 Good morning everyone. Thank you all so much for coming. I know there's a lot of people still waiting to get in so lots of seats still over here for those of you who are arriving a little bit late. We are very happy to be here in Prague this week. We have an amazing event lined up for you this week. We've got incredible speakers. This morning I think we have some of the best speakers of the week. Linus Torvalds the creator of Linux will be here on Wednesday. Like one clap out there for Linus. 26 years. Thank you. We also want to thank our sponsors for helping us put on this event. I would like to give a special thank to Intel, our diamond sponsor, SUSE, our gold sponsors, Civil Infrastructure Platform, CNCF, Code, Huawei, IBM, Microsoft, OpenSDS, Red Hat, and VMware. Let's give our sponsors a quick round of applause. So at every one of these events we get hundreds and hundreds of papers and talks submitted to the conference. And it is incredibly hard to choose from all these different talks. I gave up a long time ago and now this year the whole LF team has given up to bring in some outside program chairs to help curate this. These people spend a lot of time, our experts in their field, and they help us pick topics, choose speakers. And I want to give a quick shout out to all of them. One Jono Bacon, Robin Bergeron, Tim Bird, Matt Butcher, Jesse Frizzell, Greg Crow Hartman, and Frank Rowan. Let's give the program chairs and all their committees a big round of applause. They work really hard on these events, so we really want to thank them. So I have a whole bunch of reminders for all of you today. First of all, the sponsor showcase is on three levels here. So go around and check out the different sponsors that we have here in their booths. Lots and lots of people are hiring this week, so if you are looking for opportunities, this is a great place to be in particular for developers. We also this year have a new networking app, so if you haven't gotten it already, go and download our networking app and we will be able to help you connect with other attendees. We have also some very fun and specific events this week that I want to call attention to. One, our annual women in open source lunch today is at 1 p.m. in the grand ballroom at the mezzanine level. So all women and non-binary attendees are welcome to attend, so please do. That is always a really good event. Second, if you are looking for a job in open source, there are lots and lots and lots of folks hiring. So tonight we're holding a career mixer at 7 p.m. also in the grand ballroom, so please register on the website in order to attend that. We also are going to be doing some mentoring this week, so on Wednesday afternoon we're going to do some speed mentoring. Again, please sign up on the website. If you're interested in career opportunities in open source, we have that speed mentoring available to you. So we've got lots and lots of great content, many events. I think you're going to have an amazing week. And I want to take now, let me see, a couple of minutes to make some announcements for some new things that we're doing at the Linux Foundation. How many people here know about how important data is to all of our lives? How many people have heard the word big data lately? Yeah, it's the big thing. We are working on big data initiatives here at the Linux Foundation. You're going to hear from some of our speakers about big data and machine learning. But one of the things that we recognized at the Linux Foundation about a year ago and started working on is a licensing framework, an intellectual property sharing framework would be an important thing for big data. As we embrace the idea of big data, they're just like an open source where all of us are smarter than any one of us, right? We learn that through jointly writing code together. Well, the same thing is going to apply to the knowledge we create using big data, meaning that no one is going to possibly be able to create all the data by themselves. We need good frameworks to actually share this data. Think about it, whether it's AI or machine learning, someone has to train these models using data. It could be for vehicle safety in autonomous vehicles. You're not going to get all of that data from one source in order to make sure that driverless cars remain safe on the highway. And there are just tons of different use cases that we can all imagine where the sharing of data is going to be really, really important. And so at the Linux Foundation, working with dozens and dozens of organizations all over the world, we started about a year ago working on the CDLA license. This is an agreement to share data openly and embody the best practices that we've learned over decades sharing source code, but could be used to address the unique needs of sharing data. So today, we are going to announce version 1.0 of our community data license agreement. Now, there are two types of agreements here. And the reason that we only have two is because one of the lessons in open source that we learned a long time ago is that when the number of different open source licenses started to increase, the compatibility for code sharing started to decrease. And organizations like OSI and others got together and sort of created a system and started to try and limit the number of open source licenses so that we could better enable sharing. What we're hoping to do with data is get ahead of things so that the same thing doesn't happen in terms of data sharing. But we did feel that we needed two distinct types of licenses for sharing data. Again, based on the incredible precedent that you see in open source licenses. One, a sharing based on copy left. This is an idea that share and share alike, that people can, essentially, if you use that data, you're required to share back data with everyone else. The next, the other license that we have is a more permissive license, like an Apache-style license, where you can use the data and you're not required to share any of those changes. And so, those are both launching today at CDLA.IO. Go check these out. We'd love to get feedback. It's an open community. There'll be an ongoing process. But if this works effectively, I think we can get ahead of a lot of the data proliferation in terms of licenses and get big data working together to really train the machine learning and AI algorithms that are really going to change our lives.