to epistemic innovation: Insights from open science hardware projects in Latin America. Environmental Science & Policy, 150, 103576. https://doi.org/10.1016/j.envsci.2023.103576 Associated article: https://sparcopen.org/impact-story/often-overlooked-sharing-of-hardware-is-a-missing-link-in-open-science-puzzle/ Burke, N., Müller, G., Saggiomo, V., Hassett, A. R., Mutterer, J., Ó Súilleabháin, P., Zakharov, D., Healy, D., Reynaud, E. G., & Pickering, M. (2024). EnderScope: A low-cost 3D printer-based scanning microscope for microplastic detection. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 382(2274), 20230214. https://doi.org/10.1098/rsta.2023.0214 Collins, J. T., Knapper, J., Stirling, J., Mduda, J., Mkindi, C., Mayagaya, V., Mwakajinga, G. A., Nyakyi, P. T., Sanga, V. L., Carbery, D., White, L., Dale, S., Lim, Z. J., Baumberg, J. J., Cicuta, P., McDermott, S., Vodenicharski, B., & Bowman, R. (2020). Robotic microscopy for everyone: The OpenFlexure microscope. Biomedical Optics Express, 11(5), 2447–2460. https://doi.org/10.1364/BOE.385729 Grant, S. D., Cairns, G. S., Wistuba, J., & Patton, B. R. (2019). Adapting the 3D-printed Openflexure microscope enables computational super-resolution imaging (No. 8:2003). F1000Research. https://doi.org/10.12688/f1000research.21294.1 Hsing, P.-Y., Johns, B., & Matthes, A. (2024). Ecology and conservation researchers should adopt open source technologies. Frontiers in Conservation Science, 5. https://doi.org/10.3389/fcosc.2024.1364181 Pearce, J. M. (2020). Economic savings for scientific free and open source technology: A review. HardwareX, 8, e00139. https://doi.org/10.1016/j.ohx.2020.e00139 Thaler, A., Sturdivant, K., Neches, R., & Levenson, J. (2024). The OpenCTD: A low-cost, open-source CTD for collecting baseline oceanographic data in coastal waters. Oceanography. https://doi.org/10.5670/oceanog.2024.60 Useful guides UNESCO Open Science Toolkit guide on "Supporting open hardware for open science": https://doi.org/10.54677/LUMO4515 Report - Creating an Open-source Hardware Ecosystem for Research and Sustainable Development: https://doi.org/10.5281/zenodo.8301858 Report - Supporting Open Science Hardware in Academia: Policy Recommendations for Science Funders and University Managers: https://doi.org/10.5281/zenodo.8030028 Open Know-How is a specification for including detailed metadata with your open source hardware project so that its designs are more machine readable, interoperable, and reproducible: https://www.internetofproduction.org/openknowhow DIN SPEC 3105 is a specification for good practices in publishing and peer reviewing open source hardware designs: https://www.beuth.de/en/technical-rule/din-spec-3105-1/324805763 Relevant organisations Gathering for Open Science Hardware (GOSH): https://openhardware.science/ Open Source Hardware Association: https://www.oshwa.org/ Open Science Hardware Foundation: https://opensciencehardware.org/ Internet of Production Alliance: https://www.internetofproduction.org/ Open Hardware Makers provide mentoring and training on how to develop and support open source hardware: https://openhardware.space/ IO Rodeo sells open source hardware for scientific research, including the OpenFlexure microscope: https://www.iorodeo.com/ #talks #opensource #openresearch ---------- p xmlns:cc="http://creativecommons.org/ns#" Unless otherwise stated, all original content in this post is shared under the a href="https://creativecommons.org/licenses/by-sa/4.0/" target="blank" rel="license noopener noreferrer" style="display:inline-block;"Creative Commons Attribution-ShareAlike 4.0 International/a licensea href="https://creativecommons.org/licenses/by-sa/4.0/" target="blank" rel="license noopener noreferrer" style="display:inline-block;"img style="height:22px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/cc.svg?ref=chooser-v1" alt=""img style="height:22px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/by.svg?ref=chooser-v1" alt=""img style="height:22px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/sa.svg?ref=chooser-v1" alt=""/a/p ]]> Since 2023, I've given several variations of my talk about open source hardware as a key component of open science. Here, I will share extra notes on what didn't fit in the talk, a transcript, further reading/resources, and a recording of the talk. This note is structured as follows, please scroll down to the section you're looking for.

  • Recording
  • Transcript
  • Further reading/resources

Recording

I've given several variations of this talk with multiple recordings. For now, here is the recording of an early iteration I gave at the Edinburgh Open Research Conference in mid-2023 (click on the “Presentation Video” link on the page):

https://doi.org/10.2218/eor.2023.8112

I will try to put other recordings here on a best effort basis.

Transcript

I will put a transcript of the talk here as soon as I can.

Further reading/resources

Peer-reviewed papers

Useful guides

Relevant organisations

#talks #opensource #openresearch

Unless otherwise stated, all original content in this post is shared under the Creative Commons Attribution-ShareAlike 4.0 International license

]]> https://naclscrg.writeas.com/talk-open-source-hardware-for-more-equitable-open-science Mon, 02 Dec 2024 16:36:30 +0000 Talk - The critical role of open source in open research https://naclscrg.writeas.com/critical-role-of-open-source-in-open-research?pk_campaign=rss-feed <![CDATA[On 20 March 2024, I gave a talk at the Open Source for Innovation in Universities event titled "The critical role of open source in open research" (open source slides published to Zenodo). Like last time, it was informed by incredible feedback I received from various open research communities, especially Malvika of the Turing Way who first connected me to the organisers. There's extra stuff I couldn't fit into the talk, so I'm putting them here. !--more-- I'm posting: a few general notes; other resources/further reading suggested by Turing Way members; and a transcript of my talk. I'll try to clean up this post with more context and details on a best-effort basis. There is a video recording which is saved in the Zenodo item, viewable on YouTube, and embedded here: iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/MFKmZmp7HmI?si=stsNsVycBEqGKjAx" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen/iframe General notes In-person verbal feedback was positive, though I didn't get to use as much time preparing it as I wanted. I was also running out of time near the end, and wish I could have talked about the Turing Way more! This time, I also opened a Turing Way GitHub issue #3570, to track the development of this talk. As expected, I wasn't able to fit everything in, but also thank you to Sarah Gibson, Julien Colomb, Esther Plomp for your feedback earlier to help me prepare! I'm also grateful to the organisers Michael Meagher and Clare Dillon who gathered a great group of warm and interesting people for this event. :) Special thanks for Malvika Sharan for the several meetings we had to structure this talk. a note about creating a transcript For my FOSDEM lightning talk, I typed what I wanted to say directly into the presenter notes in my slides before the talk. However, this time I just didn't have time to do that. So, I tried using my phone to make a live audio recording as I gave the presentation. Then, I used the open source Whisper.cpp automatic speech recognition tool with its open-ish ggml-small.en model to generate a transcript. Then, I copied that transcript into the presenter notes of the final slides published to Zenodo. In the end, I think this method works, but is still time-consuming. The generated transcript is a huge text file that I had to manually split into paragraphs, and copy and paste individual chunks of text into their corresponding presenter notes. This is also what's below in the "Transcript" section. Will I continue to use Whisper.cpp in the future? Yes, I think its text transcription is remarkably accurate and is getting better. Though there are still paper cuts in the user experience that adds some work for me. Other resources/examples Thanks to Sarah Gibson and Julien Colomb for the suggested examples: The Gorgas tracker as mentioned in this post and described in Arancio (2023). CERN's White Rabbit project. Also see this interview about it. The Python and R ecosystems vs MATLAB and SPSS in days past. JupyterHub, specifically the QGreenland project (WARNING: Medium link). I really like this one because it's not just one piece of open source hardware, but an entire stack that could only work well when all components are open source and remixable. Transcript Note: This transcript is lightly edited for clarity, such as by removing the "uh"s and "you know"s, or "ah"s. Thank you so much for that introduction, Clare. I'm really excited to be here with you today. It's really quite a privilege to be speaking to you. And as Clare mentioned, I am a member of the Turing Way community, which I will come back to near the end of the talk. But today, I'd like to share some of my own reflections being not only an advocate for open research in the academic community over the past several years, but also as a member of the open source community. I very much think of my talk as a kind of "yes, and..." kind of presentation. And it's also intentionally provocative with the intention of stimulating, new thinking around what kind of opportunities can we consider when it comes to open source technologies and open research. I want to start very briefly by focusing on the term open research and make kind of a subtle point here. So I consider open research to cover a very wide and diverse array of different research disciplines. And a lot of the examples I'd like to share today come from my experience advocating for open science, which I consider to be a very important component of open research, but it's not all of open research. So there's a subtle difference between the terms and I'd just like to delineate the two, even though most of what I'm talking about today comes from the open science world. With that said, the structure of my talk today, I'd like to start with my reflections on some of the core values of open science, why open science is so important, including in academic research. Very briefly on a lot of the invisible infrastructure of technology that underlies the scientific research that we do, followed by I think the biggest part of my talk today, which are the additional motivations for open source technologies to enable open science. And I'd like to bring up the hardware component as well because we've heard a lot about software. And finally, I will talk about some of the communities that have been so lucky to be a part of over the years that discusses a lot of the things in my talk today. So, open science. I've talked about open science to so many people over the years, and what I have learned is that... ...if you ask 10 people what open science means, they will tell you, yes, I know what it is, but they will give you 10 different answers. So I'd just like to set the scene a little bit for my talk today to establish a common understanding just to help with the conversation. And one of the initiatives that I've been really privileged to be a part of is the drafting of the UNESCO Recommendation on Open Science that was ratified in 2021. I had a very small role to play in this, but it was a huge privilege to be part of the process and it produced an amazing document. It's really long, but I recommend you check it out. And part of it defines open science to mean a set of practices for reproducibility, transparency, sharing, and collaboration from the increased opening of scientific contents towards and processes. Again, I think this is an amazing document, but this definition is also quite a mouthful, right? So I tried to reflect on: is there kind of like an essence to this definition? And what I came to is actually the difference between science and alchemy. So what do I mean by this? I was inspired to think about this by a very provocative digital rights author called Cory Doctorow. He writes a lot about these kind of fundamental values underlying open research and open science and open source. And he said, if we think about how alchemists used to work superficially, they were running experiments, they had some research questions, they took lots of notes, and they were actually learning along the way. But the thing with alchemists is that they kept what they knew a secret from each other for 500 years. Because of that secrecy, they didn't advance the state of the art very much. And because of that, every single one of them had to learn in the hardest possible way that drinking mercury is a bad idea. I think this really hits at the core of the difference between science and alchemy because science is a fundamentally iterative process where we are always building on knowledge shared by other people and what came before. So in a way, for us to be responsible scientists, we have to continue to share what we have learned with other people to build upon our successes and failures. So I think to do good science is to do open science, and I think that's what open science is really about. Another way to think about this is what I think of as intellectual humility because I've been an academic researcher for like 15 years now. And reflecting on these years of research, I realized that whatever little bit I've added to our collective body of knowledge, I was able to do that because of everything that I've learned from the people who came before me. So a researchers, we really didn't get here on your own. It's really built on top of what everyone else has shared with you. And it is with all of this in mind that I think open science really comes with four fundamental freedoms, where for any piece of knowledge, it should come with the freedoms for anyone to use it, study it, modify it, and continue to share it with other people to continue that iterative cycle. So this is how I like to think of open science. And that's the first thing I wanted to cover today. The next thing I wanted to quickly establish is that for this science to happen, we're making use of so much shared technical infrastructure today. I remember many years ago I was at this hackathon with Arfon Smith from GitHub. And he was the person who gave me that lifetime Pro subscription to a GitHub that I'm still getting dividends from to this day. It is a platform that comes with amazing features. But at the same time, I also remember how a couple of years ago there was this big GitHub outage for a couple of hours. And it is when things like this happen that we realize how reliant we have become on the software and hardware infrastructure in our lives. Because when they break, when we hurt, that's when we realize our reliance on these things. And it's important to think about this because it reminds us to reflect on who gets to have a say in how this infrastructure works and how that infrastructure can work for us as researchers, and how we live out our lives. So this invisible infrastructure is really important. And this kind of centralization that's happening, I think, is a challenge that open source technologies can tackle. So I've been thinking about a lot of the motivations for open source, including a lot of the reasons that people have talked about today. And I'd like to go over some examples. I want to talk about hardware, but will start with a software example that I think is amazing, which is... ...the QGreenland project. So I thought this project was so cool because it started out as a bunch of academic scientists who share a common theme, which is that they all study Greenland. It could be meteorologists, geologists, and a lot of other scientists. And they developed this common software platform for analyzing geospatial data about Greenland. And they built it on top of an open source software called QGIS. It is a geographical information system, so that they can pull all of the geospatial data about Greenland into one place. They have a whole suite of tools built on top of QGIS to analyze that data. And the whole stack is called QGreenland. And what happened was that this project became successful. And last year in 2023, they wanted to run a training workshop for other researchers to learn about how to use QGreenlandfor their scientific research. But one problem they encountered was that if they have 20 scientists in the room coming to this workshop, all with their laptops and their different operating systems and configurations,it takes so much time to just get people to the same page to install QGIS,get it running, and then put QGreenland on top of it. That takes so much time from the actual training they wanted to do. So they thought, okay, can we reduce this friction a little bit? And the solution they came up with was that they started with JupyterHub, which is kind of like a server-hosted version of the Python-based kind of Jupyter computational notebook that a lot of data scientists use. But they were able to make some additions to Jupyter and tweak it so that instead of just running Python, they're running an entire Linux desktop environment on top of JupyterHub. And with that, they can then install QGIS into that Linux environment, and then they put the whole QGreenland geospatial data platform on top of that. And once they put all of this together into one package, they serve it from their server so that the participants in the workshop, they can just open up their web browsers, go to a particular URL, and the whole package runs as a web page inside their browser. And this saves so much time in the workshop because they don't need to set QGIS up on every individual computer. Now, the reason I love this example is that all of these components, they are open source to begin with, and they demonstrate the FAIR principles of open science. Now, I think a lot of you know what FAIR stands for, but just so we're on the same page, FAIR stands for... ...Findable, Accessible, Interoperable, and Reusable. And this is a big thing in open science, and I think QGreenland demonstrates all of it. Because of this open source publishing online, it's easy for people to find it. The way they set it up is really accessible. It's interoperable because the components are open source, and they were able to tweak the components to interact with each other. And, of course, it's reusable because other scientists can adapt it to different research contexts. And I think this is a demonstration of how the FAIR principles that are so important to open science are enabled by open source technologies. Okay, so this is a software example, but if you look at the UNESCO recommendation on open science, it talks about several main pillars of open science, including the usual suspects like open access publications, open data, open educational resources (I think this one is really important!), and of course, open source software code. In addition to that, the recommendation emphasizes that hardware is a really important part of open science as well. So I like to focus a bit on the open source hardware side of things. And if you really think about it, hardware underpins so much of scientific research. It was literally hardware that took people to the moon. That's how much we rely on hardware to do science. It can be huge pieces of equipment like the Large Hadron Collider, Or it can be something seemingly simple, but equally integral to the research infrastructure, like microscopes that we use in so many labs today. Now, the thing with hardware is that it's very often closed source, like a lot of software. And some of the challenges with that is that it's not reproducible in a scientific way. There's vendor lock-in, which was mentioned before. There's forced obsolescence, and there are very high costs. The cost is not only in terms of a very expensive piece of equipment. It's also the very high switching costs, where if you decide there's another equipment you want to use, but since it's not open source and there's no interoperability, it's very difficult for you to switch to a different platform. And this causes a lot of global inequalities in research. I personally know some scientists in some global south countries who really want to have a particular piece of instrument in their lab, but the one manufacturer that makes it simply do not sell it in their country. And even if they somehow get access to buy it, the cost is so high that they cannot afford it. And if they somehow scrunch together the money to be able to afford to buy it, once they have it, they won't be able to get any support on it. They cannot maintain it themselves. And it just becomes prohibitively difficult for a lot of researchers in different places around the world. So I think when it comes to the social impact of our technologies, it's really important to be mindful of a lot of the global inequalities that come with the technologies of today. So in contrast to that, open source hardware is defined as hardware whose design is available so that anyone, again, can study, modify, distribute, make, and sell hardware based on that design. And there are a lot of examples, actually, in scientific research. An amazing one that I know about is the Open Source Imaging Initiative. So this is a consortium of universities across Europe, including some companies, I believe, who came together to create a completely open source MRI machine for medical scanning and diagnosis. And if you know anything about MRI machines, you know how complicated and intricate they are. And they're actually creating an open source version of it that's becoming successful! Open source hardware has been to space. Researchers in the U.S., they've developed the ORESAT, which is an open source CubeSat, that became a common platform for scientists across the U.S. to build on top of for remote sensing applications. It's been launched several times already, and I think they have more launches scheduled. But the example that I'd really love to talk about is the OpenFlexure microscope. So this is a lab-grade microscope, originally developed by researchers at the University of Bath in the U.K. (I think their team is based in Glasgow now). The point is it's completely open source and modular, and you can 3D print most of the microscope yourself. It comes with a lot of features, starting with the basic ones like bright field imaging, or fluorescence imaging. But because it is fully open source, there was a separate research team in a different part of the world that looked at the designs, and they actually enhanced it and improved it to greatly increase the resolution for fluorescence imaging. And this is something that people weren't able to do with the closed-sourced microscopes that they used before. These are just a couple of features, but what's also really cool is that this open-source microscope, if you want to build it yourself, the cost of doing so is only about 200 US dollars. Now, for those of you who have used and bought microscopes for use in the lab before, you will know that these microscopes often cost an order of magnitude more than OpenFlexure for doing the same thing, and I think that's absolutely remarkable. And because of its low cost and because it's open source, again, as an example, researchers in several sub-Saharan countries, they were able to take the OpenFlexure design to locally produce and maintain that microscope from malaria diagnosis when they weren't able to do it before. And in addition to this, it has actually prompted the formation of some small businesses in those countries to locally produce and sell these microscopes, and it's again becoming a new business model that's enabled by open source technology. Okay, so to kind of build on some of the points made earlier, Joshua Pierce is a researcher in this, and he calculated that open source technologies, including hardware, can provide economic savings of up to 87% compared to functionally equivalent proprietary tools. And again, my other point is that in addition to the savings, it creates new kinds of businesses. So I have a bit of a background in molecular biology, and I've used PCR machines a lot. And there's a company who sells these Ninja PCR machines for US$500. Again, if you have bought this for labs before, you'll know that they typically cost an order of magnitude more. So it's amazing how open source not only lower costs, but creates new kinds of businesses as well. Okay, so I talked about some of the benefits of open source technology just now. And to build on Clare's point earlier, I think we're faced with so many global challenges today, whether that's climate change or pandemics or other problems. And they're so big and urgent that I think open source technology is what enables the inclusive and rapid innovation needed to address these really urgent issues. And to bring it back to my earlier point, I truly believe that we simply don't have time to be alchemists anymore. We cannot afford to be alchemists. And I think this is a huge motivator for why open source is so important and critical to open research. Now, with all of that said, here actually comes what might be the most provocative part of my talk today. So, you know, again, we've seen so many motivations for open source, like the collaboration that happens, faster innovation that's so critical to solve problems of today, the lower costs and business opportunities, and so many other benefits, right? But I feel they are just the tip of the iceberg in terms of why open source is so important. And there are some underlying values that I think really adds a lot to the value proposition of open source. In my view, that could be things like the autonomy and agency that we can have over the technology that we use and the freedom to use it for our purposes. And I think these are the things that also underpin why open source is so important. Dr. Julieta Arancio is a researcher of open source technologies, and I think she characterizes it really well, where technology really affects the way we think about research questions. And when a piece of technology and the tool that we use is closed source, it means that rather than being enablers of our creativity, we end up doing what the available tech lets us do. Because the people behind that technology gets to dictate what you can do with that technology. And what that means is, in this context, is that closed source technology also implies a certain kind of epistemic power behind it in t