I'm just visiting Taipei for a few months, been here about six months, I work as a data scientist in San Francisco and my partner and I were planning on traveling to Taiwan for a little while and then like COVID struck and we ended up getting it coming here on the go-kart visa so we've been spending, we took some time off and now I'm working remotely. And I was just like reading a lot about the digital democracy efforts that you've been meeting in Taiwan and I wanted to ask more about that and understand it. So in particular I was curious about V-Taiwan. Which is weekly meeting right here. Okay cool. Yeah I guess like one question that I had for starters is, I looked at the website and it seemed like a lot of topics hadn't been updated recently is it still active, still going on? Yeah it's still active. Recently they've worked with the open parliament people on getting the national action plan from the parliament side of open government out. There's also a recent discussion about social enterprise related acts and so on. I think there's going to be one about like shared, I don't know, U-Bike or shared E-School terms or something, but I don't run V-Taiwan day to day anymore because I've become the additional minister in 2016, October and then I just handed the governance, the leadership of V-Taiwan to other people in the GoPierre community. But we've taken the V-Taiwan inspired model and installed a roughly equivalent structure within the central government called the Participation Officer Network which primarily oversees for example cross-ministerial repetitions on the joint platform. Yeah I might take those. Sure of course go ahead. Cool. We're going to be on the record anyway. I'll take notes anyway so it's like. Are the meetings open to anyone? Sure of course. Okay cool. I just dropped by. You too can't drop V-Taiwan. Okay cool awesome. And then what are you, so I think there was a paper published in 2018 about the process and I think at that point the major initiative that had gone through the process was the Uber regulation. Yeah. It had to be like Marines. Yeah. On my liquor sale and so on. Okay yeah. I guess maybe you're not the best person to ask but have you had any like learnings about the process since then? Like things that have been successful and things that have been most successful. So V-Taiwan had a very narrow mandate in that only emerging digital economy related issues could be deliberated. And this is fundamentally because it's a self-selecting, self-electing process right. People who find time to contribute set agenda through crowdsourcing. But if we apply this to item of marriage equality or some other domestic issues that are unrelated to the digital then the self-electing nature of the V-Taiwan community could be a problem because there really is no balance in including the stakeholders on the less digitally connected parts of the society. So it was a pilot, it was an experiment. And so it was quite successful in tackling the issues where there's no or almost no traditional representation. The first few cases for example there was no unions of tail workers, there was no unions of gig economy. Nowadays of course there are but back in 2015 there were not. There's no business association of all the start-up of the registrar came in islands. So there's no traditional councils or associations or heads of representative trade councils and so on to talk to you. But we need to regulate that anyway. So it's easier because there was no better alternative. But in more traditional politics where there are like the existing entrenched representatives, this methodology wouldn't quite work as is and it needs improvement specifically taking into the account the face-to-face component of deliberation. Yeah, that makes sense. Do you have plans to expand it to other areas like an increased participation? Yeah, it's already done. But the joint platform as I mentioned accounts more than 10 million visitors, I think consistently millions of visitors every month. So it's almost half or probably already over half of adult population in Taiwan, which is actually not the whole story because one quarter, more than one quarter of petitions there were started by people who were not even 18. So now adults also play a big part there too. And I think that's fundamentally where we're going because instead of having the 16-year old, 15-year old thinking that they have to wait a number of years before they participate in the democracy, why not just have them set the agenda through petitions. So we've already expanded that quite considerably using the joint platform. Yeah, that makes sense. Does the joint platform, is it based on bolsters or is it your own platform? Yeah, each joint deliberation can choose a different set of technologies, but the petition side is our own platform. But the design is from Iceland, from Betere Kavík, and where each petition, once they collect 5,000 signatures, get a point-by-point response by the ministries.  So you can ask vote and downvote, but there's no way for troll to grow. And that's very balanced. But if it's cross-ministrial issue, like if it's a white disagreement even within the government about how to define the same, well, we usually use polis in a way to crowdsource the common values out of those, they're very different positions. That's right. Yeah. How do you authenticate using it on a platform? The people registered it like they already do. The joint platform uses SMS. Okay. Yeah. Okay. Oh, interesting. So just you have to have a time when you use number. Well, if you get like 50,000 or just 50 SIM card numbers, the anti-money laundering people will be out here anyway. Yeah. It is actually quite expensive to get a 50 SIM card without getting notified. But some people have two or three phones, that's fine. Yeah, that's it. Okay, cool. Yeah. And then let's see, so have you noticed like as you scale this like any pain points or any issues with, it sounds like access is really good. Yeah, sure. Broadband is human, right? Yeah. Yeah. And are there any other learnings that you have from like the, from the past like two years or like four years, like since you terminated the joint platform? Yeah. I think people really, really like to set the agenda by themselves without the government setting the agenda to discuss. The only exception seems to be like really early stage as a general setting. For example, when we ask people what do we need to do when we're opening up mountains for mountaineering, for hiking and things like that, there are of course competing values at play about natural preservation, indigenous nation preservation and things like that. But also better access also translates to more people care, right? And that's one part. There's also a part about opening up the oceans like professional fishing people and amateur fishing people. And these are like different profiles. And sometimes they see things as zero sum, but actually with education, many people can understand the oceans more and so on. So for these like really broad, like there's no fixed set of solutions, issues, then it's a little bit like the digital issues that we have used to tackle in that the crowd sourced feelings and the crowd sourced like general narratives from personal perspective start to become very valuable. But if this is just one predefined trade off between existing value like one value versus another, then there's less chance for the Polish or any crowdsource approach to work, which is usually a later part of the stage. So citizen initiatives or early enough stage conversation where it's about feelings and values that you seem to draw the most number of people. Yeah. And do you find like special interests like tend to be more or less represented? Because I think like, so one problem we have in the United States is that a lot of policy that's not at a community level is done by like in person meetings. And like just to get to these meetings, like oftentimes I might be held like during the day or like at an inconvenient time or convenient place. And so people who are working can't attend them and like maybe people who are retired or represented or something. Do you find that like having the online platform improve? Like does it increase the presence or decrease the presence of special interests in the decision making process? Yeah, back when V-Taiwan first used Polish, I think the first UberX case really gets a lot of people loving this way or another. But once we resolved out and saw the common values, the next one we tackled was Airbnb. And interestingly, Airbnb said they set an email to all its Taiwanese members asking them to go to Poland and advocate the Airbnb position. So I guess with asynchronous modes of communication, there's more opportunity for this kind of mobilization to go on simply because online mobilization takes less effort, right? But much to I guess Airbnb's surprise, only about one third of the members they mobilized actually agreeing with the Airbnb position because Poland is very high bit rate. It's a crowdsourced like weekly survey. So if this is just a yes or no question, maybe Airbnb would have succeeded in mobilizing the people. But when people go to Poland, they see very nuanced eclectic positions.  Of course, that's not the case. Right. So so people still have like legitimate improvements that they really want to see, even if they have already lived in Airbnb for a few days before. Right. So I think more than two third actually offered constructive criticism to the Airbnb position, even if they actually given that they're mobilized by Airbnb newsletter. I don't think special interest is that big a problem because people are given much more bit rate to express. Yeah, that makes sense. And just in general, like, what do you focus on these days if it's not like running in Taiwan? Like, what do you mainly worry about like in the past like month? Well, counter-infodemic encounter pandemic has been a focus for the for the past year. It's been quite a bit of time with good car holders, actually. Simplify in the process. So are you a economic affairs or science and technology? Economic affairs. Economic affairs, right. So, yeah, the science and technology ministry just relaxed massively last Christmas so that anyone with the potential to contribute to science or technology are eligible, which is pretty much everyone. Yeah, because I applied on the science and technology track and had to wait for my application to be rejected, which took a month because I guess the past year. Yeah, I know, I know. Yeah, and most of the most gold card applications end up finding that MOEA is easier. So and most change that last Christmas. So it's a bit of a friendly competition. So I think, yeah, what we're seeing now is that Taiwan is becoming a much more transcultural place so that people are based in Taiwan but working on international projects. So the presidential hackathon, for example, we've seen record number of people who were not based in Taiwan, but nevertheless participate in the presidential hackathon. So I spend a lot of time working on the presidential hackathon and also similar hackathons like the Kohak and so on, which also use Polish to crowdsource norms that's acceptable around data for fighting Covid for the five countries participating. And we really get some pretty good like the contact tracing apps that generates one time link, but that's not actually report or you're aware about anywhere outside your phone or things like that. Yeah, cool. That's really exciting. So have you found success in like introducing like I think I think also like like you mentioned, you're working on rebuilding some government websites and properties with with more modern technologies and also introducing some crowdsourcing. Oh, yeah. Yeah, that's right. So it's like, I guess what it would have, your findings been in that area? It's kind of an open-ended question. But sure. Yeah, we run the RAID project, RAID being rescue action by youths. So RAID.pdls.tw, the RAID project for fourth year now. We're about to begin the fifth year where we ask for interns usually like younger graduate level, but also higher undergrad level to dedicate two months of their time, three people at a team to look at any government website that they don't like and change it for the better. And the first couple of years is all about the charts. The first year, the interns did nothing but fixing websites so it works not in an IE only way, which is good because the Microsoft deprecated IE right afterwards. And the next year all we did was to ensure responsive web design. So it works on phones of all different widths, right? But after those two, like very infrastructure work, the third year see, for example, the hiking portal where if you go to hike in Taiwan, depending on your trail, you will have to apply to like up to four different agencies, each with their own website. So we use the open API spec to make sure that existing websites are turned into API endpoints. And then the interns build this single portal Hike.Taiwan that can just plan your trip. And because it's API based, so an ecosystem of apps and so on. Additional services build upon those APIs. Later on, we'll repeat that for Ocean.Taiwan. And then last year they started working with municipal government. So the main lesson is that if the career public service can see the young people as, you know, once bringing gifts, almost like reverse mentors instead of just criticizing them, right? So they can see this partnership as really good in terms of time saver. They don't have to like debug their website anymore, right? Anyone who see something wrong also suggests something better. It decreased the risk and it also improves mutual trust. So much so, I think we don't have the allotted quota of interns anymore for this year's rate because many other municipalities and government ministries start to think about interns as teleworking interns. And so all of them actually want more quota because they see that this is actually a great way to improve the digital service. Yeah, what technology stack do you use in the government? Is it kind of all over the place, like depending on what website it is? We strongly prefer OpenAPI, like the Linux Foundation standard, the speedy open source manifest. And I think that the point is that as long as you speak OpenAPI, that all human interactable parts, whether it's mission writable or mission readable, has an API equivalent. We don't quite care, which technology is that you use because then it's trip like a Lego block that other services can apply into. And so the OpenAPI stack is actually piggybacking on the universal accessibility track, where if people contract a government website and a vendor says, oh, I can do this for people with side, but not with blindness, they could be disqualified for discriminating against people with blindness. So we piggyback on that and say if you deliver a website but you don't speak OpenAPI, well, you discriminate against robots that could be disqualified. So that's the thing we insist on. OK, that makes sense. Do you have like, maybe I could have figured this out already, but do you publish a lot of your government websites as open source and GitHub or GitHub? Yeah, sure, sure, sure. Our GitHub repo is PDIS. PDIS, OK, yeah, I think I've seen that before. That's awesome. And then so I guess you also focus a lot on like fighting disinformation in Taiwan is basically just like fast, like I guess like the strategy is like fast response to disinformation specifically around COVID. And like, I think, I think like using memes and humor to discredit information and disinformation. Yeah, like, has it only been for COVID or you've also been fighting disinformation? It's for general purpose. So the COFACTS project of Dev Zero is one of the first team to use wiki like dynamics so that when people flag something as fun or potentially disinformation on even into any encrypted channels like line, it gets trending on a dashboard. And then the COFACTS people can just wiki crowdsource the most viral ones, the ones that have an R value above one, so that the fact checkers can concentrate their energy on one because each day there's only this much of mental bandwidth of the population, only this many disinformation will trend any particular day, right, because it's competitive space. So if we focus on inoculating only the trending ones, then we don't waste our time working on the ones that will probably not be trending anyway. So the dashboard is also important. The economic sector, for example, Trend Micro, Taiwan's leading antivirus company also have a what they call a farm jada, a disinformation buster, right, that also works on this area where you can invite a bot into your online chat channels and it just scans each incoming message and just post our clarification if it detects scam or disinformation. Another startup called Husqa also offers a very similar offering called Meiyui and so on. So there's an ecosystem about it now. Cool, awesome. And have you extended back to the like some of the work we've done with like introducing more technology government, have you like seen any challenges or pushbacks or like any like kind of stumbling blocks and getting wider, I don't know, like more and more adoption of open technologies in government? Yeah, most of all, I think the fear and certain doubts seems to be centering around cybersecurity, because when you use open source code, you implicitly let random strangers upgrade your system, right? And that's not a very good position to begin. So literally the first thing I did when an institutional minister has to recompile the Linux kernel so we can run secure Linux and run a security product called Sandstorm so that even untrusted applications could be run within a container that deflects or mitigates pretty much all the XSS and other attacks and so on. And we got the Devcore team, which I think second place in Devcom CTF to do penetration testing until they say Sandstorm is secure, right? So that's what we do, just to have a sandboxed security perimeter and also run penetration testing. So the Polis system at polis.gov.tw now is also public digital infrastructure, even though it's open source, we also do penetration testing and things like that. Yeah, yeah, gotcha. And so it's the most of the technology used for kind of web-based running in Sandstorm? Yes, sir. Yeah, and OK, interesting. And we use that for all our transcripts and things like that. Yeah, yeah, like do you use like, is there like a Google Docs equivalent, I forget? Yeah, sure, we use CodeEMD, which is the open source variant of the time you start up Hack time fee. OK, gotcha. And then, I guess like another question I have, are you involved in the digital ID card project? Mm-hmm, yeah, sure. Yeah, and I guess like what are the goals of the Taiwanese digital ID cards? Is there like an eventual ambition to allow people to vote, for example, using their ID cards? Well, at least for the e-collecting, yes. And currently, we already have a PKI card, the Citizens Digital Certificate, or the CDC. The thing is that the CDC only maybe has one quarter of people who have ever used it once. The active users is even smaller, and mostly because the CDC really isn't used much in other than paying taxes and so on, right? So the CDC has a way to authenticate oneself is going on, there's nothing going to change about it. The main idea from the Ministry of Interior is that since we already have a paper-based ID card and a PKI-based card, the CDC, maybe we can ship these two cards in the same form factor so that more people will have access. Of course, that also raises a lot of cybersecurity issues because for the paper-based card, sometimes people, when they go to a parking lot, they just exchange this card for a coupon of the parking ticket. But if this is a CDC, if this is a digital certificate, then that opens a host of attack services and so on. So people understandably, and with the more experience about the health ID card, which is universal last year, people demanded that maybe we need Estonia to have a specific act about the norms of what to do, what not to do with a universally issued Citizens Digital Certificate. So we're now working on that act. And if it's passed by the legislature, then there could be real consequences for parking lots or hotels, insisting on having the photocopies of your ID card. Yeah, or explain sports centers, I guess. I know. It's like a rapid or something. That's right, that's right. I mean, if people ask for your photocopy of the backside of your credit card, you'll probably flip it out, right? That's true, yeah. I guess even the Justine ID has a lot of... It has some information, and I don't know what's on there, but it's probably information That's right, exactly, exactly. So we improved that design, but people said that at regulation level, like what to do, what not to do, doesn't really carry any penalties as such. And so people want to do a special act for it, so we're working on that act draft. Yeah, yeah, okay, cool. That's exciting. And then, I have another question here, but I heard you. Sure, sure. Where did you write it down? I guess, I had like... That's fine. That's fine. I think you're also working on promoting digital innovation in Taiwan, and just like trying to bring in more... Like what are you doing in that area? I think it was the goal, especially the gold card, to bring in more entrepreneurs and people to start... People who are here for the, I don't know, food in broadband. Hiking and surfing. Yeah, yeah, yeah. And frankly speaking, we are not saying that the gold card holders need to be forever staying in Taiwan, but we do want to share our experience in both broadband as a human right and also digital competence as a basic education curriculum plan to people in the world, so that when we fix local problems like the infodemic and the pandemic, the Taiwan model can also be shared with the gold card holders and through them to the international community, how to tackle the pandemic with no lockdown and how to tackle the infodemic with no take-down and offering our model as a preferred, at least more democratic model that other liberal or social democracies would like to partner on. So this is a more Taiwan can help approach in international health, I guess. Yeah, that makes sense. And like, what else are you doing aside from the gold card program to promote innovation? I guess like, I don't know a lot about this they have a general purpose inbox. Yeah, I haven't tried to start a company in Taiwan, but I guess like, my friend who started a company, I think in the hardware space, primarily they were saying that, for example, it's harder to incorporate a company in Taiwan, like it's harder to incorporate an LLC than like, in the United States like, you can do it in like half a day or something, but I guess it's like a multi-week process here. Yeah, we've shortened that, I think it used to be a like physical face-to-face process for most people. It could now be done online, but I'm not pretending that something like the Stripes and you know, click here to start a company. A company starting as a service exists in Taiwan. Currently, probably the whole process still takes a few weeks. I think up to four weeks if I'm not mistaken, but at least it's quite streamlined. And we have a like startup help center and actually the northern startup lab center is actually just across the aisle, it's actually that building. So you can go to the startup hub and they'll walk you through the process. Yeah, and a lot of technology in Taiwan is hardware and it feels like the software community is more nascent. There are like some Taiwanese software companies, but it feels like there aren't many big brands that are like kind of well-known outside Taiwan. Well, there are two business accounts, right?  Yeah, yeah, yeah, yeah. Yeah, it's like less like consumer brands. They don't say power by trend micro, right? Yeah, right, right, right, right, yeah, yeah. Okay, I was just curious about that. Sure, sure. That's most of what I wanted to ask about. Yeah, I'm just curious about, let's see, with the pull of stuff, because I know the pull of stuff was created by some guys in Seattle. That's right, that's right. They're now pivoted into a foundation, I think it's called math and democracy. Yeah, yeah, yeah. Yeah, I'm not sure if it's actually being used, it's been used in a few other places around the world, but I'm not sure. Yeah, I'm not sure, but have you liked it? A ton of it in Denmark. The Canadian government did a French translation and bilingual interface. Singapore used it for use engagement. There's quite a few users and our contribution in penetration testing this and so on also bolstered the government's support from other parts in the world because they now know that it's more cybersecurity hardened. Yeah, yeah. And then I guess like, I guess ultimately what I'm asking about this question is because I think it'd be interesting to introduce some of the same ideas in the United States and work towards some of the same causes. It's been used in Bowling Green Kentucky, at least. Yeah, oh yeah, yeah, I think I remember hearing about that. Yeah. Yeah, I guess like one of the problems is or like Taiwan is a little more I think dense and homogenous and it's just like smaller in general. The United States is like very big and I think one advantage I guess of Taiwan is that like if, I don't know, like if you're having an argument with someone in Kaohsiung like you, you could, you chance are you've been to Kaohsiung because it's only like a few hours in the train. But you can say that in many of the smaller states like New Jersey. Yeah, I guess like in the United States things tend to get nationalized. Like that's the, for better or for worse like media is like very national now because a lot of smaller media companies can't continue to compete. So they have like big national brands like the New York Times or CNN that have more of a national focus. So a lot of people's news also has a national bent to it. So people tend to get very involved in issues that are actually kind of like not even directly affecting them. Yeah, but from the Bowling Green experience I think the rough consensus of people like putting art into STEM education like diversifying the broadband choices and things like that are decidedly local. So I think it's just a matter of airtime given. As I said, the national media of course focus on national issues. I would argue even the more anti-social corner of social media like on Facebook and so on. Also the viral memes tend to be national or even international in focus. But if you look into the more pro-social corners in Taiwan, of course we have the PDT which is the equivalent of Reddit by it's run by the social sector like literally National Health University student pet project. And because they don't have shareholders or advertisers naturally the local issues like the policy in Kentucky, Bowling Green surfaces up and people discover the more pro-social aspect of things. So I think there's a lot to be done if you use the keyword digital public infrastructure. You'll probably see quite a few communities working on to recreate the experience of town halls and public parks and public libraries and so on. But in the digital space. So we don't have to deliberate about our agenda putting arts into education or diversifying broadband on the digital equivalent of the Nile Life District where there's private bouncer selling addictive drinks which is Facebook. So that we can talk public infrastructure that are also digital. Yeah. I was just like a sign up. You mentioned PDT I spent like a while trying to sign up for an account and I had to go because I think. It's open only to NTU students. Oh, okay. That's why it's literally NTU project. Okay. I thought it was like anyone in Taiwan but then I try to sign up and they like need like it. Yeah. I think you need like NTU. Cool. And so I think that's most of the questions that I had. Is this, I think you're changing the format that the office hours going forward, right? That's right. So starting next month only registered social innovation organizations can book at a time. And mostly it's because the accountability also matters. When people walk in, I want to understand that our conversation is for the betterment of the public good. And if someone is registered as a social innovator then at least once a year they have to publish a public account of them doing that. So it's a threshold that's actually not that hard. So if you complete this 30 days startup creating process and also register on the social innovation platform. Yeah. All right, yeah. I think it covers all the questions that I had. Yeah, it was nice meeting you. Cool. You're still, like I said, we can wrap up here. Unless you have any questions you wanted to ask me. Well, yeah, are you in touch with the timetablecar.com community? A little bit, yeah. I haven't contacted any other meetings yet but I would mainly to go to some of them. But yeah. There's a digital community. Because they put something very much like the rescue action by youth. Because the original go-kart website from the government was so horrible they just created a new one on GitHub. And then they get invited by the national government council. So now go-kart.nat.gov.gov is actually co-created by those forks. So the work gets merged back. And I think we really need more people doing that. You asked about how to foster innovation. That people systemically forking the government I think is one of the best ways. Yeah, yeah. Yeah, that's really cool. Awesome, well, anyway, yeah, it's great to meet you. I'm a Shakespeare fan for, I guess, the pandemic, so. Yeah. Yeah. OK, really good questions. Yeah, thank you. Thank you. Have a great day. Yeah.


The Economic and Financial Crimes Commission, EFCC, says it secured the convictions of 3,328 in court between January to November this year. This was disclosed at a one-day workshop on financial crimes reported, according to the Zonal Commander of EFCC, Ms. Nganeka Ngokike. The number of convictions by the Commission is on the rise. She said the anti-corruption campaign requires concerted efforts. The authors figure out the interior for future of 40 assets in Nigeria, United States of America, London and Dubai, belonging to commanding extended president E. K. Burma. Two is failure. An undercourt issued a final for future order of two parties, stated in Abuja, belonging to the Zanyarist in Mahdakeh, commanding the self-proclaimed resources. These are just a few of the assets covered for federal comment of Nigeria this year alone.


Okay, so this is slightly weird. I feel like I'm talking into space. All right, so I'm Liz Rice. I look after open source engineering at Aqua Security and I am the author of a book about container security and I am currently the chair of the Technical Oversight Committee at the CNCF. And despite my extensive technical qualifications, it took me a little while to figure out how to get this session to work, but I think it's, I believe it's working now, so that's good. All right. Okay, so now I can find the Q&A button and my impression is that if you have questions you'd like me to answer, you can put them into that Q&A session. All right, I hope everyone is coping with this platform better than I seem to be. I think I'm okay now, all right. Okay, so I have a question. What's the best thing I can do to make my containers secure? This is the kind of thing that I could talk about all day. So there are lots of different stages to the container lifecycle and there are things that you can do to improve security all the way through the lifecycle. But I would say if you only had to do one thing, I would recommend scanning container images for known vulnerabilities. There are plenty of vulnerability scanners available out there. You know, some of them are commercial products, but there are several free and open source options. Open source container image scanners include Trivif on my team, Ankor have a solution, there's Clare. So there are a few different options and if you use a container image scanner you will pick up when your images contain known serious vulnerabilities. So that prevents you from deploying something that is known to be very insecure. So because it's so simple to build something like that into your CI CD pipeline, that is high bang per buck, it's very easy to do and it makes your deployment much more likely to be secure. So I hope that answered the question. I could talk about some other ideas for things that you can do to secure your containers. Not running as root, so I'm about to do a talk. I actually prerecorded the talk, but very shortly my talk will be going out about rootless containers and most of the time as you'll see in that talk by default people run containers as root. That's the kind of default setting if you like and root inside the container is the same as root on the host. So if there were to be a container escape if somehow a container got compromised and someone was able to escape from that container, perhaps there's a vulnerability in the container runtime itself, we've seen a few of those. If some like to happen, I don't wanna scare anybody but if it does happen, if you're running as root inside the container, you escape the container, you are root on the host, this is a bad, that's a bad situation. So that's kind of game over for your security on that host. So the fact that you're running as root is something you wanna avoid. Rootless containers is one option. Configuring a user. So in your Docker file, setting a user ID or in your YAML as you're configuring your pods so you can define a user ID that you want to run under, make it non-root, that will be more secure. What do I love about working in open source? That's a pretty cool question. So I think the thing that I like best about open source is the feeling that you're interacting with people from kind of all around the planet, people that you've never met, get some value, something out of something that you've built and then they get in touch or they contribute to your project and they give you the benefit of their wisdom on their time. And that's super rewarding, I think. The fact that you interact with people and you feel like you've given them something or they've given you something and it's, everybody is raising each other's game. I think that's probably the thing I like best about open source. Plus everybody always seems to be so friendly and welcoming. I'm missing meeting people in real life at events and meetups and so on. So I'm looking forward to getting back to that when things get a bit more back to normal. Ah, very nice question here. Complimenting me on my keynote yesterday, thank you. Looks like I work on a lot of great things, any advice for attaining work and life balance. I've got to say that's probably something I wouldn't consider myself brilliant at because I do have a bit of a tendency to commit to so many things. But I do carve out time. I spend quite a lot of time doing sport, doing training and I kind of set aside time and try very hard not to let anything encroach on that. My husband's very good at making sure I eat regularly, which is probably a very good thing. Yeah, I think maybe setting boundaries around the time. I try very hard to avoid making a regular commitment to evening meetings because I think it would be all too easy to fall into a world where your day stretches from eight in the morning till 11 at night and I don't think that is a long-term path to success. So I'm pretty protective of my out-of-hours time unless there's a really strong reason to do something out of hours. Technical question again, okay, are there some containers that have to run as routes? And there's an example of needing to open a low numbered port. So yeah, there's a lot of software that has been containerized that was originally written in the era before containers designed to run on a host. And normally, if you want to open a low numbered ports, you need privileges to do that and those privileges come if you run as a route. So you would typically run a web server, for example, or load balancer. You would typically run that as a privileged user because you needed the privileges on the host to open the low numbered port. If you're running inside a container, that is less of an issue because you have port mapping. Your code can be running, thinking it's talking on port 80, but that could be mapped to any port outside of the container. So that's no longer a good reason to have to run as route. So although a lot of software expects that it needs to run as route, it can usually be reconfigured to run on a different port. And there are some collections of container images. For example, bitnami did a lot of work to create versions of well-known popular images that can run as non-route software. So although you may find a lot of official images that do expect to run as route, there's usually a way that with a bit of work, you can find a way to run as a non-route user. Okay, along with AQUA, you work closely with the CNCF. What types of things do you work on with them? Yeah, so mostly the work that I'm doing with the CNCF right now is with the Technical Oversight Committee where we are with a group that sets the technical direction for the foundation. In practice, a lot of what we're doing is assessing projects that want to join. And in practice, in order to assess projects or help them move up the maturity scale from sandbox to incubation to graduation, then we actually spend quite a lot of time thinking about the criteria of what it means to be a graduated project and trying to figure out how we can scale those assessments and judgments. We have a lot of projects that want to join, which is fantastic, but we're a group of volunteers with day jobs as well. So we recently, well over the last year and a bit, set up special interest groups within the CNCF that can help the TOC. So we can ask these special interest groups in say storage or security to help us with some of the technical assessment in particular projects. And that helps us kind of share the workload, which is really helpful. It's helping run an open source project different, easier, harder than leading inside a big company like Aqua. So Aqua's not that big, we're about 300 people. So I mean, it's not tiny, but it's not like an enormous corporation. I think it's very different. I think if you're inside a company, a company will have particular commercial goals typically and defining those goals kind of top down. I think that's usually the way that most companies operate, sort of have a top level goal and then that rolls out into goals and KPIs for teams and individuals. I think in open source, while you do still have collective goals, it's less, it's much more collaborative and much more kind of, you know, nobody's really gonna get into a huge amount of trouble. It's more about trying to find cooperative ways that where everybody gets something out of the contributions that they're making. So I like to think that internally in a company that's also my management style, that I'm not kind of cracking some kind of whip and trying to get people to do that. I hope that, you know, if we have a group of rational people and we all talk about what we want to achieve, we will come up with a sensible way to achieve that together with our skills. So in that sense, I like to think that you can manage in a commercial organization in a similar way to what you do in open source. But at the end of the day, it is slightly different in that you have these kind of, the different incentives and the different goals that you're ultimately trying to achieve. They can be complimentary though. And I'm lucky that I work for a company that allows me to spend time on open source and values the work that we're doing. And we do it in a way that we, you know, is complimentary to what we're doing as a commercial organization. How did I get involved in open source? So kind of almost by accident, I think. I actually remember years and years and years ago when I first came across open source being quite dismissive about the whole idea because I thought, well, how on earth can a team of volunteers possibly do a kind of real professional job?   Of course, that's not true. You know, over time, I realized that that's not true. But that perception years ago put me off for a while. And but the way I got involved was really working with startups. I spent a few years working in and co-founding startups that mostly failed, but, you know, learned a lot along the way. And in a startup, you're constantly trying to show people what you're doing. And I learned that I really liked kind of presenting things. And my sort of engineer inside me wanted to show people technical things. And I realized that, you know, there was this huge community of people who were interested in having these sort of technical conversations that you could show them a thing and they'd go, that's really interesting. Let me tell you about what I've done that's related. And that kind of sucked me in. So it was more through the kind of community events presenting that I got involved in the world of open source. And that made me take the whole the way that open source projects work much more seriously. And I got much more interested in it and ended up making that kind of the focus of what I do as a job. Can I talk about Kubernetes security posture management? So, yeah, this is really it relates to I think it's gone. I have a, I can't remember what they call it, a term called cloud security posture management, which is the idea that when you set up your cloud infrastructure, there are some best practices you really should be applying, like putting permissions on your storage so that not everybody on the whole internet can just go and look at your data, making sure that you have multi-factor authentication setups to secure access to your console. And CSPM cloud security posture management is about tools that check that you're applying those sort of sensible security practices. So KSPM is applying that similar thinking to Kubernetes and saying what are the sensible settings you should apply, not just to your Kubernetes configuration, but also to the way that you're running your containerized workloads in Kubernetes. How can you configure them in a way that's secure? And KSPM tooling is really assessing your YAML files, your configuration and saying, is it applying these security best practices? What do I enjoy working on the most? I'm a bit torn there between, I mean, I really, really, really like creating content explanations, typically talks, and getting the sense that somebody has understood something because of the way I explained it. And when that lands, when somebody comes and tells me that they figured out how containers work, they understood it because they saw one of my talks. I think that is the thing that I find most rewarding. It's definitely that kind of sense of achievement when you feel like you've done something and other people appreciate it. In projects that you've worked on, do you have any what not to do lessons? Oh, how long have we got? I think so the first thing I would say when I first got involved in open source was worrying too much about perfection and thinking that if I put code out, people would look at it and find all the flaws and think that I was a terrible engineer. And in practice, anything you can publish, people don't really pour over it in very great detail, but also, everybody who's ever written any code knows what it's like to improve it and that it never really feels completely finished and that you're always wanting to make it better. So I think getting over that idea that it's not good enough, it is good enough, ship it, get it out into the world and see whether or not, how people react to it, that would be, so the what not to do would be don't hide your code and try and polish it too much before you show people, get feedback early. I think another thing that we're learning about a lot in our own projects in Accra is trying to figure out the way to be helpful and welcoming to community members. There's been a lot of great talks about that today and other events in the past where we talk a lot about community and making projects accessible for people to help out and get involved. And actually, the reality day to day is, oh my God, there's so many things coming in on GitHub and how can we answer them all and how can we make sure people aren't frustrated because we haven't responded to them in a timely fashion. I think that balance, making sure that we're doing work and also responding to other people's work in a timely fashion, I feel like that's something that I'm still trying to get to grips with what the right balance is there. Okay, I think we are pretty much through all the questions. Thank you very much everyone who asked some questions. Appreciate that. If you are still online, the next thing that I would love your feedback on is my talk on rootness containers that's coming up at quarter past the hour, so in three minutes. So I might go and take three minutes to, since I don't see any last questions coming in, I will take those last three minutes to go and grab myself a cup of tea and hopefully answer some questions while my talk is streaming out. So thank you very much.


Thank you for joining, we're going to be going over the highlights for the Challenge Week for the DNA Chef, Mellie Alexander. Welcome Mellie. Thank you. And we have Mellie here with us, one of our volunteer researchers. And Celia is also on audio for us here, so I'm just going to go ahead and share my screen so we can get started on the highlights. We'll do that real quick, there we go. So just to briefly explain what the WikiTree Challenge is, it's our largest ongoing community event. Every other week, volunteers collaborate to grow seven degrees of connections for a special genealogy guest star. So this week is all about Mellie. So for the week we have what's called a free space page where we use it to collaborate on all your ancestors and your family out seven degrees in every direction that we could go. We use Discord, it's a real-time chat application to also do a lot of collaboration. So we'll start off. Let me take you first through an explanation real quick what CC7 is. You'll see us say that a lot. And it is basically a person's number of connections on WikiTree within seven degrees of them. So that's any type of family relationship, including relationships through marriage. So the degree measures the distance of relationships. Nuclear relatives, for example, parents, siblings, spouses, and children are one degree away. Grandparents, aunts, uncles, nieces, nephews, in-laws, grandchildren are two degrees. So they are connected through two relationships and so on. So that's how that works. So the higher your CC7 number is, the fuller your branches and the tree are. So just taking you to your profile on WikiTree. When we first started, the CC7 number was 660. And today you can see right here it says 2,245. So you got two new badges on your profile, the CC7 1,000 connections and the CC7 2,000 connections. And they were, we hit 1,000 connections pretty much the next day after the challenge started. It was like pretty soon. And then the day before the challenge ended we hit 2,000. So. Wow. Yeah, it's really amazing, really. So you'll see on the score sheet that we have, where we track, you can see all the, let's see, I think I passed the score sheet here. You'll see all the different WikiTree volunteers that worked on your tree. Okay. Wow. Yeah. So you can see we increased it 2,227, I think it's up a little bit more now just because people kind of still work on it. Okay. Even after the challenge ended and so 849 profiles were added to your tree. But there were already some people on WikiTree. So when a profile is added and then connect to one that was already there, then it expands even more. So that's why there's that big growth, the difference between how many connections you got increased versus how many profiles were added. Wow. So many people. Yeah. I got it. So a really nice graphic we have from an app that's available on WikiTree is called the seven degree or six degrees app. And what it does is it shows you in this graphic form, these are all the connections when we started within seven degrees. This is what it looked like. And this is what it looks like now. You can see it really jumped way up. Yeah. Well, when we first saw it for our challenge for American ancestors, I think we joke we can make this into some lovely, you know, some like almost like placemats and dishes or something. Think about that. You could have your CC7 on your, you know, your permanent dishes or something to keep with you. Put it on your wall. It makes me think of one of those braided grugs. Yeah. Yeah. Yeah. Exactly. It's almost hypnotic, hypnotic, like looking around it. I mean, it's gorgeous. It's beautiful. I just can't believe that these are all my people. It's like, wow. Yeah. Yeah. And the more connections, the more profiles that are out there, the more connections that are out there, then those are places where other people can then come to WikiTree and connect in. Wow. My God. It's never a permanent number. It'll go up anytime someone wanders across and makes a connection. Yeah. Yeah. It's still gorgeous though. Wow. And then the next one we want to show you for a graphic is this is within seven degrees of you. This is the migration patterns basically of the people connected to you. This is where they all went. Wow. So this is a static image, and we'll get these images to you. But if you ever want to explore it, I'll send you the link for this too, but we have WikiTree Plus, which allows you to really delve into the database on WikiTree. Okay. So when I'm, I just put in, show me seven degrees of your profile ID here. And then if you click this WikiTree Plus map right here, that's what takes you to that map of profiles. So it's even a little bit different now because that snapshot I took of the map was right after the challenge ended. So there's even more profiles now. You can see all over and then with the WikiTree Plus, you can zoom in then into. I believe that that dot that's confusingly off the coast of Africa is an unknown or no location. Yeah. So that's not an actual. Yeah. But yeah, you can, you can zoom in with WikiTree Plus. You can zoom into these locations and really get down to, you know, street level basically of them. So yeah, it's a lot. There's a lot of tools that you can use with the, with WikiTree, the database. So it's a lot of fun to explore. I had no idea there was a map and especially something that's so interactive. Yeah, like delve into like specific towns or cities. I just, yeah, it's just I'm seeing, you know, a lot of the European ones and I'm kind of familiar with already, but to kind of get more specific towns would be really cool to really do more research with. So it's, yeah, it's incredible. Wow. I had no idea. Yeah. The red dots are birth locations and the blue dots are death locations. Okay. That's good to know. Yeah. Cool. I'm just like. Yeah. There's a lot, a lot of tools to play with on here. Okay. Yeah. It's like I could barely see it without my glasses because I'm on my phone right now, but yeah, I'll go into a bigger computer and like really play with that map for sure. Yeah. That's going to be so cool. Yeah. And we'll, we'll, like I said, we'll send you the link to that query so you can kind of play with it. Okay. Cool. So on the space page that we talked about, we have a section where we ask the volunteers to share, well, where are they working? Where, where did they go? Where did this challenge week take us? And so we have six provinces in Canada. And then we have a whole bunch of different countries. And we have 29 states. Cool. That it went to you. Yeah. Wow. Kind of a list version of what that map shows you. Okay. And then we have tell us, have, we asked them to tell us any interesting finds that they, they found out. And so there was a whole section on the different. Maybe one on social media. That was it. Yeah. That was really cool. By the way, I appreciate that Melanie. It's like, you don't want to take this webinar. Oh, that was, that was about my other subtle hint though. Yeah. That was so cool. So there's quite a few. You'll want to go check that out when, you know, when you have some time to spend looking at it. And then there's also a section for military profiles. So you can see that, you know, within seven degrees of you, those that served in the military. Awesome. So a couple of the interesting lines we wanted to share with you was the one that Melanie shared on social media about Yosef Gordon, your second great grandfather and how he was. So here's his profile. So you can kind of get an idea what that looks like. Wow. I didn't realize that was, he was a teacher. I had no idea that that's just. Yeah. At least when he came here, as far as we know, we don't know what his occupation was back in the old century, but at least when he came here, he taught, taught Hebrew lessons. So that's so cool. Okay. I don't think we can extra income in. Yeah. I don't know any Hebrew whatsoever. My grandfather did try to teach me before he passed away, but I don't remember any of that. Unfortunately. Yeah. Another interesting find was this gentleman, Edwin Pearlstein. He was an entertainment attorney. Wow. Okay. Yeah. So some of. Yeah. Some of his clients included Lucille Ball, Frank Sinatra, Groucho Marx, Liza Manelli. Yeah. That was kind of interesting. And so on his profile, then is linked newspaper articles about him and then also more about who some of his clients were. Wow. Okay. I love Groucho Marx. So that's pretty cool. Yeah. So he is a spouse of your first cousin, two times removed. Oh, okay. I was like, how do I, how do you connect? I never heard of this person before, but okay. So if we go, if we go right up here to his, the menu option up here, you can just do connection to me. And then you just right now it's looking at me, but if you just change this right here to your, it will automatically fill with your ID for you when you're logged in. But we can go ahead and check that. Oh, I see. Okay. So there's the six degrees from you. Okay. That's really cool. Yeah. Wow. Huh. And then the next find we wanted to just share briefly was Samuel Rosenberg. He was the oldest voter when he died in New York. He was 106 when you passed. He had voted for Lincoln in 1864. No way. Oh my God. Yeah. That's really interesting. Wow. Okay. So he is related to you. Sam's daughter, Jenny, married your second great-grand-uncle. Let me put that in. Okay. Your ID just comes up now because I've done it so many times. There are different things. Yeah. There we go. Okay. Cool. Yeah. So that's fun. You can check your connection to anybody because you have several connections to each other. You can also check your connection to the tree now in different connection paths. Right. So Melanie and Celia did a lot of research and work and a lot with the Jewish research. So Melanie or Celia, do you guys want to talk a little bit about what you worked on or what you did? So you want to go first? I think most of what I did was just sort of moving stuff to the tree that others had found. But there was a lot of the Brodsky family. Okay. And we went through, we did a lot of, we did a lot of work and didn't get a lot of results. We went through a lot of various sources looking for them in the old country and just absolutely could not find them. We found the, we got a very clear idea of where they came from, found the actual town names on some documentation. I can't remember off the top of my head, but it's a couple places in Lithuania. And they all, a lot of them came from the same area. It was Vrbalis, Lithuania and little areas around that. And they just, they must not have digitized those censuses yet because there just was absolutely nothing on them, which was disappointing, but we did our best. No, I'm sure that whatever you found was great, especially if you could like isolate it in a particular area of Lithuania. Yeah. We definitely found there was, I mean, I'm not, I spent a little while now, so I don't remember exactly where all of our sources were, but we did find enough things like naturalization papers and that sort of stuff that, that spelled out what countries or what the towns were. And JewishGen.org has a really great tool that lets you just plug in a town name and it will, you can do a town name very vaguely because of course this is being relayed from somebody who doesn't speak English very well to somebody who has no idea what that word is and is writing it down blindly. So spelling can get really creative and they're really good at finding the site is still really good at finding the right places. We dig through something. I'd be like, I've never heard of this place and I'd plug in and they'd be like, oh yeah, that's like three miles from the last place you asked for it. I guess that feels really good to me that we are on the right part of the country and a huge amount of them came from that Revalis area. The Brodsky family and everybody that they married into and and all that came from the area. That's awesome. Thank you. I don't remember exactly where the Brodsky's are on your tree. Yeah, the name changed from Brodsky to Harris. Yeah, that's right. Yeah, but Simon Harris is his family. Exactly. Yeah. Yeah. And so there were a lot of them and they married and one of them, one of my favorite things was one of the guys, one of the women married somebody had kids. She was a second wife. She had kids with him and then her, her youngest sister married his oldest son. And also had kids.  It was his second marriage. It's okay. Wait, I had no idea he was married a second time. No, no, it wasn't him. It was one of the, one of his siblings. Yeah, it was, it was a Rosa, I think. Okay. Her, she married Kaminsky and her younger sister married the oldest son of the, of her husband. Wow. Met a met a family reunion, you know. I almost had a heart attack for a second. I'm like, yeah, no, no, it's okay. I know. I find it badly the first time too. Okay. A little bit of relief. Okay. But even still it's like, you know, marrying into it again. Wow. Okay. I mean, I had my grandfather married three times. So, and, you know, there was a marriage that nobody knew about and I had to kind of find out by accident. So, yeah. And Azure, I worked and Mali, I worked on the Gordon and Malvin line and a little bit on the Levine as well. So I don't know if you want to turn over to that Azure. Maybe look at. So with, with Herman Levine, we at least were able to get lucky in that. And this actually find was, I believe, through Don Marie and another volunteer found the declaration of intention for him at least that listed where he was from. So a lot of the other branches from your family are really in the Minsk, Belarus area. And for Herman, at least we were able to identify that, you know, his, his talent, he was from was the acid, which I think is now the Ansqa. He was on the profile there. So at least be able to give you a little bit more info. We were just completely stuck on, could not find a positive ID on where he was buried and his death record. So that might be a follow up for you to look into that because that would help to see if what his parents names are listed to help you go back further. Okay, that's cool though. And we had more luck, I would say on Joseph Gordon and his wife, Maryam, who we identified her actually her name was actually like murky murky. I think by saying it wrong. Malben and there was a lot more on them and they also seem to be coming from probably the probably the Minsk area, it seems. So Azure, if you want to turn over to turn over to the Malben side. Yep. And if we look at, so we were able to at least go back on a little bit on her. And we noticed that there was also some intermarriage amongst the Grazowski family, which Mary, which Burke is a daughter Helen married to Grazowski and then her brother also married to Grazowski. So it's likely there is some connection there. And we got back to at least with Maryam's death record kind of identifying at least her parents name. So that is helpful and a confirmed brother. Oh, cool. Okay. So I think that was exciting. So there was a lot there. And even the kids were were named on the profile for Barnett Malben as well, which is one of their sons. Right. That sounds familiar. Okay. And then when we look at the her husband, the Gordon, so his, his name was Yosef. And there was, you know, that was the one with, that was the teacher that we mentioned.  And you have a Cohen line. So there's very much likely to be a lot more if you can take them backwards more via a little more info on exactly where, since you have that ancient priestly line going through like the Coens. So awesome. Wow. That's so cool. Yeah. It'll take a little time to flush out, but I think we had some good ties on some of the cemetery records. I think there was on some of these lines, there wasn't a lot of naturalization records. So then we weren't able to get as much, but there might be some clues, especially since you've done some DNA as well. Awesome. Yeah. Cause like sometimes I'll look on ancestry and just see third cousins and fourth cousins. And I see Collins. I'm like, Cohen's where is Cohen even coming from or Kaplan for that matter? Yep. Yeah. So yeah. So yeah. Kaplan was, was Joseph's mother's maiden name. And then the Coens was Merke's mother's name, Cohen. So that's where those are coming from. Okay. Cool. Yeah. Cause it was really confusing cause I'd never heard these names before until I started doing DNA tests and thinking, Cohen and Kaplan, that doesn't make any sense, but I guess it doesn't make sense now. Okay. That's so cool though. That's great. So Melanie and Celia, did your connection to Mellie decrease? I don't, I thought there was a slight change, but not overly. We didn't directly connect cause I have a cluster that goes into the Minsk Belarus area, but not directly that we connected. They might have known each other at some point, but it might have been a different schedule too. So hard to say. Okay. But yeah, I'd have to go back to the chart to see if our numbers went down or not. I think mine went down one. No idea where. Somewhere. Yeah. I think we got closer by two degrees. Let's see. Okay. Yeah. I just got the steps. No change, I guess. I thought it went down, but this is no change. But maybe that was just since the, we did have some problems with the spreadsheet. So it might not have captured. Yeah. Cause it was 22 when we first started. And now it says 18 on your profile when I'm looking at it. So yeah, it did go, it did drop. So that's cool. Cool. All right. That's what all those different connections gets you. You know, if you have multiple connections and there's different paths to, to people. Great. And of course we're ninth cousins. We're all related. You know, we have to go back. Maybe a long time, but you can figure it out eventually. You know, just calling everybody cousin. And I think it'll solve real peace right there. There we go. Yeah. They all connect somewhere. We do. We really do. And I think we need to be more aware of that. Yeah. I don't know. That's my tea sense, but yeah. But, uh, I think we're all connected. And we're all connected. We're all connected. We're all connected. But, uh, yeah, this is so exciting that I was like, all right, what are they going to find? What do I know? What do they know? Yeah. There was a couple of stories that we didn't put quite in the highlights though, but I remember I saw there was one of your relatives. I think it was. Let me try. Oh yeah. If, uh, Azure, if you go to profile Gordon dash 21657. There actually was a story I uncovered that made, uh, the news a couple of different places. Yeah. I'm sorry, Gordon dash 21657. I was going to type it in 75. So I'm glad I asked. Yep. So, okay. So, so yeah, so this is, uh, from a sister Dora. And when she was approximately 17, she might have been a little older. It was a little hard to say. Um, she was actually working as a bookkeeper. Um, and she actually, after coming back from the bank, she got robbed by three youths. I'm being, being nice there. Um, and she had no money on her because she deposited the bank and they, they roughed her up, but they, they caught them and they charged them and everything. But apparently it made a lot of the news, uh, nationally as well. Wow. Cause of that story. So yeah. Okay. It kind of gave us a little insight into who she was. And I think cause it named her address. Um, at home with her parents, I think that helped kind of tie that together a little bit too. Uh, she worked for an employer that helped manufacture, uh, naval uniforms. Wow. So thinking about, especially, you know, living in the Lower East side, a lot of these families were, you know, they were, you know, in Schmatte shops and other things. So that was a little more of a full on business that she was working for. So, okay. Okay. So she's, she seemed to, okay, you know, and then she married a few years later. So, but I, but it was just kind of a, an interesting story that kind of happened though. So interesting how you could find these stories, you know, you try to go to like newspapers.com. And sometimes it's really easy to find things. And then sometimes it's really difficult. Yeah. And that's where it actually came up though. I think cause, you know, a lot of it is really, especially I found with a lot of urban research, um, having a good idea of all the addresses, I try to list them on the profiles in wikichery, because I find that that's a really easy way to kind of know if you're having the same person, if they have a similar name, if you can tie the addresses together. So that makes a lot of sense. No, I appreciate that. Yeah. I know when there was one story that, um, happened in California, but it got reported clear to Australia. It was on Trove. Uh, this one, Ernest Wiley, he, uh, started out life in Massachusetts, migrated to California. And unfortunately the girl he was in love with was a little fickle, I guess. There's a whole newspaper, several newspaper articles about the story and his letters. Um, but he, he had an overdosed dose of ladenum by his own hand. So it's really a sad story. He was a very, I mean he was only 26 when he died. Oh my God. So just really sad, but it was, you know, they reported it clear to Australia. So we were trying to find out, well, is there Australia where there are family members that were in Australia or something, but we didn't, we haven't come across to me yet. So, but. Yeah, I know I have, I have cousins in Australia from my mom's side. It was one of my Campbell ancestors that left Canada and emigrated all the way to Australia. And I, Oh wow. But I should probably read about it a little bit more. Cause like sometimes I have a tendency to, to focus on my immediate family instead of cousins or aunts and uncles. And I know I, I should be more aware of looking at their stories too. Cause it's also part of my story. So I, and sometimes that in those collateral lines is where you can find some more information maybe about the direct, your direct ancestors too. That's really true. That's really true. Sometimes I just feel like when I do research, I get really overwhelmed sometimes. And so I become really laser focused, but I think that now that I know a little bit more about my family and that I could feel more confident about my resources, I could kind of relax a little bit and go, you know, maybe I should check out his brother or check out, you know, this cousin and kind of see their stories too. Cause they're still part of my story. Yeah. That that's, it's good to know that there are like these articles about my family and more resources and then stories that are fleshed out. So yeah, that's the thing I need to be more aware of for sure. And there are, you know, one thing that we have on wiki tree too, that not a lot of people know about is the wiki resource library, which is kind of a place where we've gathered together free books and resources that are online and kind of like made a library out of it. So that's linked down here to the bottom of the page too. So they're just a lot of great, you know, some resources that maybe people don't think about or know about. So that's another good thing about these challenges is that the learning opportunity, you know, I've learned a lot since I started working on these. So just from different people from across the world, bring in their knowledge and sharing. Yeah. And where we could, we also added research notes. So if we check something and we couldn't find something, we have a theory, we also put it in research notes too. So that gives you something to kind of pick up from as well. That's really cool. That's really cool. Wow. I just can't wait to play with that map. I know. That's a great thing. It is. I love it. I mean, when I'm flying cross-country or flying internationally, I'll get bored with the movies and shows. I'll have the map. Yeah. See where I am over the ocean. Yeah. That's like my favorite thing when I fly. So yeah. Yeah. Wow. Well, we had a lot of fun doing your week. We had, I think we had a total of, yeah, 38 participants for your week. You just had a blast. And I think that's all we have to share. Is there anything that you'd like to see or questions that you have? I know. I just want to thank everybody for participating and to kind of helping me flush out my family tree. I know like with my tree and ancestry, I put it in private just because I'm still kind of a private person. And also I don't want people to see what I have and it's not correct. I don't know if that makes any sense or not. Like if I know that my sources are correct, yeah, go, go, go at it, you know, have a field day, whatever. But, you know, sometimes when I would look at, you know, somebody else's record on their tree and I'll look at the sources and sometimes they're incorrect. I kind of get mad. Yeah. Kind of like, um, that's not right. I can tell you why, you know, like ancestry will say, do you agree with us? And I'll say no and they ask you why. And I'm like, I'm not going to tell you right now. But no, I, again, thank you all so much. I really appreciate all of your hard work. I just can't wait to play with that map. You know, read these stories and learn about my cousins and aunts and uncles that I really don't know too much about. Yeah. Well, thank you. I know that being private and having us do this was a great way to work together with you. And I just want to say that we are very proud of you. You know, I know that maybe out of your comfort zone. But so thank you for allowing us to, to do it. We had fun. I appreciate that. You know, at least I know you in person and I know Melanie in person. So it's like, OK, I trust them for sure because I know them. So yeah. Yeah. I've had my dream done too.  I mean there's a lot of like just even just some of your collateral cousins We found a lot of even like them on the military profiles I'll say there were quite a few that had some really interesting stories of newspapers on there You want to take that, you know and just there might be one she didn't know about Because yeah, you had a lot of people I think in World War one World War two that were being called out as well Yeah, I can only imagine I know that my dad never served You know, he was around for the Vietnam War, but he never served for instance And I know that I've seen draft cards of my ancestors and my uncles and stuff like that I know I had one uncle That served the World War two and was killed in action. So and I know he had a purple heart And I think my cousin has it. I don't know he says he has it So we'll see but um, yeah, it will be interesting to kind of read more about some of the military profiles for sure Yeah, and and too if you have pictures of any of your ancestors There's a you know Definitely if you want to add them to we could treat we'd love to see their faces if you want to add them Yeah, I have some photos for sure. Yeah, and I'm still you know trying to get more family photos from sibling I'm not gonna name who they are I've been on their case for a while. It's like I Need to add I need to add a leak to the Wickey Tree 15th anniversary cookbook where you're you shared your grandmother's recipe Yeah, and yeah, it was It all brought back a lot of memories for sure And I was really surprised that it wasn't added in the the roots tech cookbook for whatever reason even though I know sure I was literally one of the first people that submitted a recipe through email I don't know what happened, but whatever Yeah, well, I'll be sure to add a link to her profile that goes to the page For her for that recipe that you submitted because we loved we love to have in that Thank you. Yeah, I know it's it's a fun recipe, you know, my grandmother wasn't the best cook But she had her moments and those were one of the recipes that was a big hit every holiday for sure. Yeah, it's great Yeah But yeah, thank y'all so much. I can't wait to start playing with everything in Wickey Tree and Yeah So yeah, and be sure to reach out We're all happy to help you find things or you know talk about what we found or anything so Yeah, there's always the discord chat if you can get if you sign up for it you can actually see your archive for your week I like seeing that when I did mine. So oh really and you'll be kept busy for a long time with this This will take you a long time to really go through and you'll never be done You'll always find something new that was added. So I'm sure I will and I think that's like the cool thing about You know joining a family tree is there's always gonna be something different something interesting something new Something I'm gonna be like, huh, that doesn't make any sense. But you know, that's why I have you guys. So yeah Yeah All right, well, thank you everybody for joining us for the for the reveal and thank you again Meli and Melanie and Celia. We'll see you around the tree. All right. Thank you guys so much. Thank you


Welcome to MOOC course on Introduction to Protogenomics. In the last lecture, you will introduce to the concepts of cloud computing. Once the workflows have been set up, the next step in automated data processing involved in providing input data and collecting output data. Today's lecture by Dr. Manny will introduce you to the steps involved in execution of data analysis tasks on cloud platforms. So let us welcome Dr. Manny for today's session. So now you have your workflow description language that has told you what your workflow is, what tasks are in the workflow and how to string them together. And then I have told you that the algorithm that you are going to use for that workflow is encapsulated in a docker. So now how do you give it the data? How do you get output? Because in a cloud computing thing, everything is on the cloud, nothing is local. So if you have a big data set here, how do you give it and how do you basically run the whole thing? So that is kind of the next part of the presentation where, so you start with the workflow and then there is something called an execution engine. So the workflow is given to an execution engine which is generally a flying pig for a fire cloud. So it is called Cromwell and I have no idea why they represent it as a pig with rockets on it back. So maybe it's nice to see pigs fly. But the execution engine is called Cromwell. So what Cromwell does is, Cromwell interfaces to all the actual computing hardware. So if you are using Google Cloud, Cromwell knows how to interact with Google Cloud. If you are doing it on your local computer, it knows how to interact with your local computer or if you have your own grid engine or other local cluster computer that you have, it can run on any of those. So this provides like a common platform on which to run your workflow descriptions and your workflows without worrying about what the underlying hardware is and how the underlying computing infrastructure is recruited to do the operation. So you basically give your widow to Cromwell and then it will kind of run wherever. So I think right now Cromwell runs on our broad grid engine, it runs on any locals, you can run it on your computer if you want and it runs on the Google Cloud. They are trying to add Amazon services, it's not ready yet but it's something that's in progress. So how do you use the cloud to kind of do cloud computing? So I think I mentioned parts of this before but I think it's worth going through again. So here the traditional way is you bring data to the researchers. So you do your sequencing, you do your proteomics, you have a data repository, researchers download the data. So here data sharing is basically you're making copies of the data. So making copies is usually not a good thing because if you make a copy and change it, nobody else knows that you changed it. Or if the original people who put the data in the repository say oh I should have done this differently or there was something that was wrong, I am going to fix. And then they put it there. People who copied it don't know that it happened. So you need to send an email and then they have to kind of figure out whether they want to get it or not. So data sharing is data copying. The other thing is it requires big infrastructure at each side. So to do like genome alignment, it takes a lot of computing power. And so if your institution wants to do genome alignment, they need a big computer. And the other problem with these local traditional setup is the fixed nature of the computing environment. So you bought let's say 500 nodes in your cluster computer. Suppose there is a job that now requires a thousand nodes. You can't run it at once. You have to split it into two, do it 500 once and 500 next time. Or let's say you suddenly got a lot of users that are requesting resources. So this workshop for example, all of you connected to some, the IIT Bombay computer and said I need to run Prodigy, that's it's going to be hard because there is only a limited set of resources. So some people will get the resource, others will have to wait. And the other issue with a lot of this data is when you have genomics data with germline mutations and stuff like that at the US, Europe and I presume India also has a lot of restrictions on how you can make this data available. If you have identifiable data, you can just like put it out for people to take a look. You need security. And also when you are working on your project, you don't want your competitor to figure out what you are doing. Because when it's on, you are on the cloud or you are local, you have to have your own security. So somebody has to kind of make sure that your competitor doesn't hack into the IIT Bombay computers and take your data or figure out what you are doing. What you are doing. So you need a kind of a relatively robust IT department to take care of all this. In the cloud computing way, data sharing, so you bring the researchers to the data. So the data is sitting on the cloud and then people go to the cloud to do what they want to do with the data. So the data is like there is only one copy. You don't make multiple copies. So you make any change, everybody sees it. And the next thing is that the cloud provides the infrastructure. So I think I mentioned this before. I won't belabor it. So you don't need to have your computers and maintain it and so forth. But the biggest advantage is that it's elastic. So for five hours or for five days when you are running this workshop, you need a 500 nodes, you can get it. Because Google has hundreds of thousands of nodes and they can give you a few more if you want. And so you don't have to now wait for resources. You can get whatever you want instantaneously. It's very elastic. And security is now centralized. So if you access to this data is now centralized. So if you say only people who have gone through some kind of a data use certification can access this data, you need to implement that in only one place. And it takes care of it for everybody. So here you would have to each center that downloaded the data is responsible for implementing its own data security. So this is an example where it shows the actual genome processing requests per day over several months in the cloud. So you can see how much it varies. So I guess here somebody got a bolus of data from their sequencing experiment and now they want to do alignment. So they request a lot of resources. Whatever nobody is using, maybe it's vacation, whatever, not much being used. So if you are on the cloud, then you pay for only the things that you use. But if you have your own computer, you have already paid for it, whether it's being used or not. And usually at least at the Broad, we have found that using cloud computing resources is like significantly cheaper than using Broad IT. We have told them that and we are trying to migrate away from Broad IT. So when you are working on file cloud, the way you develop code is to you work on your local computer, you develop your workflow description, and then you have your inputs that you want, and then you use Cromwell to test your code, your workflows, and you can test on your local computer. And when you are ready to deploy, you can deploy it to the cloud and then it will run on the cloud. So that's kind of the model that's being used. So that is facilitated by the fact that the Cromwell can run either on a local computer, on a cloud computer, or on your local cluster. So when you have workflows that you have written, you can invoke them in several ways. So one is you can directly invoke them using the command line. The other one is you can use pipelining services from Google Genomics, or you can use the FireCloud portal. So the demo I'll give you will use the FireCloud portal. And it makes it relatively straightforward to kind of take other people's methods, apply it to your data, and kind of look at results. So I think this just says the same thing in more words. So there is an API that you can use to access all the workflows, the workspaces, and so forth. And then you can either access the resources using a workbench, which uses the API. So you type a command, and then it uses the API to get what you want. Or you can use the FireCloud portal. So this is kind of the overview of how FireCloud works. So you have researchers, some just use FireCloud, some actually write workflows. So when you have a workflow, you have workflows along with the configuration which says what parameters I've chosen for the various options and where the inputs come from. And then you use Cromwell to execute it on the Google Cloud. And then you have containers that provide the algorithms. So the one other thing that is mentioned here, is it the next slide? That I'll kind of briefly speak about is so when you're running on the cloud and you have data that you want to apply your algorithm to, where is the data? Is it on your laptop or where do you put the data? So that's where in any cloud computing environment, you will also have data storage that is part of the cloud computing environment. Because if you have data on your local computer or laptop or somewhere else, it takes a long time to upload the data to the cloud. Because if you have a 50 gigabyte data file, it takes a long time to use the internet to kind of upload the things. So if you did that, your algorithms will run very slowly and will spend most of the time waiting for the data to be available. So you create these things called buckets. I think Google calls them buckets. Amazon calls them something else, I think. So you put your data in the buckets. So the pipeline is the kind of sequence of algorithms that you want to execute on your data. So for example, we have discussed about a lot of ways you can analyze data. So you say I want to do these five things. So I want to pre-process my data. I want to remove missing values. And then I want to do a two-sample t-test. And then I want to visualize the results. So there are four operations you want to do on your data. So can you visualize the results first? Can you start by visualizing the results? You can. You need to do the other analysis before you have something to visualize. So there is a sequence in which this has to be executed. So basically taking your data and running it through a sequence of algorithms. So the sequence of algorithms is called a pipeline. So they have to be executed in sequence. And so that string of algorithms is called a pipeline. And you can use it for just genomics, for just proteomics, for proteogenomics, for all kinds of things. In the demo I will show you some of the pipelines we have for proteogenomics and what they do. But they are basically a sequence of algorithms that you execute in order to do a lot of analysis. Any other questions? Okay. Yeah. So your question is where we store the data? Yeah. Yeah. So you are asking what buckets are? Yeah. Okay. So I will go into that a little bit more. So buckets are basically like the hard disk on your computer. So it essentially stores data that is used for your analysis. It also stores results that come out of your analysis. So any data that you would usually store as a file on your hard disk in your local computer would be stored in a bucket now. Because the cloud computing environment does not have easy access to your laptop. And so basically all the data is used from a bucket and results are put back into a bucket. So let us say you are working on like a project where you want to use TCGA data. So you want TCGA breast cancer data for the 1000 samples that has already been done. And you want to combine that data with some data you have and do an analysis. The nice thing about using cloud computing environment is that public data like the TCGA data are already available. So in FireCloud there are workspaces meant primarily to make data available. So TCGA data is already available in a bucket. So I think that is what is marked as a data library here. So all the TCGA data from all the cancers are available in buckets. You just need to know which bucket it is in. So once you know that you can link that bucket into your analysis. And then you have your data that you want to include. So that goes into your workspace sorry that goes into your other storage. So you put your data here, public data that is already available on the internet and other places has been uploaded here and made available to you. So now you take those two, you run your algorithm and then it generates some results. So the results are temporarily stored in workspace storage. And then when the pipeline is done executing it takes that and puts it back into your regular storage so that you can log into your bucket and then download the results if you want. It is the same concept, it is just same files. So yesterday David had a file for loading your gene data right. So that file now if you wanted to do the same analysis on the cloud you would put it into your bucket. Because that is the only place the workflow will look for data, yes. So the actual physical way they store data is slightly different but you can think of it as folders with files. I will show you how it looks on when you go into a bucket when I go into the demo. But it is basically folders with files. Any other questions? So on FireCloud all the workflows that you create are called methods because they are usually algorithms or some kind of tasks that you want to do analysis that you use for doing analysis and they are described using the workflow description language. So all those are stored in a method repository. So the method repository has a collection of workflows and each workflow may get its method from one or more containers. You could have three workflows that use the same container but they use different settings or they use the container in different ways or they may use different versions. So you can have one container that goes into multiple workflows or you could have different containers for different workflows. So it is very flexible. So workflows are basically stored in the method repository. And then to make it easy to apply it to like biological samples in a biological setting there is also this thing called a data model. So the data model specifies like how samples and aliquots of samples and participants from whom you get samples are all kind of put together so that you can apply your algorithm to specific types of data. But here I think what we are trying to say is that workflows now have inputs that you want to provide. So what is the value of your threshold is it 3 or 5 or 7 what input data set do you want to use. So those are all configurations for your workflow. So a workflow in conjunction with the configuration with knowledge of what kind of data you are working with provides like a configured method and then you can run a configured method using Cromwell. So I think this kind of provides more explicit detail about the buckets. So you kind of have a portal which we call FireCloud that interacts with the Google Cloud platform. It uses the data model to access the various data storage and data libraries that are there to provide inputs and outputs for your methods. So this is the data model I mentioned. So there are essentially like two basic types of data you can deal with. One is a participant which is essentially you can think of as a person providing one or more samples and then you have a sample. So you could have a gene panel, you could have like actual blood sample that results in whole genome or exome sequencing, you could have tissue that you got, you could have other kinds of samples and they all result in more data that are now made available as data files. And then there is metadata about those data that is stored along with the information about the participant and the samples that you can use or update for your analysis. And then in order to enable some sort of automated batch processing, so you want to align whole exome data for a sample and you want to do this for your entire study, your study has 100 people. So instead of like invoking it 100 times on a sample, you can create a sample set and then you say I want to run my alignment on the sample set and FireCloud will automatically go it will create 100 jobs, one for each sample and then do everything in parallel and get things done quickly. You can also have sample pairs. So suppose you had a control and a tumor from the same patient that would be a sample pair or in sequencing you get a normal blood sample along with the tissue sample to do mutation calling and stuff like that, so that would be a pair. So you can set up these upfront in your data, in your metadata table and then use that to provide input to your methods, so that you can configure your method properly and run it. So it all depends on how the methods are set up. So you can create three different sets with different subsets of your data that is definitely possible. You can run specific algorithms on each set, but if there is an algorithm that is that allows you to compare two sets, then that would take two sets as input and then you can use that to run it. So it all depends on how the methods are written and what they expect as input. So suppose there is no such method and you want to write one, then you would say my method takes two sets as input and then I look at the difference between the two sets to do some sort of an analysis. So right now in the proteogenomic pipelines we are not using sets in the right way because usually when you do some sort of database searching or some proteomic or genomic analysis, we end up with a table that has all the samples and genes or proteins listed in a single table. So as of now we have kind of hacked this thing to say that that whole table is a single participant and then we just use it on the whole table. So if you had two subsets in your input you would say what your subsets are, but the data model would just think of it as one participant. So it is kind of not the ideal way to do it, we are trying to use the actual sets and the problem is that when you get output from SpectraMill or some proteome or data pre-processing software, you get it as one table. But when you do genomics and you do like exome sequencing and you get copy number or mutation data, you get one per sample. So this is kind of tailored towards how data comes out when you do genomics, but in proteomics it is slightly different because if you do a TMT 10plex, you cannot separate those individual samples and say each one is one sample, but the whole block is one sample. So we are trying to figure out what the best way is to kind of take that model from proteomics and map it to the model that is already here. So we are not done with that yet and that is part of the reason why this is still not fully public. So we are still working on some of the aspects of it. Any other questions? So I think I have mentioned this again previously. So you have a workflow, you have a configuration that says what the inputs are, you have a data model that provides those inputs and then you send it to Cromwell. Cromwell communicates with the Google Cloud Platform, it runs it in parallel to the degree possible on the Google Compute Engine and then you get your results in the appropriate buckets. So each task is executed on its own virtual machine. So if you have five tasks in your workflow, each task will get its own computer essentially and if possible it will run in parallel. But if two tasks are related, one task will get its own computer, once that is finished that computer will go away and then you get a new computer for the next task and you take the output of that from the bucket where it was written and then use it for this new computer that is just being created. So the whole, the cloud platform works on this concept of a virtual machine which is a CPU for doing the computing, hard disk for local storage so and the methods that you get from the docker. So all these go into one virtual machine and then there are buckets that are separate from the machine. So the buckets are not part of your virtual machine to start with. The virtual machine only has like storage but it does not have buckets. Buckets are separate long term storage. So when this virtual machine goes away after the task is done, all the data that was in the hard disk also goes away. You do not have access to it anymore, it is wiped out. So how you use the virtual machine is you start with the bucket, you copy the data you need to the virtual machine. So that is called localization and then you do all your computing in the virtual machine. Once the computing is done, you delocalize the data, you take results that was written on the hard disk and put it back into the bucket. And then the task is done, this virtual machine goes away and any data or any settings, any results that was on this virtual machine is no longer accessible. So you have to set up your things in such a way that things that you want as output are properly marked as output so that at the end of the task it will copy all those to the bucket during the delocalization process.  So I think this is a combination of everything and a repeat of a previous slide I think. So it is just to recap that how the whole system works. So now of late I think FireCloud also has notebooks available, people are familiar with Jupyter notebooks in Python. What you do is you have a notebook that basically knows the programming language and you kind of type commands and as you type commands the results will appear at the bottom. And then if you want to give it to your friend to look at what you did, they can see the code that you type, the results you get, you can do plots, you can also add explanations. So for example, the R program we wrote yesterday, if you had done it as a notebook, there would be an opening section saying this is code to do x, y, z and then there will be the actual code and then the results would be below it. If you want to plot it, you can plot it. And if you want to run it on a new dataset, all you have to do is change the dataset and then click enter and the whole notebook will run and so all the results will be regenerated with a new dataset. So that is kind of the new recent concept to make computing easy and to kind of be able to share your computing with others or when you publish your paper, if you make a notebook available that has your entire methodology encapsulated, then you do not need to field queries about how did you normalize the data or what did you do to filter, everything is there and the results are right there. So following up on that, so that concept primarily started with Python programming and now has kind of percolated into pretty much any kind of programming you can think of and so FireCloud is also starting to support that. I have not used it much but it is available and that is where you would find the actual FireCloud environments. In today's lecture, you are introduced to the concepts like Cromwell, which is an execution engine that executes workflows across multiple hardware. Several paths can be used to run pipelines on FireCloud. The results once obtained are stored in buckets. These can be retrieved and accessed by the user by simply logging to the cloud. A data model specifies all the information relevant to the patient, sample as well as when needed for creating a configured method. In the next lecture, you will be given a demo of FireCloud and how it can be used to set up data analysis workflows for large datasets. Thank you.