 All right, well, good morning, good afternoon, good evening, depending on where you're joining us from today. Welcome to Engineering for Change, or E4C for short. Today, we're very pleased to bring you a special segment in E4C's 2016 webinar series focusing on mobile data collection. My name is Yana Aranda, and I'm the Director of Programs here at Engineering for Change, now the year moderator for today's webinar. I'd like to take a moment to tell you about a mobile data collection series. The widespread availability of mobile communications offers international development researchers, practitioners, and students new tools and techniques for collecting field data and determining success of projects. So, we've partnered with the Development Impact Department at UC Berkeley for DIL, for a series of six webinars to introduce a sample of theory software tools and demonstrate how to implement each tool in practice. For a recorded introduction to the series, please visit the E4C homepage. Today's webinar is the last in the series featuring open data kit for ODK, presented by Wayland Burnett, one of the founders and core development team members of ODK. Although this is the last webinar in this series, our regular series continues with the webinar tomorrow, April 14th at 11 a.m. Eastern Standard Time on prototyping on a budget with Ryan Vineyard of Highway 1. A San Francisco-based hardware incubator. If you would like to make recommendations for a specific platform for us to consider for future webinars, future topics, and speakers, we invite you to contact the series team via the email address is visible on the slide. Before we move on to our presenter, I'd like to tell you a bit about E4C and who we are. E4C is an electric exchange platform and global community of over one million designers, engineers, development practitioners, and social scientists. Leveraging technology to solve quality of life challenges faced by underserved communities worldwide, we invite you to join E4C by becoming a member. E4C members enjoy access to relevant current news, professional development resources including jobs and fellowships, and a growing database of hundreds of poverty alleviating products in our solutions library. E4C delivers a unique user experience based on user site behavior and engagement. Essentially, the more you interact with our site, the better we are able to serve you resources that meet your needs and interests. We invite you to join our passionate global community and contribute to making people's lives better across the world. Please check out our website to learn more and sign up. We are excited to collaborate with Dill on this and future webinars after the series. Dill is an international consortium of universities, research institutes, NGOs, and industry partners addressing global poverty through advances in science and engineering. Dill has headquartered the University of California, Berkeley, and was launched in 2012 with support from the US Agency for International Development through the US Global Development Lab. This leverages the innovative capacity of world-class universities to design development solutions, which couple new technologies with novel economic and behavioral interventions. Dill calls this approach development engineering. Now, the webinar you're participating in today is part of E4C's professional development offerings. Our webinar series is a real-time and on-demand resource showcasing the best practices and thinking of development practitioners. Information and upcoming installments in the series, as well as archive videos of past presentations, can be found on the E4C webinar page as well as our YouTube channel. If you're following us on Twitter today, I'd also like to invite you to join the conversation with our dedicated hashtag, hashtag E4C webinars. So, a few housekeeping items before we get started. Let's see where everyone is from today. I'm going to get started by entering into the chat window on my location. I'm joining everybody from New York today. So, there we go. Should be staying there. And I invite you to share your location in the chat window as well, which is located to the bottom right-hand side of your screen. If the chat window is not open in your screen, you can access it by clicking the chat icon on the top right corner of the screen. So, any technical questions should go into the Q&A window. But I see for now we have folks from all over California, Indiana, Berkeley. Thank you so much for joining us, everyone. Pennsylvania. Any questions that you want to have for the presenter, please enter into the Q&A window. And again, if you don't see that, please click on the icon on the top right-hand corner of your screen. If you're listening to the audio broadcast and you encounter any trouble, try hitting stop and then start. You may also want to try opening WebEx up in a different browser. Following the webinar to request a certificate of completion showing one professional development hour for this session, please follow the instruction on the top of the E4C professional development page. And you see the URL listed right here. So with that, I'd like to go ahead and introduce our speaker for today, Waylon Brunette, who is one of the founders of ODK and a core member of the development team. Waylon is currently a PhD student in the Department of Computer Science and Engineering at the University of Washington. He was formally advised by Professor Gayato Boyello and is currently advised by Professor Richard Anderson and Magdalena Balazinka. Waylon's research interests include mobile systems, sensing, ubiquitous computing, and data management. His work focuses on designing systems that improve the lives of underserved populations in low-income regions while leveraging mobile computing devices and sensors. And with that, I turn it over to you, Waylon. Thank you. Welcome, everyone. So today is the last series. I'm going to focus a little bit more on some of the lessons I've learned and introduce the brand new ODK 2.0 to our new series. First of all, though, I want to thank everyone who has contributed to ODK. ODK is used around the world. Thousands of organizations, thousands of deployments. And there's a lot of graduate students, technical staff, undergraduates, professors, companies who have all contributed back to the ODK ecosystem. So this is not really my work, per se. It's the community's work. So I'm going to first talk a little bit about ODK 1.0, which you guys are some of you may be familiar with, but if you're not, you'll at least get a sense. So yeah, that ties in and then introduce the brand new set of tools that we're releasing this week. So first of all, to start with ODK, since we were development engineering, we really wanted to focus in on this kind of environment and we really wanted to bring technology. So we're from the computer science department. So when we were really starting, it's like how can we leverage technology to help people in really rural villages? And so we first did some study and found out that all the rural villages, what technology they had available, they may not have power, they may not have water, but what they did have is mobile phones. So when we decided to do an intervention, we decided that we were going to build technology on mobile phones because all the infrastructure was already being built up around the areas for mobile phones. People had businesses, even though they didn't have power, they still figured out how to charge their mobile phones. And they also knew how to, where they needed to go for cell service and they really used their phones for more than what just talking or SMSing, they used it for many tasks. And at the same time, why we were examining that, we also wanted to make sure that going forward to make ODK successful, that we put it on a research trajectory that really fit well with the current technology trends in the industry, right? So those of you in the more developed context, such as Australia, Europe and North America, you'll know that basically we've switched away from PCs and we're now on smartphones and tablets and we're all using the cloud, right? We all have Gmail accounts. So if whatever we decided to do was going to be successful, we needed to make sure that we weren't building on old technology that manufacturers would cook making because if you're going to scale, it needs to be around for 10 or 20 years. So we really wanted to make sure that any intervention we did was made on that technology trend. So Open Data Kit was first publicly released in 2009. We decided on Android devices because they were more open than, was not as locked down as iPhones. And the real goal was to make a modular open source architecture that people could reuse, so we used the Apache 2 license. More information can be found on opendatakit.org. The real goal of the project though is to magnify human resources through technology. As technologists, we know that technology is really not the solution. What we want to focus on instead is making technology that people can use to do their job better, quicker, or anything to improve their process to help out in development. So ODK 1.0 really focused around the fact that there was a lot of paper that was really clumsy and inefficient. And the fact that many NGOs back in 2008 were hiring all these companies to make custom mobile apps. So what we did was basically decide to separate the rendering of the app and building a database server back in and just allow you to design a form with questions separating kind of the business logic from the rendering logic and all the technological problems. And this turned out to be really, really successful. But I do want to point out that ODK was meant more than just as a paper replacement because you can do richer data types. Like you could collect GPS or video or audio. Also, by putting constraints on the data, you could make it so that people gave you better data and then you could do customized workflow. So it wasn't just paper replacement. It was also an improvement in rural workflows. And the biggest thing we just designed the system for was being disconnected and that's a big thing for us. So many of you out there probably see in ODK if you haven't, here's just a few ODK collect screenshots. In part of what I want to point out is that you can see that you can do pictorial type questions. You can check to make sure if you're asking for someone's birth date, it's not in the future, things like that. This is very similar to what you've seen from the other tools. And the reason why Open Data Kids kind of go at the end is for how do all these tools fit together in this ecosystem? And when we were designing Open Data Kids, we really wanted to make tools highly modularized and customized so they can be easily composed and are specialized into appropriate arrangement for the task at hand. So we basically wanted to use exploit the open interfaces and allow people to share. We didn't want one monolithic application that people were competing with. And again, we really wanted people to take advantage of the evolving technology so that 20 years from now, it would still be relevant. So we really set up to create this open source ecosystem and the real design was we wanted small chunks that people could reuse. And you've seen in this series, Survey CTO and the Kobo Toolbox both actually use Open Data Kit underneath. So they just take what we have as a starting point, expand on it. And this ecosystem was really based on trying to let them add features and create value to really build a community around the fact that we needed data collection in the field and getting on those technology trends. And this community has continued to grow up even more but there's now more than 60 consulting companies out there that help people do ODK deployments because graduate students and us try to make new tools and do research whereas there's a lot of companies out there that can help you. However, everything from Open Data Kit is free. You can go download it. It's just if you need extra help, it's available for you. So after we did that, that was great. Then we found out, well, the people thought it was, when they deployed it in the field, it was really great, they were using it but we were missing some things. So one of the things that ODK 1.0 doesn't do as well as we'd like, but ODK 2.0 will do better is updating data on a mobile device. So basically every time, if you were revisiting a location multiple times, people were then re-entering data over and over again and they kept asking, can't we just pull up the old data, see that, make a few modifications and resubmit it? And that was one of the big changes that we were unable to accommodate that we're now accommodating. Many people wanted to customize the look and feel. So ODK 1.0, because we render it for you, it's a very utilitarian look so that it works for all organizations because people use ODK from environmental monitoring to AIDS patients to carbon credits. So one look and feel doesn't work for domain independence. And so unfortunately, people don't like that utilitarian feel so they want more customization to fit their individual needs. So ODK 2.0 allows for full customization. And also people like, this is great, I'm collecting a lot of survey data, but I want to use some kind of sensors. And then, paper's not going away. If there's some way you can make our lives easier by making it so you can bring together paper and the mobile technology phone and make it so it's more integrated. And so I'll get into those new features. So the big design improvements that we heard from people was that we needed to be able to make it more feel like a PC's interactive environment where you can see the data interact with the data versus the old style of you kind of take the data collected, done, and move on. And we then decided most of the time, people were kind of frustrated with the XML we didn't understand, and most of the time they just wanted to output as like a CSV into their system. So we switched to more of a table-based using database rows than the old XML. We moved to runtime computer languages. The reason why we did that was to make it so you could change the look and feel without re-compiling a complete Android app. And we increased the different inputs you can use such as sensing and paper. So one of the big changes that is coming with ODK 2.0 is that it's database-centric instead of file-centric. And you will have a local copy of any relevant data on that device. So if you're visiting a clinic that you visited six months ago, any updates to that data will now be available on the device instead of just collecting it as survey data. Another big change is that people really wanted to customize and they were tired of the utilitarian field that I was mentioning earlier. And so we set out as like, okay, well, how can we make it the easiest for people to make customizations? And so the idea being that if everyone probably in the world is maybe made a webpage, probably the lowest standard of use is probably a webpage. So now the whole system is now based around webpages, but it is not based about webpages on running on a server because running disconnected is super important to open data kit. What it's now based on is this local server running and it's being rendered right on your client. So ODK is maintaining its disconnected operation, but we're trying to bring in technologies that will make it easier for people to customize their look and feel. So they can make it purple in the background and put their logos on. So I'm gonna contrast a little bit of the difference between ODK 1.0 and 2.0, but I just wanna make it very clear that ODK 1.0 is not going away. It is a product that will remain out there. ODK 2.0 is not a replacement. It is a parallel set of products. So ODK 1.0 has been very, very successful and handles very simple use cases and it's great. There's a large group of organizations and individuals that wanna do more complex things. So we have to add more features. We also, that means that the simple cases could get bogged down with a lot of access features they don't need. So both the new tools and the old tools will continue to be supported and exist. So it's not going away, it's not a replacement. There choose the set of tools that works best for your needs. So ODK 1.0 is really just basically you collect data on the mobile device and you stick it into the cloud and collects that very simple program that we used before. Now, we wanted to maintain the idea of small swappable parts so that Kobo and Survey CTO, as they work with their customers, can also swap out. They may have better versions than we will come up with. So from our free versions that people are more than welcome to use. And so we made the very focus on small tools that are very customized to do tasks well. So to be able to add all these features instead of making one big monolith application, we made five applications now instead of one on the phone. Now, we're gonna make a packager to make it so your users don't know this, but just if you're designing an application for deployment, you may want to use multiple tools. And the different tools now are scan, which is the papers, object, mark recognition, survey, which is similar to what COLLECT does but is much more powerful. It tables to view data. And one of the biggest things people wanted was the bi-directional transmission and update. So now your data can synchronize. When you're online, your data will synchronize between all your devices. And this is probably one of the largest changes between ODK 1.0 and 2.0. And it's probably one of the most requested features. So I'm gonna talk about Survey, which is basically kind of like COLLECT, except for the fact that when people, if you've dealt with X-forms, you know that it's one linear flow through that uses relevance. And people were really struggling when wanting to do complex workflows. So we took a completely different approach that's basically making, it's focused on making complex workflows, accessing databases, querying things. So people often would complain that I just wanna query the list of countries. Why do I have to do, enter them all in the X-forms? And it's just a pain. So ODK 2.0 really tries to solve some of those things and bring into the use cases that are a little more complex. An example that I'm bringing up here is the ammonia detection that we did with some partners. And I wanna bring this up just quickly for the example of why ODK 2.0 was needed. So we needed more complex workflows for medical protocols. So we needed survey. And then we wanted to do some pulse oximetry to detect how well the child was turning oxygen. So then we needed sensors. So we needed kind of this combination of different tools working together. And so we basically made survey. And survey now, so it's more complex, needed a new language. So those of you who've used XLS-form, we now have XLS-converter. And it's a JSON representation instead of XML, which was big in the tech field. And this is actually very expressive. You can jump around and go to different workflows. So it's not that singular workflow anymore. So you can do ifs, else, and a lot of new features. The idea behind tables was people are like, great. I've entered my survey data. Now I wanna come back and revisit that location. I wanna see the data that I need. So tables is really to fill the gap in our tool chain. So an example is maybe a cold chain. So I may be going out to clinics to see how many vaccines they have left in their clinic or the refrigerator is working. And every time I was going out there, I had to re-enter the same information. There's fire refrigerators, there's these many vaccines instead of just going in and updating curating the data. Or same with patients. So community healthcare workers that were following up with the different patients were really struggling to say, I don't wanna enter their age every time. I just want that pre-populated into look again. So survey and collect really weren't designed to just look at rows and rows of data. So that's why we developed tables. So tables allows you to look at things in map views, graph views, simple list. You can color code it. And an important point here is that access is the exact same data that's on the device as survey. The access is the same thing as what sensors. So all the data is integrated all together and hidden from the user. It just looks like one seamless application that they're working on. And you can fully customize this with HTML and JavaScript if you don't like how we did that. But we don't wanna get away from entering data and using the richer data types and having the data cleans, detecting the fact that if we said enter a number you can't enter a letter. So the idea is the tools work in connection with each other so you go back and forth. So if you're in tables and you wanna update an entire record, we actually launch survey so all your form constraints are then actually put back and enforced on the data updates or on the new row. And sometimes people were like, can I, they had multi-sectional forms. So they had a form that had follow-ups and sections where they're like, well I do this on the first visit, second visit, third visit. So now a record can actually have multiple forms pointing to the same record. So again, this gives you a lot of flexibility not that you have to use it. But again, this is why ODK-1O is good for the simple case, ODK-2O is good for the more complex case. So a common question is, well what's the difference between survey and tables? And it's actually a spectrum of things. So we could have designed one tool but one's really for viewing and updating data and summary reports and one's really for entering data. And both of them in theory could actually do the same thing. It was just very complex to make any one tool do one thing. So we made two tools that are designed for completely different use cases and your application will likely be in the middle somewhere. And you might want to use both, you may want to use one under customization. But the idea being that one tool to rule them all really doesn't work out very well because it becomes so complex that you just end up programming. And really, we're trying to avoid people having to program too much. We want people just focusing on what data they want to collect, what surveys, what is their actual development goals, not the technology. The technology should fade to the background. So ODK scans another new one of our tools. And it's the idea that, well, sure handwriting recognition is hard and paper exists, but can we do something in between that's better? So what we've decided to do is using computer vision basically recognize when people mark circles. Or if they draw numbers rigidly we can also automatically read this. So the idea being that like if you're having a vaccine registry people would take the vaccine registries hand into them in the computer. Instead if they would just mark dots and write some numbers in the cell phone could automatically input that data into ODK survey and the person would then be able to clean it up if necessary. So this is a real pipeline effect that will help really bring down cost of deployment so that not everyone can have a smartphone and paper still always durable. So kind of the combination of paper and digital. And then the last new tool is sensors. And the idea behind sensors is there's a lot of tasks out there that computers are really good at like watching things and being able to have it so you can have lightly trained people be directed into what they need to do is very helpful. So in this case just connecting a thermometer to a phone while someone's pasteurizing breast milk will help to make sure that the milk is heated to a point that it kills all the bad things but doesn't kill all the good things as well. So you can give instructions like heat milk and then when it gets to a certain temperature it can beep, they can take it out they can put it in an ice bath as well as with sensors we've attached to printer you can make custom labels. So really it's turning the mobile smart phone or tablet into kind of a full-fledged application interactive system is really the goal. And so finally where we're headed is we're working with University of Berkeley and the DOLAB to develop the Missouri platform so that instead of having aggregate you'll be able to put all your data in the cloud and be able to better share your data with built-in security. However, that's not gonna be available for another year or two. So I've quickly introduced all these topics. All these tools are now actually available on opendatakit.org since you only get 20 minutes I'm not gonna try to go through each one of those tools. However, I highly encourage you all to go download it. We're in the process of updating all the documentation and that should be done on Friday and then you should all be able to have fun but this is supposed to be a lessons learned introductory webinar. So with that I'm gonna take questions. Thank you so much, Wayland. And I'm going to go ahead and invite our attendees to enter their questions into the Q&A window. I really personally enjoyed seeing the youth gaze of ODK as supporting Internet of Things in this case or the something technologies. Have you seen that be kind of a rising trend in terms of the application usage? Yes, so I would say that over, we've been at this now for six, seven years and so first of all, it was paper replacement and then when people start to understand the power of being able to experience technology just like we do in the developed world and all the use cases, sensing, monitoring, all those things, people just want more and more and more. And so I think it's a building on top of each other. So the first thing with OpenDataKit is, we kept everything in flat files and X forms so people could really see the data and trust us, right? It was just an effect of wanting to build and trust. Now that the trust is there in technology, now they want to see what else they can do. Right. And so we get all kinds of requests out there. And so do all the companies. That's very cool. Have you been tracking them actively? Oh, there's way too many. So, the... That's good. We pick partners and try and work with them for research, right? Because we're based out of the university research side of things. And what we encourage is by making all of their stuff open source that companies like Survey CTO, Nafundi, can work with all these different organizations out there. Yeah, for our listeners, for those of you who have maybe not participated in the entire mobile data collection series, we actually featured Survey CTO. So you're welcome to check out the recording to get a better sense of their specific instances and exactly how they've leveraged ODK through their work. So one question has come in amongst others. Is it possible to track... Oh, sorry, just as moved down as I was reading it, is it possible to track and record data... Data... Let me see, track and record data, the use of any particular app in the mobile. For example, for educational purposes, I want to know if students are watching an educational video in an open course software and record to see how much time they spend on videos. Is that technically feasible? Yeah. Is that built into OpenDataKit? No. So the question really becomes as you... OpenDataKit, again, tries to keep small and modular in our design philosophy. So we leverage other people's players. So you would have to instrument the player. Well, that's fine. You could have a player that records that information. It's just not where, what we've done. So you mentioned, was that in mind? I see a few questions that have come in regarding whether or not you collaborate with certain organizations, for example, such as Engineers Without Borders. And when we kind of started talking about use cases for sensors, you mentioned that as a research, being housed in a research institution, you have to kind of pick and choose which organizations you engage with. And of course, the folks or the organizations that leverage with UK further have their own partners and so forth. So in terms of criteria for being selected as an organization to partner with and develop projects, do you have any criteria that you employ currently to say, all right, we're going to work with this particular organization or we're currently prioritizing work or research in this field? So this is what we're seeking out. So let me back, I want to make a couple of comments on this. First of all, I want to highly encourage everyone. OpenDataKit is used by many people by themselves without any of the companies. So we're kind of the free software that you can go download for free and use. It's only if you need extra help, you have to go use one of the companies. So it's just because we don't have the time to help you customize for every little issue. But there are thousands of people around the world who use OpenDataKit right now without any help from anyone. And that's actually a testament to really how well and simplified the design is. And that continues to be our goal. Second, since we are a research institution, what we want to do is figure out what's not working well on the tools? So if you're using OpenDataKit and there's something that's, oh, it's really, this is a big deal that it's not, it can't do what I need to do, that's what interests us, right? So then the questions become, how do we adapt technology to make it so it's easier to do that? Sometimes we can't, honestly. And sometimes, because a lot of times it may not be a technological problem, it might be a human resource problem. So. No, that's very helpful. So in terms of that, what are, can you speak to some of the projects that you're currently working on where you are testing limits of the software or are you really testing kind of the capacity of the system? So, sure, I mean, so I mentioned a few. So the vaccine, instead of having everyone have to enter data in, they're replacing vaccine registries with paper now that they can just take a picture of and the phone automatically processes all that information. There's NGOs basically making patient books or patient cards, very commonly used. Now, they're redesigning them. So there are more X's and boxes to fill out. So that patient information can be entered much more rapidly. The, we're working with large NGOs for disaster response, synchronizing all the data. There's trials going on in 10 year with HIV follow-ups. So if you go and visit a bunch of HIV patients in the field, looking at all their previous information that was now available in tables, there's hopefully some work with bringing down the spread of dengue and then there's a lot of agricultural work too, like fisheries, you know, so if you go back to that same plot and I measured the corn, last week at two feet, isn't that three feet? So we can track that a lot differently. And so it's really the people who are like, I wanted new technology, I want paper, I want sensing, or I needed to do that follow-up work and how do I do that follow-up work? Or I have this complicated medical workflow that I need to triage. That's really fascinating. Actually, following up on some of those examples, you've shared quite extensive numbers in healthcare, disaster relief, and agriculture. One of our listeners wants to know if you've actually seen anything in human rights reform, any applications of ODK for that. Oh, yeah. So there's been tons of that. So the Carter Center uses ODK for election monitoring. The Berkeley Human Rights Center, which is now in Harvard, was one of the first adopters of ODK and went around the world documenting human rights violations. And there were one of the people we worked with to get encryption right on ODK 1.0 so that no one could see it, so that people got captured or arrested, I mean, wouldn't have to worry. That's incredible and very empowering. All right, so I'm looking to see if there are any other questions here that our listeners would like addressed so far. We don't have additional questions being loved our way. So I'm gonna turn it to you, Leland, and see if there are a question that you get very commonly that you think is really important for our listeners to kind of get insight into. So I would say that one of the technology trends is important, I brought that up, but if when you're designing your interventions, think about where it will be in 10 years, because when you start, you will probably have a pilot with 30 maybe, and then you're gonna wanna scale to a countrywide, maybe continent-wide. And when you do that, it's gonna take years. So one of the most common things or rubs we get is as engineers that I get with the organizations, is they're like, has to be as cheap as possible. And so they wanna use older phones or whatever, and I'm always discussing with them that that's great, but then you realize your intervention won't be able to scale if it's successful, because you're gonna have to redo it. I mean, you're gonna have to redo it again on the next technology, on the next technology, on the next technology. I really think one of the reasons of the success is we were looking out at the future. Now, of course, you have to kind of guess what the future is gonna be, but I think that that's something that us as technologists are better positioned as. And I guess the one thing that I really wanna also bring up is we're really focused on grassroots and making organizations and making it empowering people to collect their own data for all their own uses. And that's been one of the big successes of Open Data Kit is people use it all over the world, and then you hear about it later. Everything from canines that track animals around the world to carbon monitoring, to deforestation, to, it's just where bus stops are, New York City used it at one point. I mean, like it's not, City of Dallas used it to monitor their sewer system, right? It's not just, we've used it, we made a platform that was supposed to be so generic that it could be used in any development domain. And really, it's on completely outside the development domain, and people use it all around the world. So, you know, targeting a simpler user interface so people don't have to program very much. The people will learn over time, Yvonne, as you give them steps to build up to that. Well, you talk about really trying to anticipate the future, and it's very clear that you guys have done a tremendous job of that. And certainly, I think that 2.0 is positioned for tremendous success, and it's very exciting to see how far it's grown, and speaks to the need for this platform. So, with that, and no questions that I see that are burning from our participants, I do encourage everyone, if you weren't able to ask a question, or if something comes to you at a later time, to please reach out via the email address listed on the slide and share your questions. And certainly, for those of you who are seeking pH codes, the code is, our pH of the code is right there. And I'd like to thank you, Weyland, for taking the time to give us an insight and wish you the best of luck with the upcoming launch. And thank everybody for joining us on this last of our webinar series on mobile data collection. We will be combining all of our recordings and publishing an article with additional platforms to share with everyone so that you can continue to learn from these webinars. And thank you all, and we will catch you on the next E4C webinar. Have a good afternoon, evening, or morning, wherever you may be. Take care.