And yes, yes, we are back at Big Things Conference 2020 and we are at the attic, we are in the attic room at the top of the house, this home edition that we created for this special ninth edition of Big Things Conference. It was a fantastic first talk with Brian O'Neill and we have a second speaker ready, which I'm introducing you straight away. Localizing a video game that is preparing for its sale in a new region or country can make a huge difference to its success and sales figures, but it's a big joke. It's not just the translation, it can be new audio, graphics and even altering aspects of the game because of cultural sensitivities. One of major game studios, Electronic Arts, is developing AI tools to make this faster and easier. To tell us more, we have with us the director of localization, analytics and video audio at Electronic Arts, he's Mario Bergan Piños. Mario, welcome. Hello, thank you. How are you? Thank you for having me. Very good. Thank you. Lovely to have you in this super cool office of yours. Yeah, it's not a background. It's my actual office.  Yes, it is. It's work, it's work. You have to say, no, this is work. Of course, this is totally work. Console, sorry, hidden over here. We're looking forward to listening to you, so whenever you're ready, go ahead. Okay. All right. So, I hope you can see my screen. Okay. So, good evening, everyone. My name is Mario Bergan Piños and I'm director for localization analytics as well as the video and audio departments in AI localization. Well, as you can see, this is quite a mixed role and everybody asked me kind of the same thing. Why data, audio, video, it's kind of like really mixed. Why is this? So, I'll quickly sum up my experience. So, I come from broadcasting technology, so 3D video composing, audio. And after working for several multimedia and broadcasting companies, I started in EA for a summer job and I tried out and I stayed there for 16 years. So, it's been a long ride. So, my profile has been primarily focused in audio and video localization and then I moved between different departments and then kind of ended up in leadership roles in Madrid. So, I can say I'm not a data expert in the sense that I don't code but I'm a data enthusiast as we call it and I'm a business expert, that's for real. So, this kind of mixed experience with my leadership role and also co-leading innovation for localization kind of created the perfect mix to give me the opportunity to actually create and manage a data team. So, how come that all of a sudden I started getting involved in data? So, my entry point was mainly player data. I kind of started looking into the relationship between player data and specifically FIFA. This was kind of like four years ago. After that, I kind of started getting curious about asset telemetry data and then financial data and then machine trust data data and then vendors data and that's how I kind of realized that cross-referencing data and having all of it kind of like in the same place was something really powerful. So, to start doing this, we kind of created this data, this log analytics team and as soon as I created it, I realized thanks to Noelia, our data manager, that EA could benefit not only by merging and exploiting all of the data that we had from different sources but also from machine learning technologies like machine translation, speech-to-text, text-to-speech, or even automating several processes through algorithms. So, my talk today is kind of like about all of these changes and this journey, kind of like creating this team, the learnings that we had and then talking to you a little bit about what kind of data we're handling and what localization in video games is all about. So, I'll get it started. Before I start speaking about data, some of you might be wondering what is localization about. So, our team in EA kind of centralized all of the translations, voice-dabbing, testing, manuals, video, and basically all content that is not English for all of the EA games. So, our operations are quite complex in the sense that we're always kind of like shipping in a simultaneous ship, which means that at the same time as the English is shipping, we're shipping the rest of the languages. So, as you can imagine, this kind of means a lot of changes and complexity in the operation. So, we need not only to have specific tools but we also retrieve quite a lot of data that helps us kind of like to take better decisions in our operations and the quality or even the language decision-making. This is like we kind of have our guiding principles. So, we say that we obviously localize, you know, all of the EA games, text and audio, and all of the player-facing content. We partner with all of the EA studios, publishing worldwide customer experience. We're really highly scalable through technology, automation, and industry partnerships. We consider ourselves that we not only localize, but we kind of craft, you know, we ensure that the artistic style, it kind of targets the languages and cultures. And we try to achieve that immersive experience for players around the world. We also consider that localization kind of generates revenue in the sense that we should have analyzed and maximized the return of investment of each of the languages. So, we try to influence those localization decisions, you know, based on data. Our mission, similar to the one of EA, if EA inspires the world to play, localization kind of makes that possible, you know, especially around the world because of the languages. And then our vision is basically to be EA's voice for the right localization solutions. So, going to the next one. Here, I wanted to give you kind of like a snapshot of all of the data kind of streams that we handle and we consider, especially when we kind of started doing our taxonomy in EA localization. So, we have audio, we have video translations, financial testing and player data. So, if I kind of start with the audio data, we basically gather data from all of our audio departments, you know, from the recording studios we work with having almost like everything that has to do with the speed of recordings, the cost, vendor data, and all of the files basically that enter our content management system. So, we are basically aware of every single move, you know, that these audio files are making through our workflows. And if we have gone through re-recording or the quality wasn't good, we kind of, you know, cut all of those telemetries. The audio quality KPS are basically, they're really based on manual checks and back-entering. So, we know which assets were good or bad. And when they got into our systems and how many times they went back and forth, as you can imagine, this kind of gives us excellent insights about, I don't know, our vendor accuracy or the development studio's asset turn. So, how many times, you know, we actually redid some of the localization, as I mentioned before, because we have to do everything in simultaneous shift, you know, all of the changes that are made in the English content have to be replicated in the rest of the languages. Sometimes, specifically, for example, in audio up to 12 languages. So, it's quite a lot. With video data, it's mainly anything that has to do with marketing videos. So, we basically localized all of the languages for the marketing videos in four years. So, everything that you see on web pages and Twitter, tweets, whatever, right? So, we do all of the localization. We work in, with this department, we work a lot with automated image recognition to automate, basically, our quality assurance. And that gives us quite a nice metric, you know, our own workflow accuracy. So, we also try quite a lot of the stuff that has to do with the scopes, and the back and forth also of the videos. And because we are dealing with marketing, as you can imagine as well, you know, there are tons of changes, you know, in these videos. For translations, we kind of have two different areas. One, what we would call like regular translations, in the sense that this is like the translations that are basically done by translators. And in here, we kind of track all of the quality-based feedback from our testing teams, the speed of translation, the cost, and anything that has to do with the translators. The other area, it would be the machine translation area. So, here, of course, we have a really big focus in machine learning, and we are basically trying to improve the quality of those languages and also creating our own KPIs. In terms of financials, of course, we mainly track forecasting and billing internally to EA. And we're very good at this in the sense that we have been doing this for quite a long time, and we distributed quite a lot of data. So, for this specific one, it was really a challenge to gather all of that financial data and get it into the same place. This is something we're working right now. So, these days also we're really focused on anything that has to do with life services and life games, because games right now are not only like shipping a game and then wait for 12 months and then shipping another one, but content is constantly being changed. So, we also have to track the financials around that. Testing. For testing, we have bags, speed, quality. Everything is based on amount and severity of bags. This kind of gives us all of the trends that we need to focus on and what is important. So, there's also quite a lot of data regarding resources. We have quite a big internal testing team, so there are quite a few tools that are helping us, basically, to handle all of these resources, and we also track data around that. And then player data, one of the most important ones. So, this is where we study our game behaviors. It kind of, depending on the areas of usage of the game, monetization, but for lock specifically, for localization, it's really important how the game has been used in text and audio. So, for example, are people skipping, you know, cinematics in a specific language or are people using one language against another, you know, within the same country? We are also experimented as well with player sentiment metrics in which we can extract data from forums, social media, mainly assigning keywords to positive or negative sentiments, and this can be quite useful. So, this kind of gives you a brief snapshot of kind of our complexity and how we could lose a great opportunity if we didn't organize all of this data. So, when we started to look at all of the possibilities to cross reference all of the data that I just mentioned, we found ourselves with 35 different databases. We also needed to speed up our ROI process based on player data. And we, of course, wanted a data driven culture and whatnot, right? So, we didn't have the team to do this. We didn't have the talent to do this. So, that's when we reached the conclusion that we needed help and professional ones. So, that's when we started kind of creating the team and this is kind of like what it looks like, right? So, when we started the hiring, obviously the first thing that I did was looking for a data manager. In this case, Noelia González. I mean, she was supposed to be also here with me. So, I say hi to Noelia. She's looking at me. She's watching. So, when I first met Noelia, we kind of decided to divide the team in like four different areas. So, we have a business analyst area that is helping us with the management and understanding of the business requests. We have a data engineering area that is kind of like creating our data infrastructure which I will explain a little bit later. We have a data sciences area that is for applying machine learning techniques for localization. And we have a data analyst area where it's basically kind of like creating the APIs and the visualization of all our insights. So, the team is not big, but it's very senior. We try to nurture ourselves of segments from other teams in localization. Temporary staff, trainees for a specific project. So, we work also a lot with universities. So, yeah, when we had the team in place, we wanted to strive for that sort of like data-driven culture. And I kind of like get our own departments in localization really excited about this, right? So, in this slide, I wanted to mention some of the learnings, you know, that we went through, you know, through this journey. So, for example, you know, when we started all of this, you know, when we started talking about different initiatives or the data lakes or whatnot, you know, our first reaction was like, okay, let's just ask ourselves the right questions. What do we want to accomplish? What problems are we trying to solve? And we find ourselves, you know, with quite a lot of projects that we could help at our different departments. So, the next thing that we had to do is basically knowing our data sources. So, a little bit of what I showed before, you know, like you saw the different areas that we had. And this was definitely the most tedious task, you know. We had to look into every single database that we had, you know, track those volumetries, you know, how many times those databases were updated, are those real-time? What are they coming from? Is this basically an Excel in someone's computer? What is this, right? So, we had to go through all of that. And then when we had all of our initiatives, something really important was kind of like trying to map them and basically measure, you know, how much effort it was going to be taking, each of them, and then measure also the output, you know, and make a little bit of a return of investment on each of the initiatives. And then, of course, MVPs, right?  MVPs for us is key, because we didn't really have that culture of creating minimum-bio products, and we were always kind of like immersing ourselves in huge projects then, and then having this for years and you don't realize, you know, how much time you would lose doing something like this. So, we're also striving to kind of like, you know, try to fail fast if we need to and then reiterate from there, right? So, that's what we're trying to do. And then data evangelization, which is, you know, again, trying to get people excited about data. How are we doing this? So, data evangelization, for us, it's kind of like something key to get people, you know, as I said, excited. So, a good entry point, and this is, again, learning that we had throughout our journey. Data evangelization is kind of fast and a quick win, so, you know, creates some of it, you know, for your teams and then, all of a sudden, you will realize that people are getting engaged, you know, in data. So, I mean, you can see some examples here, like, you know, doing some machine, machine translation story, you know, grads or even stuff that we had, you know, small kind of data visualizations that we have here. We're trying to ship, you know, some of this every month or so or even less.   And I can say that the ones that we had in the office were quite successful. We have quite a lot of people, almost the whole office coming in. So, that was great. Something that we also do quite a lot is trying to, we have a mentorship program in EA and what we're trying to do here is being really active. So, trying to spread our message by coaching and mentoring internally. So, we also try to do something that we call Seguments, which is basically borrowing people, you know, from other teams to work with us for a few months and train them at the same time. So, also internal and external visibility is quite important, again, you know, like this forum.  This is something that we did as well. And for the training, which is something quite important, you know, you need people to start kind of like doing their own visualization as soon as you kind of create your data lake or whatever it is, you know, you need people to start using whatever, Power BI, Tableau, whatever it is, right? So, there's also a bit of training and this one, we try to do something different. We try to go for something called the data school. So, data school for us is something that we're trying to create our own data training program, you know, based on experience and recommendation from our area experts. So, the idea is that we try to create four different training paths, you know, from business analysts, data engineering, data scientists and data analysts. And the reason why we're doing this is because of, this becomes like a three-way tool, you know. First, you train other department team members, as I said, for second moments in our teams. The second is that it will help, you know, onboarding in your team from external candidates or trainees. And the third one, we feel it's a super important personal development tool. So, if you're not really familiarized with the data world, you know, this is an excellent tool. To give you an example, we could have a software engineer coming to our department from a team working with us for six months.  So, what better than doing this himself, right? And this is something that we're actually doing. And with this program, you know, so also helping us, you know, to fill the gaps that these people might be having in some of the area. So, training sources can go obviously from pre-training ourselves, kind of like recording videos and then, you know, some of the paid trainings. But I think the interesting bit is that we kind of created our own sort of like application in which people can, you know, get in here and kind of like do their own evaluation, you know, about how much do they know about coding specifically or data exploration. As soon as they have kind of like filled this up, they will get some results, you know, for each of the areas. And then some recommendation, you know. So, the cool thing about this application is that it also serves a couple of things. You know, it helps people to visually knowing, you know, which trainings it would be better for them. But it also gives us some insights, you know, from the different departments that we have in EA, you know, what is the level that they have in terms of knowledge. So, I think that's, you know, and one of the ideas that we have is that as soon as we shoot this to the EA localization team, we're probably going to be doing something for the rest of EA because I think it's quite important that we gather as many trainings as we can. So, okay.  You want quality of data. You want people having easy access to it. So, how do you do it? So, that's when we kind of started, you know, building our infrastructure. So, we started, you know, creating Ada, which is our EA log data house. So, when we started creating this hub, you know, this is kind of like an environment in which we can basically centralize data in a single repository of those dependencies. So, kind of like saving costs, efforts, and most importantly, after transforming those pieces of data, basically all of those data sources, it will give us, you know, kind of like the quality standards that we need. The name of Ada is actually, I like, you know, because it's coming from different sources, but the one that I like the most is because it comes from Ada Lovelands, which is considered to be, you know, the first woman super engineer. So, how does it look like? I'm not going to get really technical here, but our data hub kind of gives us kind of like the autonomy basically to our different business users to work with their data almost as a marketplace, right? So, the data hub is kind of like an open business data source with different solutions. It obviously has its governance. It will have its rights, security, but it is to have all those 35 different databases that I talked about ingested and wrong, you know, inside that data hub. So, people can basically, you know, use their business intelligence tools and create APIs and whatnot, right? So, all of the transferred data, you know, will be residing in our data lake, which is called Hall of Justice. Yes, we're pretty freaky about video games and also heroes. And this is based in, I mean, it's Amazon Web Service, and it's obviously quite scalable in terms of computing, but at the same time, we also have our own computers at the office, you know, that we will use for machine learning. And in this case, we call it an polygon and it's a really powerful computer that is helping us, you know, also to save some credits in Amazon. So, this is pretty how it looks like. All right. So, that was really interesting as well, but what about the projects? What are you guys working on? And I think this is the probably that is more exciting. So, I'll start with some ideas and some of the projects that we're working on in terms of player data, which a lot of people ask me. So, in this slide, I kind of thought about, you know, asking ourselves some questions that obviously all of them are, you know, have kind of like a guess as an answer. So, for example, can we create customized content based on player data? In example, record more via lines. This means if I knew from player data that, for example, in Spain on a game like FIFA would I know based on player data that people are playing with a specific team are playing a specific friendly matches, how many substitutions from a specific player they are and things like this, you know, I would know what are the behaviors of the players that we have inside FIFA, meaning that whenever I need to localize something, I won't do it exactly as the English, because that wouldn't make any sense to us. So, what we're doing is basically customize in per language. So, whenever people are listening to the speech and the commentaries, we try to refresh that, not only by the same concept that the English game is doing, but basically doing it specifically for each of the languages. So, we found that that was pretty cool and customized. Another thing would be do we know which language to invest depending on the player usage? Yes, of course, this is what we call our ROI process and it's also taking information, obviously it's taking information about sales and it's taking information about our own cost in localization but something really important now that more and more we are basically everything is about player engagement, as I said before, games are not only shipped every 12 months, but we have content constantly, we need to know if people are engaged. So, knowing if people are engaged with the language itself, with the text, with the audio, are people using this? It's pretty important for us to make the best solutions. Should we localize Polish in a specific game or maybe just doing audio or only text? We wouldn't know stuff like this because also of the player data. How do we get live sentiment from our localization games? This is something as simple and as difficult as going inside social media and basically or doing web scrapping from forums and using keywords, we can basically know if a game has been doing whether wrong or we can extract information about if people don't like a specific commentator or things like this. And the last one, could we change FIFA commentators based on English vs. foreign player language choosing? And I actually have an example about this, which this kind of happened between FIFA 19 and FIFA 20 and it's got an interesting case because when we started to retrieve data from our Dutch commentators we realized that there was something off, that there was something weird. In this case you can see that in FIFA 19 there was quite a lot of people playing in English so when I say this, it means that when people started FIFA they actually changed the language between Dutch to English, specifically for audio meaning that they were changing the comments and they were changing the commentators. So at the first glance you realize that okay, well the Netherlands is probably the highest in English proficiency across Europe so maybe we shouldn't be really worried but this is kind of strange compared to other languages. So then we started looking at player sentiment and looking at the forums and we kind of realized that people were kind of like complaining about the commentators. So we took the chance and we basically after quite a lot of talks with marketing we changed the commentators and this is what happened the next year that we decreased the usage of English in the game to 12% and we increased obviously that's to the 86%. So this means that a 16% uplift is quite big. If you think about going from 70 to 86 for us it was quite a success story and I think the success story was being able to track this and being able to make decisions with this kind of data. So in terms of machine learning, what's the stuff that we're doing? You know? We can basically, can we customize machine learning engines, for example like speech to text or text to speech or machine translation. This is something that we're working on right now. So machine translation is the one that we're obviously more advanced and we're doing stuff, for example, are we able to automate tests with image recognition? This is something that we're also doing with our marketing videos and I will show you a couple of examples later or can we even predict financial forecast based on historical series and we have a lot of financial data, can we do something like this is something also we're working on. In terms of to give you an example right now, stuff that we're working on in speech to text something that we're doing is obviously trying to search not only for the best KPI in terms of quality that we can get but also tracking this KPI. So we're tracking every rate of each of the engines, for example, Azure, Google Watson, we're looking at IBM and other companies and also the character error rate. So what we're doing is kind of like tracking from each of the languages this constantly. So we know which language is basically behaving better than the others and which one has an uplift in the last few months. This is something that we're doing so whenever we want to invest some time into improving one of the languages we know which is the one that we actually need to go for. And we're doing this for, you know, same thing for text-to-speech and machine translation. And then you know, image recognition this is something that was quite helpful in the past year. So we went for an MVP and this was almost a few months ago and now it's embedded in our workflow. So this is one of the examples of how we use machine learning technologies. Image recognition in this case, you know we went for a trading agency logo. So what we're trying to do is kind of like trying to recognize, you know, these age ratings, you know, and what we do is like we have let's say that we're doing, you know as I said here, more than 10,000 videos a year, right? So we need to embed, you know, in each of the videos these age ratings and we were doing this, we were checking and doing the quality assurance almost manually. You know, from this video just to make sure that we were not shipping a video that was supposed to be 12 and then it was 7, right? So now what we're doing is by image recognition we're kind of like getting this automatically and not only automatically knowing that this is a 7 but where is it placed specifically and in what time? Because everything is compliant, right? It needs to be in a specific place, it needs to be triggered at a specific time. So we don't really need now people looking at this video. So we actually is safe quality of money and we actually, you know, same as we talked about the MVPs, now we're reiterating into that MVP and doing more stuff and so now we're actually looking at subtitling prescription and then entity recognition which is basically looking at recognizing characters, for example from each of our games. So we can look at not only transcribing these subtitles and that this can be from art but also recognizing characters from the game in videos and getting that into a database. So I hope that wasn't too fast or too much of an information but this is in a nutshell what we are doing right now in entity localization in terms of data. So we have a lot of work in front of us and but we're really excited and totally open for questions. Thank you so much Mario. That wasn't too fast but that was a lot. I know. It was fantastic.  You started talking about FIFA, you almost finished talking about FIFA. There's some pattern there, isn't there? No, I know. Yes, totally. You're totally transparent. So thank you for telling us the cultural change that you have to do to get people excited about data and you mentioned the importance of the team. You actually mentioned Noelia several times. So hey, no, Noelia, we know now she's worldwide known around the world. Noelia and the importance of having a strong team that you needed the help and you found the strong team and then it actually surprises me that you have to evangelize in data, getting people excited about data. You mentioned all the things that you're doing and I wonder, data scientists, data engineers, data analysts, there's plenty of jobs, they have fantastic salaries. I'm surprised that you actually have to get people excited about data and you mentioned the log data school and all the things that you're doing and the fantastic app that you have for people to find out their knowledge and their suggestions that you give them and people ask you what about next exciting talks and openings in electronic arts if you need any extra help for all that amount of work, tell us what are you looking for and what are the next talks that you might be sharing through the school, the log data school or that we can join. Yeah, totally. So a few things that you're actually doing is now for example, we're doing talks about our infrastructure all of the work in machine learning and there's a lot of stuff about visualization and storytelling specifically because it's one of the things that most of the departments within your localization were really focused on like there are tons of graphics and tons of data that they have but they don't really know how to present it and how to tell the story around that. So this is something that we also are helping them Sorry, but Mario, are you talking about the storytelling within the games for example or the storytelling to understand and interpret the data? Exactly, the storytelling Is it two different things? Yeah, it's the storytelling about the data itself. So how do you tell the story behind the data because normally we've seen so many power points with graphs and nobody understands and this is about that. It's not only about retrieving that data and visualizing it into a really nice way by telling the story about it. Well, they said that the power of data is not the data itself but what it means and to know just gathering data by itself is no use. So I guess that's what you call the storytelling which I thought it was just to interpret the data but of course to know the story behind it and to be able to sell it to offer it to the excellent. So when is that happening then Mario? So we are one of the things that we are doing is looking at forums like this one and having people from our teams also presenting. So the data is cool unfortunately it's internal to VA for now but some of the talks that we have internally are going to be really similar to the ones that we are going to be doing externally. So we'll keep you posted. Okay, so people want to know also the openings we have to check on your website or you keep us posted through the social media etc. Exactly, so we have jobs at EA.com I think and in there you will have mostly based in Madrid but now with COVID you never know. We have people all around the world in the sense of within our team in Madrid right now we have people in Salamanca in Valladolid, in Valencia so it's all good, we can have people from anywhere. Excellent news. I think people have seen your cool office and they say I want one like that. So you're going to have a lot of requests. Just one last thing before we go Mario because you mentioned Ada Lovelace you named Ada the EA Log Data Hub which I really like because I don't know if you know that she has a day Ada Lovelace or Ada Lovelace and she has a special day which is the second Tuesday of every October so I expect that Electronic Arts is going to make something special for this second Tuesday in October next year obviously because now it's gone regarding your EA Log Data Hub beta please tell us that you're going to come up with something in honour of all the successful to honour and celebrate the achievement of women in STEM careers and I put you there into that the situation now. We're really focused on that honestly so yes, yes, yes, yes, I didn't know the date but now I have it written so we'll make a big part of it. Noelia, writing down on the agenda Noelia, second Tuesday of October we expect to have some kind of something special from Electronic Arts there you go some homework for you you weren't expecting that were you Mario? No, I didn't expect that. So sorry about that but it was lovely having you we ran out of time so we want to say goodbye hopefully we'll see you around because we're also in Madrid but thank you for this fantastic talk congratulations on all your achievements good luck with all the work and keep us posted, yes please keep us posted okay? We will. Big kiss to Electronic Arts and Mario and for you audience don't go because we're going to come in a few minutes with our third speaker at the attic


These days, it feels like a new AI solution is popping up every week. And that's a great thing, considering it has the potential to benefit all industries and help solve some of humanity's biggest problems. But until now, AI solutions have been expensive, complex to build, and hard to access, often out of reach for both individuals and organizations. The truth is, we all benefit from accessing AI. Whatever our background or field may be, Enter the concept of AI democratization. We'll explain. AI democratization is the process of making artificial intelligence more accessible and inclusive to a wider range of individuals and organizations. And some companies, like Intel, are playing a big role in speeding up the democratization of AI so others can safely benefit from the technology. In recent days, it seems there is an increased sense of urgency due to generative AI. Now, generative AI can get pretty pricey. And this is because it requires training models that need a lot of computing resources. These models are typically trained on very expensive hardware. The good news is that we are finding solutions that address the performance, price, and sustainability needs for AI. Intel looks to address these concerns with built-in AI accelerators in their fourth gen Intel Xeon processors. In addition, AI requires more than hardware like chips and silicon. It needs a software platform that spans multiple hardware architectures and vendors. That is why Intel is leading the one API industry forum. One API specifications and open source projects allow developers to build, train, and run AI models on a wide range of hardware platforms so they're not tied to a single vendor. Personally, as a developer, having open source toolkits to build code faster and more efficiently is key when thinking about different frameworks that I want to be building. I know this sounds like a lot of technical information so far, but the whole point of democratizing AI is making it more accessible for people without a technical background. That is where the Intel digital readiness programs come in. By partnering with academic institutions, businesses, and industry experts, Intel's programs inspire people to use AI more responsibly and ethically. Build solutions and apps, foster more trust, seize new opportunities for responsible use, and stay competitive in an increasingly digital world. So whether you build AI tools or build with these tools, there is room for everyone.


Hello, welcome everyone to another training webinar of OpenAir. Today it's the fifth version of our Horizon Europe Open Science requirements in practice webinar. And before we start, I would like to quickly go over some housekeeping notes with you. Okay, so as you might have noticed, this webinar is being recorded and we will share the recording shortly afterwards. In order to ask questions or share your thoughts or comments, you can use the Zoom Q&A section. You can also use the same section in Zoom to upvote any questions that you would like our speaker to address first. You can also find the presentations in this link or scan the QR code available in this slide. And I will make sure to also share this link with you in the chat shortly afterwards. So with this very brief note, I would like to give a warm welcome and introduce our speaker for today. So today we have with us Jonathan England, the training specialist of OpenAir, that will be guiding us through the open science requirements in Horizon Europe projects and programs, and also share some tips, guides and tools and services that you can use to make sure that you are compliant. So with this very brief introduction, I would like to give the floor now to Jonathan so they can give their presentation. Thank you all. Thanks a lot, I see you. My screen. Okay. Welcome everyone. So today, as you probably gathered, we will be talking about the Horizon Europe requirements in terms of open science. And I'll also cover some of the open science parts in the grant proposal. So the slides already on uploaded on the nodal. And you will find on the first slide basically all the different resources that I'm referring to in the in the webinar. You probably already noticed, but I'm going to give again and like the definition of open science, which is the approach based on open cooperative work and systematic sharing of knowledge and tools as early and widely as possible in the process. And this covers as you know, open access to publication to data management. And it also covers also the concept that I will refer to in the second about open access to data as open as possible as close as necessary. But also the European Commission does put in Horizon Europe, quite a lot of emphasis on sharing information about output tools, instruments, and to validate or use the results and the data. That's the digital, whether it's physical or digital data should the access to the results should be available for to validate the conclusions. So we'll first start with the publications, then I'll go over the data, and then we'll see a few more aspects of those recommended practices, but which are not required. In terms of the mandates for open access to publications, you have to deposit the peer reviewed manuscripts. So there's two different version which I'll mention in a second. And so one of those version in a trusted repository. And again, I'm going to cover what the different types of versions exist and what is a trusted repository for the European Commission. So one of the big difference with if you were funded on the H 2020 is that there's no embargo period allowed. So you have to make your work available in open access immediately upon publication, and you have to retain your rights. By applying creative commons license on one of the versions of your manuscript. And as I said, you need to add in information about research outputs to validate the conclusions. And also don't forget to add the acronym code of the project within each publication. So a few definitions. So when you first send the job to a publisher, it's what we call a pre print. Then the peer reviewing process happens. And then when the final version is is the accepted peer reviewed version is what we call the author accepted manuscripts previously was also known as postprint. And usually this is the version that you might be retaining your, your rights on. But after the publisher does all the copy editing.  So the pretty version is the version of record. And so either the accepted manuscript or the version of record are fine, as long as you put one of those in open access you are. You are. The man you're. Sorry. You are fine with the mandate. And in terms of trusted repositories. There's a whole definition that the European Commission gives. But what we want to what I want to really focus on is basically anything that in your discipline is commonly used and is always a general purpose repository or your institutional repository will be considered as a trusted repository. It's not something as like the publishers website, it wouldn't be a repository by itself. It might be available in open access on the publisher's website, but you still need to deposit on repository. So you can search for that on open explore. Then there's also other websites for publication, for instance, open door, which allows you to, to search for specific repositories. There are a few things I want to mention about the mandate around open access. And first of all, the publication fees. So usually called article processing charges or book processing charges for books are reimbossable if the, the journal, the publishing venue is in full open access. If it's a hybrid journal where you know it's subscription based journal that allows. Authors to publish in open access.  But the ABCs when you wouldn't be able to cover them under the grant. In terms of the license, the issue of publishing a book or monograph on text formats, you can apply a more restrictive license, but bear in mind that a chapter in an edited book is not considered as, as a long text format. So it would still be under a Creative Commons attribution license, which I will mention in, in a few seconds. One thing that I want to really insist on and is linked to the whole mandate is that you have to deposit one version of your manuscript in, in, in this trusted repository. And so that's what we call self archiving. So, irrespectively of whether it's a full open access or hybrid or wherever you publish you need to deposit it also on the trusted repository, which also means that the, the author accepted manuscript and the version of record might have different licenses applied applied to it. And for subscription based journals or hybrid journals, you don't always have to pay for open access. It's the coalition as you might have heard of it. I have issued the rights retention strategy, which is basically a statement that want you that you it's a statement that you put when you're submitting your your article to the to the publisher, and it basically assets ownership of at least the other accepted and that means that if you have author ships on that version you are compliant because you will be able to upload it on on the repository. You can check the journals eligibility. And by going on general check it will just put from the European Commission, and it will let you know if, if the journals allows you for this route. There's also another option, which is open research Europe, which is the publishing platform from the European Commission. I'll go over this a bit more into details just to to give you a bit more insight of why the European Commission created this. So the first thing I want to, to mention is that the, it is a publishing platform. It's not a repository so you go there to publish your work not to deposit it and not self archiving. And if it's open to all horizon 2020 and horizon Europe beneficiaries, and it's free for you to use it's an optional service so you don't have to use it you can, as I said before, you can publish whether you want. And you can use it so you can still publish after the end of the project. It's based on open peer review, meaning that the name of the reviewers, the, the actual content of the reviews, or the revisions, the versions of the revisions are openly available. And you first publish basically your, your work, and then the review happens. So the work is immediately available, even though it hasn't been peer reviewed yet. And because it's made by the European Commission, it has automatic compliance with the open access requirements, because it will self archive it automatically for you on Zenado. So the whole thing I said about self archiving is only that the only time where you don't need to do it is for horizon for open research Europe. So the publishing process is quite streamlined. And there is in house editorial team that does prepublication checks to ensure that all the policies and guidelines are followed. And then the publication is is deposited. It's available for those two to read. And the reviewers are invited to do the review. And then once it's passed review it is archived on on Zenado and indexed in all the different indexes. So it's multidisciplinary. There's a lot of different types of articles that you can submit depending on your fields. And there's, as I said, a lot of different prepublication checks, but the team does not review the actual content. It's only the guidelines, language, data availability, ethical approval and all this. The review process is also quite transparent. Reviews are suggested by you as authors. And then they basically go ahead and do like the normal peer reviewing process, but in an open in an open way. For an article to be approved, it needs to have at least two approved checks. And it can have up to one approved with reservations. And so basically until it is fully approved, it wouldn't be considered as a past peer review basically. And this is just an example for reference of what reports could look like. And one thing also that is interesting to mention is that they are from research communities, so collection and community gateways that is available on open research Europe. That's that could that you can basically have a look at if you're interested in all the different papers in that field. And yes, there's a newsletter you can you can subscribe to. Okay, so this was another view of the requirements for open access to publications. And now I'm going to give an overview of the requirements for research data. So, in terms of the mandate, you have to manage. And again, everything I'm going all those keywords I'm going to mention, I will explain them in in future slides. So you must manage basically all your data following what we call the fair principles so it's the fair principles are findable, accessible, interoperable and reusable. You need to create a data management plan by month six, which you will update during the project and before the end of the project. You must deposit all the at least the metadata but hopefully the data itself as soon as possible after it's been produced. Or after it has gone any quality controls. It doesn't need to be open but you need to at least deposit it. And you need to deposit it in a trusted repository and follow the rule of opening as open as possible as close as necessary. So, as I said the data can be closed, but the metadata so metadata is any data that explains what the data is the authors, the title, any persistent identifiers that link to to the data. All this is what describes the data is what we call the metadata. You also have to share the data under either a CC by but preferentially under CC zero license. Again, I will explain in the future slide what those are the difference. And as I said before, strong emphasis on providing detailed information about research outputs to validate the and reuse the data. They are obviously and this is very clear from the documentation from the European Commission that intellectual property rights is really important for the European Commission. So they are valid justification for not opening the data so commercially valuable data for instance does not have to be open you can make it closed so that you can exploit basically the results. Obviously, if there's any data privacy that protection rules of, you know, sensitive data, personal data on the GDPR, then obviously you wouldn't be opening that up. There are a few exceptions in terms of the opening the data. If it means for validation, you might need to open it to specific individuals. And in, in, in case of public emergencies and that was created or added to the policy because of COVID-19. And you, it can be triggered by the European Commission and you would need to provide immediate open access basically to not just the publication but also to to the to the data. And they, they might be some conflict with intellectual property rights and this has to be discussed directly with the project officer in general. So, as I mentioned before, I'm going to describe a few things that I had mentioned before a few definitions. So this is the same slide as for the publications, the trusted repositories basically the same definition. And so use one that is well endorsed in your community, or use a generic one like the nodo for research data, there's a specific website where you can look for different repositories, we call these related. Or you can just go and open a explore it has all the different repositories available. So, in terms of licenses, I mentioned for publication, it has to be on the creative commons attribution license a CC by license. And for data, it's perfectly a CC zero. So creative commons is, it's an actual license. So it's, it's a legal binding license, basically that CC by at least it avoids any confusion basically of what you can or cannot do with the data or the publication. And so under CC by you have to basically say, could the authors were only in which context. So, for instance, all those slides here, you can see in the bottom right is under CC by license, meaning that you can reuse as you want, you can modify it. As long as you credit the, the origin, a CC zero is a bit different and I won't go really into details of why it's preferred for data but CC zero is basically you can share that without having to attribute the the authors. And it's quite similar to public domain type of, of a license. So I mentioned the data management plan. And it's a beast in itself, and I can't cover it in what goes into detail but data management plan if you haven't heard of it is a formal called a living document because you will be updating it every time there's any modifications. It basically says how the research data during and after the project will be handled. So, during the project, how are you going to share with other partners, the data after the project, what are you going to do with the data, how are you going to to share it with with the world. The issue with a data management plan is that there's no absolute right or wrong answers. As long as you justify why you made this this decision. And it's in theory. Okay, it's just that you have to prove to the project officer basically that you know what you're doing with with your, your projects. And in terms of the fair principles I mentioned those again. Again, it's, it's a two shorts of a webinar to be able to go into details. And, but basically there are a few different concepts around so, for instance, having your data always needs to have what we call a persistent identify so it's like a DIY. So, for instance, if you deposit on Zenodo, it will give you this URL that was there's never any broken links with a person identifier. It needs to be deposited on a trusted repository. It needs to be well documented. So have a read me file has a clear license and use open file formats if possible or well used file formats, all the type of aspects are form what we call the the fair principles. But again, if you're not familiar with them you will need to look a bit more into it to get familiar with it and to be able to also fill in the the DMP. And you also need to provide so all the articles needs to include data availability statements. Even if there's no data associated with the article you still need to to to provide that. A couple of useful tools that might interest you. I mentioned it already open explore and it's you can search for publication research data to repositories. It has, it's basically an aggregator of all the different types of information they exist, but it's publication data softwares grants organization. It's used by the European Commission, the research graph days behind it is used by the European Commission to make sure that you are compliant also with your data and publication, the data and publication requirements. Amnesia is for compliance with GDPR basically is where you're going to analyze the personal data or sensitive data and it's a useful tool so that you basically don't have to fall under GDPR because the data becomes anonymous. Argos is a tool to write data management plans it's free it's open source. It's, you can create different versions of it so you can update it throughout the life of the project. Then you can even publish it on Zenodo. And it has the Horizon Europe DMP template already embedded in it. And there are some community calls if you want to participate in this. Okay, so I've mentioned up to now the requirements. So I'm going to, it's a bit more towards the end or during the it's the reporting basically on the monitoring of those of those elements of open science requirements. You will always have the, the project offices and the reviews that will be monitoring compliance around the open science, the open science mandates. And you need to report basically in an instructed way on the portal what's your, your achievements basically. So in terms of the continuous reporting you have different probably familiar with the, the portal, you have different tabs that are relevant to open science. The publications is basically for publications and you can import automatically it will suggest based on so for instance if you were to upload it on on Zenodo. And you will link it to the project and then it will automatically appear on on the portal and you can accept it as part of the project or not so it will already be pre-filled for for you. That's why it's important to deposit on the trusted repository because it makes also your reporting easier. They are, I'm going to go into details of this, but because you'll have the slides, but there is a few fields that you need to make sure that are that are correct. In terms of data sets, it's the same. It will, if you deposited it on the trusty repository, such as another it will appear in the suggested data set and you can just accept them the same way you did with the publications. There's also the results and other results and tabs, which can be slightly confusing because of the names. So the results focus on the any discovery series product services methods that you come up with as part of the project, whereas other results is about reporting other type of resources like softwares, protocols, prototypes, workflows. So yes, it's, it might be a bit confusing at the beginning but I think after this, it's well explained on the portal. So up to now I've explained, I've covered basically once you've already have a grant with Horizon Europe, what your requirements are, and we're going to take a step back. Because I also wanted to give another view of during the ground proposal, what are the open science elements that you need to cover. Again, this is a site so that you get an overview of which parts of relevant to open science. So in part A, so the application form, you have to list publication data sets that are relevant, that your publications are relevant to the call. And in part B, so the actual project proposal, you have to under excellence impact and quality and efficiency of the implementation, you have some elements to mention around open science. In terms of publications, so part A, you always want to be, the publication use sites have to be available in open access, meaning that they have to be on a trusted repository available. If you share, if you cite one of your publication that is not in open access, you won't be considered as valid for the current proposal. One thing important because you probably know that the commission doesn't evaluate researchers and the researcher assessment isn't done on impact factor anymore. So the impact factor of the journal that you mentioned is not relevant. It's the actual quality of the content inside the paper that will be. And you can also give some insights in what you want to publish, including the commission's platform, Open Research Europe. In terms of research data, it's the same, the data you list needs to be fair. And so openly available if possible. An official data management plan is not needed at this time, but they will ask you very similar questions to it. So, in a way, you're doing like a mini DMP inside the grand proposal. So you already need to start thinking about it. And there's a distinct web package project management that must include the DMP as a believable. And as I said before, it's by month six. In the budget, don't forget that the article processing charges, the open access fees for full open access journals are eligible. So you should include those. Any help with data curation costs can also be included and you should definitely think about who and how you're going to manage the data. That's also why it's important to have that in the to think about this mini DMP when you're submitting the proposal. And anything related to engagement of citizens will add basically like bonus points to your applications and you can include them in the budget. And so just a couple of tips I can give in terms of the grand proposal in terms of the open science is to be as specific as possible. And so you don't want people the reviewers to try and find the information of what you will do with the data and you want basically to to prove to the commission that you know what you're doing and that what will be done in the in the proposal. And there's a few special cases, so the ERC and mercury fellowships. So in the ERC, there is no explicit evaluation or requirements for the open science, but it will always have a positive impact if you include them. And it doesn't have a specific work package. But it does have, it does require a DMP. And for the mercury actions, it is open science is quite a big important aspect. It will be considered under the excellence criteria. And, and it also needs to include any training activity and career development that has a focus on open science for it to be scored better. So there's a big focus on open science in in in those schools. So I mentioned until now, the requirements, but there's also a lot of other different types of open science practices because open sciences and umbrella term. And so I'm not going to go into details, but I'm going to leave those slides for you if you're interested. And basically, while the mandatory open science practices are required, so you will, your score will be lower if you don't address them. The recommended open science practices don't have a negative impact. They will only have a positive impact if you include them. So if you include citizen science, for instance, that will be a positive. But if you decide not to do citizen science, it won't have a negative impact. So, yes, there's a lot of different elements to it. Pre-registration is basically where you will publish the plan of a study. So the research question, hypothesis, research days, design, how you're planning on analyzing the data before you even start doing the research. So pre-registration, if you're planning on doing that, I would highly recommend adding it inside the grant proposal to show that you're really trying to make your research as open, transparent as possible. Pre-prints is, as I mentioned before, the version when you, before peer reviewing. So Open Research Europe is an open peer review process. So it doesn't really have a pre-prints, it's immediately available. But there are some pre-prints service that you can use to, so archive for physics is the most known one, but there's now a lot of different ones that you can use. And yes, I would always recommend sharing your work as soon as possible, even before peer reviewing. Yes, so then there's public engagement that can be done in many different ways. And if you are going to do public engagement, really think about demonstrating in the grant proposal what you're planning on doing that will improve your, you will get a better score. And citizen science are involving directly citizens in your research project is also something that will grant you something that the European Commission does really favor. So if that fits your project, then again, I would recommend trying to include that. So just to conclude on this presentation and before we ask for and open the floor for Q&A. I want to emphasize that it's, I know it's a lot of things around open science because as part of a grant you already have a lot of things to think about, not just the open science. So I would really recommend from the start she designed an open science strategy. So not just create a DMP or you know but really have a plan in terms of how you want to all those different requirements, all those different optional recommended practices to fit in your project. And yes, be as specific as possible in the grant proposal during the project implemented so don't write the DMP two days before the bill of all this due because it takes time so I would recommend starting from month one because it does take time to do and to review. Yeah, and make sure to report everything you do. And as I said for the DMP for instance, it's a living document so if there's any issues coming up, it's okay to change it. It's okay to, you know, change strategy during the project. Nothing is set in stone. So, yes, please keep track of those issues and continue moving forward. And yes, so we run this, this webinar three times a year, the date for the next one is already out there. And on this, I'd like to thank all of you. And I'll have a look at the, the Q&A now. So, I have a question. Most leading journals in our field impose embargo periods for self archiving possible. So we are forced either to pay a fortune in every more expensive APCs or not to publish in this journal. It is correct. Is there any way out? Yes. So embargo periods and the difference, big difference between Horizon 2020 is that embargo periods are not allowed. So yes, in the past, it was allowed by the European Commission so six months for or 12 months. Now that's not, that's not possible. So yes, you are required to, if the publisher doesn't allow you to use the rights retention strategy, then yes, you do have to pay for APCs. But again, you would have to find that money elsewhere because hyper journals would not be covered. But I would really try and go for trying to include the rights retention strategy, this, this statement when you send it. So, even if the, the publisher might not appear to want to, you can still try and then they will tell you, no, we, we don't accept the, the rights retention strategy statement. So yes, unfortunately, if you can't pay for hybrid in another way, or if they don't accept the rights retention strategy, then you do have to find a different venue for for publishing. Articles uploaded in our academia or research gate considered archived. Yeah, so I should have mentioned that. No, the straight answer is no, the academia and research gate are social websites, but they don't fit in the definition of a trusted repository. So they are useful as for you as researchers. But, and you can't share them there. But, but no, they're not trusted repositories, you need to find one that they specific to your field or a generic one like then order. And what about archive apparently does not fulfill all metadata requirements. The, the, you know, has with horizon Europe. Okay, so if you look at the pure definition of the horizon Europe, what is considered a trusted repository. There's, I think, up to now only three trusted repositories in the world. So the commission, maybe I shouldn't say that. The commission sometimes does things that like sets things that is a bit too much in advance, even if it doesn't exist yet. My view on on it, and I don't think it's an issue from up to now it hasn't been an issue brought up by the commission is trusted repositories is this loose definition of a repository that at least has minimum set of criteria like having a persistent identifier like a DIY and and has metadata and all this that is endorsing your community. So as, as long as it's robust, then it is considered as as as valid for for publishing. The one thing I do want you to mention is archive as a preprint server so you can upload your, your work as a preprint, then have it published and then change the version that is on there from the preprint to the author accepted manuscript that would make archive as a trusted repository. But if I'm not mistaken and may correct me if I'm wrong, but I don't think that's the case. You cannot upload an actual paper on archive. It's a preprint service before peer reviewing that has the option to update it with the peer reviewed version. But yes, so far, in terms of like the pure definitions of the EU in terms of trusted repositories. I would say archive is still considered as a trusted repository. Horizon Europe project reimbursed only publication in fully open access journals. What about books should the open access book be published by a publisher that publishes 100% open access, or could the publisher of the open access book be hybrid. So again, any publication that is peer reviewed falls under the open access mandates. So a book, so a long tanks format and monograph would also have to be made full of made available in open access. But it doesn't have to be the final version that is in open access. It's the same as with articles. So the on the publisher's website, for instance, the books, you could be You have to pay for it.  So you need to at least have that version. One thing to that I mentioned is that the it doesn't have to be under creative commons attribution license. It can be more restricted. But books also have to be open access. And in the same thing with article you if it's full open access full open access book publisher. It is absolutely Compatible with with the grant so you can you can ask for For the grant to cover those those costs. Okay, apparently there's a problem with the DIY let Athena answer on this shouldn't have but okay. And Could you Could you discuss creative commons licenses we've currently listed CC by However, we'd like to know what other person identifiers have used in the past and why there's a tool on the creative commons website to help figure out which license might be best. But we want to make sure we're complying with open science while maintaining certain rights. And I can't really answer this question without knowing exactly what you're referring to. It will depend on what What's your licensing. So if it's a publication, it has to be CC by days. That's the role. If it's data, it has to be CC by or CC zero or something equivalent. If it's software. It's not mandatory but It is recommended by the European Commission and It is recommended to do an open license and so it really depends on On On the type of Elements that you want to be publishing. So if Yeah, if it's if it's data, it's more CC zero if it's publication. It's CC by There are other open licenses But in my experience, the creative commons licensee are the easiest to implement. So I don't see really the The point of trying to use another one since this one is widely available If it's software, it's it's it's a bit different. Why is it important that the MP is required by month six That's just the rule that the European Commission has set The reason why the European Commission does that is to make sure that you know what you're doing with the data. So if So a very Stupid example is if you're managing personal data and you need to within the consortium you need to share it with different Partners and especially if those partners are located outside of the EU then how are you practically Sharing that that data What tool are you using what platform is the platform secure? Are they any The security protocols are in place to ensure that there's no data leaks on this kind of things These are things that you need to think about and you need to put them in the in the DMP to make sure that You have thought of them and that's what the Commission wants is to make sure that You know what you're doing, but they want to make sure that you know what you're doing And also because a lot of the time it's something that we might think about but we might not Concretely write it down so people might be using different file naming conventions and to it's to avoid any Confusions as to how to Organize your folders organize your your your files within the consortium Are there any numbers or percentage on how well the rights retention strategy is received And image most generals will just reject the paper if the it is mentioned And I don't have an actual figure my feeling is that yes, it's still something that is Let's say optimistic Although I have had experiences where researchers I think one of the elements that researchers are don't feel in in power So they feel like the power falls completely in the hands of the the publisher Which is not true in reality you have a lot of power because if you all decided to tell the publisher no that's how we wanted you could definitely do it We've seen examples of that And I've had experiences where I've Recommended to authors to send a message to the publisher and the publisher did accept So It really depends on the actual Publisher we know that some publishers are a bit more Conservative let's say but the general checker tool will help you Check if it check on on that Is ERC eligible to publish in open research Europe. Yes, definitely anyone that it falls on the horizon Europe It's specific branch, but it still falls on the horizon Europe. So yes And could it be possible to have the aspect that differentiates self archiving from publishing? So publishing is when you Do the actual peer-reviewing process and it will be available If we talk about the traditional publisher it will be available In open access for instance on the publishers websites The issue with that is that if one day let's say the publisher And goes bankrupt The website won't be maintained and so the link will just die The self archiving that the point behind it is to deposit it on a repository which has the role of a long-term preservation of research So the biggest difference is this long-term preservation of your work to make sure that it is available For anyone to read for free in in the future So that's the difference is publishing is from the Publishers websites and self archiving is you doing it on a depositing a version on on on a repository What about publication in different less scientific outlets? Newspaper or the conservice conversation can we do or do we have to deposit them in trusted repositories? So if they are Maybe I should for next time I should emphasize on that it's only peer reviewed The mandate only falls on the peer reviewed articles So if it's not peer reviewed you don't have to do it. It's not required But it is recommended by the European Commission and I personally also would recommend Uploading it on the trusted repositories such as another because it will provide you with this DOI this Persistent identifier meaning that it will never the link will never break Which can make it easier to to share because sometimes Articles in newspaper for instance might not be widely available So it can be also a way of sharing with the greater public what you you've done and it's also important as one of those Other types of resources of outputs that you did for the project that doesn't fall in the traditional way of Of publication or data Can we deposit the author accepting manuscript in more than one repository as another and the institution Yes, absolutely. It might be redundant Because From You might want to deposit in only one repository because you want the more say traffic to it the more downloads from one place And to make sure to see really in one place that impacts your your work has But yes when I was working at the previous University I would upload it on both The institution and on the note of that was the personal choice Because there was an institutional mandate also So yes, that's absolutely fine. It's just a strategy you think need to think about whether it's The best strategy or not in terms of Yes traffic to your downloads and views to your to work So for publication if they are not peer reviewed they don't have to deposit it in a trusted repository and they don't have to be reported It's as I mentioned you don't have to deposit them on a repository but There's no There's no point not reporting them because that's A really important that the commission doesn't value just the publication and the data they value other type of outputs So this is not fully open science. It's more of Dissemination and outreach But the commission is definitely interested in in all the different outputs that you you do during the project. So even if it's not mandated is definitely something Positive for for you as part of the project to to do so would still highly recommend doing it How shall we proceed if the data collected to not completely belong to the researcher The communication of objects in museums here usually the data can be used for research But not shared with others without specific permission of the museum and as the researchers we have no leverage over this Yes, so As the commission mentions is as open as possible as close as necessary They might be some elements that are not in your control. If for instance you work with a private company They might not allow you to To provide everything in openly This is another case where you can't you might not have the specific commission Again, that's perfectly alright. You just need to Inform In the dmp for instance why you won't be able to open specific data to the public and You just explain this on my situation the museum doesn't allow me and then that's okay There's no right or wrong answer as long as you justify everything. So If it was a different Case where you you were saying I don't want to share because I said but then the project officer might say well, I disagree with this I think there's still room for you to open it but in this specific case. No, it's from Another Member in your Yeah, you don't have to if You're not required to if you if you can't If you don't have the permission Will there be another webinar scientific reporting so far it's not planned by by open air. No How exactly will the content be evaluated is a novel view what sorts of aspects are seen Equality even when those aspects are made this highly depends on the reviewers and the project officer There's no right or wrong answer. You probably Well, if you have been funded by under the European Commission that it really varies from Review to review and from project officer to project officer. There some will be much more involved and others will be much more Do what you want so it really depends on the project officer. There's no right or wrong answer. You probably know Well, if you have been funded by under the European Commission that it really varies from On the actual work people rather than the Specific Set of qualitative Questions and some journals offer the possibility to buy the open access for fee And these fees eligible for funding. So this is the difference between full open access and hybrid journals if the Journal only allows Full open access. So you have to pay whatever you have to pay fee. Then yes, that is eligible if it's a traditional Subscription based journal, but you don't have to pay for open access. But if you do they will Make it open access then those costs are not so eligible Considering on the open access publications in proposal may be very probative in certain areas of research What should people do when the major journal in the field and open access So remember that In the grant proposal we are talking about publications that have been published So the mandate of immediate open access is not In place that we are talking about is open It's available in open access meaning that For a lot of Publishers there's an embargo period and that can varies between 12 and 24 months So if your work is not available on a repository in open access you can check That That you can open it up and then just add it to a repository In open access so there's a difference between the requirements during your project which have to be a very specific set of Of Sets of license and immediate open access and What is for the grant proposal which they just means that you they want you to Provide an An open access version to your work In a DMP should we deal only with open research data or is it more general any type of data used or created by the project Such as deliverable created software minutes of meeting It's Research data in general so minutes of a meeting is not considered as research data But software definitely is a type of output. It's not necessarily just data but Any other type of outputs could be Added and because when you create a software you have specific files That Created and so you want to mention okay. We are going to create Whatever type of files we are creating in the project and we're going to store them here And this is what we're going to do so minutes of a meeting is Not research data in itself so it doesn't have to be added but anything that is Part of the research output like official research outputs of the project should be included in the DMP When should there be the data publisher the latest publication data for an article So the metadata needs to be provided as soon as the data is generated So much before the publication date The data itself should be made open as soon as possible meaning it could be before the publication dates But obviously you might not want to do that because you want to make sure that the publication is there first so because sometimes people might be Afraid of scoping and this kind of other groups, you know analyzing the data and publishing Before them so that's the perfect valid reason to put in let's say embargo on opening the data but the actual metadata so the To to make the world aware that the data is Exists basically there has to be as soon as possible Do you need informed consent from parts men to place the data in a control repository Yeah, that's that's ethics and informed consents and GDP out there. So all those types of rules always always apply If you're dealing with sensitive data and so I see genetic sequence data and this kind of things There's an extra step I would say of making sure that the data is secure So as With everything if you're doing your grants or before when you're writing I would Go with the data protection officers sit down and make sure that you've considered all the The venues for GPR compliance and a lot of the Organization universities have a chief information security officer also that Deal more with the IT aspects and so definitely contact those people to make sure that your Your Infrastructure the IT infrastructure is the best as possible to protect the The the data to double check embargo piece a lot in Horizon Europe, but not patient and no, it's a reverse So H20 20 was before now in Horizon Europe in H20 20 we could Were allowed six months for Stem sciences and 12 months for social sciences and humanities Under Horizon Europe so the current calls it needs to be immediate open access And just checking that the Yes, so there's another Common the problem here is the scientists at sitting between a rock and a hard place Articles and necessary to advance one's career and get grants and be good widely recognized publishers usually have more articles submitted than they can publish Yeah, there's I am not I understand the frustration I'm here presenting the The requirements set by the the European Commission they are Really strong reasons why the European Commission does it like this because without any change it just research would not go forward it would be Published it would still be very opaque about And we saw it really well during the pandemic when there was a real need for opening the the research to to advance on on vaccines and all that I understand the the frustration because it is a very difficult Situation to be in because for your career you do need to kind of follow the rules that were like the previous rule But at the same time you're in a transition period where hopefully in the future it will the research assessments will and it's already changing but The research assessment will be more widely accepted as not based on just the impact factor on the way it's been done the last 20 30 years, but in a more in a more transparent transparent and ethical way So I can completely understand the frustration and it's something that is Difficult to to deal with But But yes, unfortunately, that's the current you're in a transition period so it's it's always the hardest but hopefully we're going in the right direction because so there's another final comment about Question about open access book with the cost for an open access book be eligible if the book plug it But publisher is hybrid and publishes all the book that not 100% open access Also the cost to be level they should be publishing on the open access books. Yeah, so it's the same as for general articles if it's a hybrid publisher Then you cannot cover the The the book processing charges under the under the grant you would need to find another way but again you don't need to publish it in an access if the publisher allows you to retain your rights on the also accepted manuscripts and So applies to see by license to that and then upload that to a repository then you are compliant Okay, so if there are no more questions, I hope this was Useful The you can always ask more questions to the help desk at open ed at the EU and I'm behind I'm the one answering those emails anyway So yes, if you have any more questions don't hesitate sending us Email and on this. Thank you very much Thank you very much for joining everyone As Jonathan said that you can always reach out to us if you need to know we hope to see you at the next one. Have a great afternoon. Bye. Bye


Hi, my name is Jayant. I'm the employee of Nordic Semiconductor. This is our 9160 product. It's the world's smallest cellular LOT SIP MZU product. It can, now I will introduce the Deccan R Plus, Deccan R Plus protocol. This protocol is a small corner of 5G standard. The Deccan R Plus can help you to build a mesh network. The mesh network don't need any SIM card, don't need any station, don't need any cellular station. They can build a mesh network and communicate with each other. But not using LOT? No, they are Deccan R Plus, they don't use cellular. No cellular. No cellular, they are no cellular mesh network. So, what is this? This is a small, this is a standard, this is a standard of 5G. It can solve the problem of many devices connection. It can connect one million devices in one square kilometer. Oh my God, one billion. So, it's an alternative to Bluetooth? No, it works in 1.6 gigahertz. 1.9 gigahertz, yes. Bluetooth is 2.4, right? No, it's not, yes, Bluetooth is 2.4 gigahertz. It's not Bluetooth, it's a non-cellular mesh network. And how far is the range? It can up to two kilometers. What? And no SIM card? No, yes. Open spectrum? Yes. Open? Yes. But in most cases, we communicate within one kilometer. One kilometer? So, I can take this, I can walk for 20 minutes? Oh no, you didn't need a special antenna? You didn't need a special antenna? Special antenna. Yes. They build a mesh network and there I use my computer as a gateway and it runs some Docker service and it can control, and now, and it can connect it to an MQTT broker. So, I can control them using my, I can control them using my Windows clients. I can control them, control their LED. What's the bandwidth? About three megabits. Three megabits, about. Is this related? Yes. This is it? Yes, it is. The Nordic 91. Yes, it is the prototype of our Nordic 9160 product. This is Nordic 9160. Nice. Is it mesh production? Yes, frankly, it's a demo to show to our customer, our customer can refer to this to create their own product. Nice. Is it brand new? No, it's not brand new, but this technology is brand new. Brand new. This technology is brand new, but this is not brand new. So, you added this to the existing part? Yes. Just with a software update? Yes. And it works? Yes, it actually works. Nobody else do this, so many people are doing this now. This technology is the world's first release. All right, so what is the DECT 2020 NR? It's like the spec of 2020. It's related to what you just talked about? Oh, because it's not part of 5G before, but it's now being included in 5G standard. So, for this to work, do I need to pay China Unicom or China Telecom? No, you don't need any SIM card. You don't need to pay anyone. Yes, you don't need to pay anyone, but if you want to connect it to the network, you need a gateway. For this demo, I use my computer as a gateway. But that doesn't have the DECT NR? Yes, it has USB connection to this. These four devices, what is this built? They are all DECT NR plus nodes. They should be. But what is this? It's the same chipset? The same chip, same 9.16. And can you put this inside the laptop? Yes. But can you put this chip inside the laptop? No, I connect it to the laptop, use the USB cable. And in my laptop, I run a service to connect this to the cloud. All right. What else is happening here? Very special. Is this the same NRF 91? Yes, it is the same NRF 91, but it don't run DECT NR plus. What is this about here? It can run NB IoT or LTM. All right. This is cellular technology. This is non-cellular technology. Yeah, it's very popular now.  Yeah, thank you. This is very popular because it has very low power. It can reach 2.7 micro amps. It can reach 2.7 micro amps in PSM mode. Nice. Where are you based? I'm based in Shanghai. So Nordic has big office in Shanghai? Yes, Nordic has office in Beijing, Shanghai, and Shenzhen. And what else you show at the booth? OK. What other cool thing? What is NRF cloud? This is off-cloud using the Wi-Fi location using off-cloud. I will explain what is Wi-Fi location. Our Wi-Fi chip can scan the SSID over there. And it upload the SSIDs to the NRF cloud. And in our database in the cloud, we can get the location of their SSIDs so you can get your location. It is more accurate than the GTS and the station location. You can see here. All right. You can just hold it. OK. You can see here. Here is our location result. It's true Wi-Fi location. Don't need the GTS. True Wi-Fi location. Yes. Database, these are the devices that had the Nordic semiconductor inside. Everything has a... These are devices from our customers. What else is really cool in this show? Oh, here is Wi-Fi 6. Yes. Here is the Wi-Fi 6 chip. NRF 7.72, OK. 7.92. Wi-Fi 6. Yeah, the Wi-Fi 6, two bands, I say. It supports 2.4 gigahertz and 5 gigahertz. The most cool thing is it supports a TWT feature. You can see here. Here is the TWT feature. Our devices, our chip can communicate with the router AP and communicate with the AP to set the interval. You can set this interval to one hour or one day. So you can get very low power consumption. Please see here. One day you can have like 10 years battery. Here, oh no, that is too long. Here I set the interval is 10 seconds. But you can set it to one hour or one day or more long. Seconds will be many days battery. Yes, you can see here. The lowest power consumption here is 12 microamps. So if you increase the interval, you can get a very low power consumption. Nice. This is Wi-Fi 6 TWT. And it should matter at the booth. This is matter. And what's the matter? What's the latest with matter? What do you do? Making all your little boxes there. I'm going to talk to him about matter. Cool. There's some different solutions. Matter is a new smart home protocol. And you can connect very different companies product like Apple, Amazon, and Google. If you have an IP protocol version 6, and you can get a matter connection. Nice. Now, what can IP protocol, internet protocol version 6 communicate if they can run in matter? You can run in Wi-Fi, thread, and internet. If you get an internet protocol version 6, all the matter things are connected. You can see all the devices. Some of them are from our demo. Some of them are from Google. And some of them are from Apple. You can see them in the Apple app. You can control them. Nice. Cool. All right. So many other things, right? Yes. So many things like here, audio, development kits. This is L.E. Audio, Bluetooth L.E. Audio. Nice. Do little speakers. Yes. The classic Bluetooth audio is very, the power of classic Bluetooth audio is a little bit high. But the newest Bluetooth standard, the B.L.E. can support the L.E. Audio. The L.E. Audio can connect to one devices to many different speakers. And it has a very low power consumption. Multi-speaker solution. Yes. Low power. It has a goal. That's just one. Two. Oh, don't touch it. All right. Yeah. Cool. All right. So thanks a lot for this tour here at the Mobile Walk Congress Shanghai. Cool. All right. Please ask again. I don't hear. No, thank you very much for the tour. Oh, yes. Cool. Thanks a lot. OK. OK. See you.


wirwch cywifiedd o washaol, neu mae'n gallu rhoi na gweithio eich oedgio. Fel ychydig eich hun, ydych chi'n siaradau ymddiad. Rydwch chi'n credu fforddau yn gallu'r cyflodyniad. Mae'n cael eu gwirio'n meddwl i eich gael yma, ond yn wirio hyn. Wrth gwyno yw i'n cymryd yw Nysyswn. Rydw i'n cyfryd yw Nysyswn, rydw i'n cymryd yw Nysyswn? Felly mae'n amlwg ydw i'n gweithio ar draws eich pwynydd. your teaching may not be all that, so perhaps at the energy level a little bit, it's going oh! Come with me for two seconds, we're going to go有 gwyntgar o bobl yn cael gwyntiaeth measureth and off you go. Because by doing that you will then put yourself back in control and the children who are in your room will start to see you as the person in charge rather than the person just managing a situation. Redirection. So, if they are fiddling with somebody else, if they are interfering with something on the table that you don't want them to fiddle with, this is ground breaking, put the goddamn resources under the table, they don't disappear. I know there are TAs that have an absolute breakdown if you move the pen tray off the table, but put it underneath them, they haven't got anything to fuss with, and then you can redirect their behaviours to where you need it to be. And that isn't about being draconian going all eyes on me, give me five, because that's some of my ADHD children, they will do some interesting signs when everything is at the same time. Think of how you can control that without it looking obvious that you are redirecting that behaviour, because you will start to see what gets them interested. So, if you are in early years and you have got them on the carpet, if you are keeping them on the carpet for more than ten minutes, I would fiddle, I would be interesting, I have been touching my friend, I have watched you all sitting here now and you are either writing on your pad or you are doing this with your phone or you are fiddling with your hair or you have gone to that zen place of it will stop in a moment. We all do it, so why are you expecting a small person to be able to regulate themselves? You have to help with that, so if you know that they cannot concentrate for that long period of time, then think about your planning, think about what your lesson structure looks like.  Managing expectation. So, if you are in your classroom and you know that that child will start doing this when you are talking and nobody outside of our profession understands how irritating this is, because I bet you have gone home and talked to your other halves and gone, they went up and down. They just look at you and have to say, why? Why is that annoying you? You could snap at any moment, especially when you catch their eye and they stop. Nobody outside of our profession, you can do that anywhere, do that anywhere and you watch teachers suddenly lose their necks. But if you know that's going to happen, then manage your expectation of what you're going to do. Is that something you can live with? Because if you can live with it with one kid, could you live with it with two doing that or three doing that? If that's not your expectation in your classroom, then put a stop to it. Remove the things that they can tap with. Give them something like fiddling frenzy. Little bits of play don't play with.  Don't forgot to give them fidget spinners because they can smash windows. But a little bit of glue tap. Salotate that round so they can stick it together. All sorts of stuff you can give them to get them to concentrate and not wiggle and annoy you. We use something called Do Disco. Is there any early years people? So we are spread the happiness school. So we use Do Disco with ours because it doesn't stick to the carpet and you don't get your cleaner giving you a filthy look. And also it's non-triggering for ASD children. The colour is a good colour.  And it will stay soft for about eight months. It's a good investment. You get 10 pots for about six quid. So it's not that expensive. If your expectation level for you is different from the TA or the TA's expectation level is different to yours, you need to become consistent because that's the only way it's going to work. So you have to allow some of your battles to drift a little so you can deal with the big things that you've got to deal with.  You manage the other bits but you work on the one thing that really is going on your nerves. If they're going into the hall and they can't line up, practice lining up. If they can't line up after playtime, practice lining up. It was the stuff that I used to do when I first qualified back in the good old days where you had a nature table and nobody really cared what the national curriculum was. But practising those things are brilliant, especially when you've got interesting children because taking them into a bigger space makes them excited and anxious all in one go. If you've ever taught them years when you take them into the hall, the immediate thing they do is slide across the floor or they run round going...  If you are going to practice, I would practice with your interesting children being in different places in the line because normally we put them at the front and we hold their hand really tight late. Now, very good when somebody else has distracted you of manoeuvring themselves to the middle of the line and you haven't worked out where they are until you've got into the assembly and they're sitting down. And it's usually when you've got visitors in. And there's you on one side and you're TA on the other side and that child's being interesting in the middle and you've got that choice of can I direct them without looking like I'm directing. So you're either sitting there going... ...and then you're trying to signal to your other half... ...and you're waiting for a hyn. Hopefully something's going to happen that they will stand up that you can walk up and bring evidence.  Because there's always a child that gets in your way and trips you up as well so you've got 48 and killing three rows of infants. You have to think you would not go into your classroom to do maths in English without being prepared.  You're the professional, be prepared for it. There are some things that children will do that you can never be prepared for and sometimes your most interesting children will actually outperform you. They will go, oh my god, look at this, I've got an audience and then you're like, oh no, don't quite know what to do. But what you do from that is manage it and then learn why it happened. You don't learn why it happened, it's going to keep going on. The one thing if I can get you to do, the last two things on this bit, is simplifying your requests and laughing.  The cat is just looking at it and the dishwasher hasn't been emptied and the things that you've asked to be put away have not been put away and you suddenly snap. You suddenly have that whole meltdown moment and the person that's with you at that time says one thing like, should I put the cat on? And you go off at them. The reality is that's how your children are feeling on a day to day basis, minute by minute in your classroom if they're interesting. So if you want them to do something, there's no point doing a whole nice big verbose speech, simplify it. I need you to sit. I need you to sit down. Sit, I don't get where you sit. Sit down. Let's not be too specific about where. Let's just get you sitting down and then I can deal with the next bit. Think about your language. If your voice is starting to sound very robotic while you are talking to them, you are losing it. So simplify how you speak. If you are going to be in control, be in control. If you don't laugh at what you see, you'll take it home and be sad. So it's really important and what we do at Waterside is that we debrief every day for five to ten minutes and we talk about all the brilliant things that have happened in the day and then we talk about all the things that have been a little bit interesting so that every member of staff can check in so that before they go home we've parked what's in our brains because the last thing you need to do is to take home those children in your head.