What's going on everyone? Sam here with late sports cards. We are ripping six boxes. Whoops. Let me go back here. Six boxes of 22 Panini Contenders football hobby for Jason T. So good luck here, Jason. Jeff, it'll rip tomorrow on drip with Kyle. It'll rip tomorrow on drip.  There's still like four or five orders ahead of you, but once he gets to your break, it'll be, I mean yours is relatively quick too with the Panini ones and the Spectre Foto. So again, sorry I couldn't get to it tonight, man. It's just dude Shopify was literally out to get me tonight. Out to get everybody tonight. It was crazy. All right, good luck. Would you say like this? Trey McBride. You've been on card auto for the Cardinals. A breaker. That's the worst it's ever been. Yes. That is the worst. That is the worst experience I've ever had. What Shopify was today? John Elway to 99. Got no base ships out of this, no bat base. All the inserts do hits numbered stuff as well. Jettas. It's kind of crucial to the base. Ricky Williams game day ticket. There's Alex Wright's rookie ticket auto for the Browns. Tyler, I was here. What's up? Tj Watt power players. That's pretty much clipped. Let's make contenders. Jerry writes. There's Mario Goodrich for the Eagles. Rookie ticket auto. Supernatural drink London MVP. That press guy. Hi, you got it, Jeff. Let's do it, dude. That was awesome.  Congrats, man. Glad he was JJ Watt. So awesome, dude. So I was so amped for you. Cam Taylor Britt, rookie ticket auto for the Bangles. Not every day. See a one-on-one. It's not easy to pull a one-on-one swoosh out of NT as well. Game day ticket Dan Marina. Kenneth Walker. It's pretty, there's a lot of people that are really into it right now. I would say Anthony. It's getting pretty into the raise down here because they're having a great season so far. Marcus Jones, rookie ticket auto, yeah. The Patriots. They are 11-0 currently. First team since, like, 1980 to start 11-0. That is the Pairings. Touchdown Tandems. Chase and Burrow. Tremac Duffy. Rookie ticket auto for the Sheeps. Nice one there. Yeah, we got an actual auto in there. Nice. MVP contenders in the home. Yeah, there's a lot of people that are pretty hyped. Like Jake, one of our top loaders, and Kyle are both huge raise fans, so they're pretty hyped about it. All right, so I'll do it for box one. There you go. Jason. It's going to be Auto Charlie Colar for the Ravens. Very cool. MVP contenders Joe Burrow is a Darian Butler rookie ticket auto for the Raiders. Drake London, supernatural. There's nice Brock Purdy on the rookie ticket auto for the Niners. There we go. Congrats. Jason. That's awesome, buddy. There we go. Get that mag for you. Legendary contenders Elway. Dude, those are a process to build those. Gladiators JJ Watt. Yeah, not great. Isaiah Spiller, variation horizontal auto on card for the Charges. Skymore, rookie of the year contenders. That is a Herschel Walker, legendary contenders 2.99 for the Cavals. Game's a ticket to the Amarino. MVP contenders Jay Jettus. Thank you, chef. That's a power player, Snicks Pajosa. Oh, we got one of those case hit things. Kurt Warner on the admit one. Nice one there for the Rants. Can we figure out those are case hits or not? I think so. They're super short prints. Sub, Joey. Unfortunately not, man. Fortunately not, dude. I apologize. But yeah, we got, we had Shopify, our back end made us not break for about an hour today. It literally set us like an hour hour and a half behind Burrow. Yep. So there's like, I got to like two personals tonight. There's a couple more in queue. Avery Williams for the Falcons. I apologize though, Joey. My bad, man. Just got absolutely wrecked by Shopify today. Channing Tindall for the, what's up? Nothing. For the Falcons. Don't worry about that, Sam. Just do what you do. Legendary contenders Steve Atwater. Oh no, Channing Sharp. Channing Sharp. Sonny Gonzalez. There's a Crystal Lodicon for the Chiefs. Ticket Autumn. Jones Contenders. And Jamal Adams. Power players. All right. Box three now. Donterio Drummond. Nice. On the blue. Variation for the Cowboys. Is 299. Parents of 75 of 99. Cleo Mack. Pashed My Homes. Game Day Ticket. Nick Chubb. Isaac Taylor Stewart. Rookie Ticket Autumn. Top Contenders. MVP Contenders. My Homes. Winning Ticket. That is Jay Jedis. Power players. David Montgomery for the Bears. I know, right? Good Lord. Jay Jedis. Game Day Ticket. Oh yes, he did actually. MVP Contenders. Jaylen Hertz. He did. I don't, I don't understand. I would have just, I would have rather just re-signed Jamal Williams. Right. Nicoby Dean. Nice one there for the Eagles. Rookie Ticket Autumn. You know? I don't know. I don't know. What happened to you? What happened to Swift? Like, I know he was dealing with injury, but he, what happened? Like, is he not the star? Tom Brady. He probably will be, but they'll probably just, yeah. Well, he got vultured a lot by Williams in the end zone. Yeah. To be fair too. So take, like, take Jamal Williams out of the question. That was Steve Young's Game Day Ticket. Take Jamal Williams out of the question. I think Swift's numbers are a little bit better. There's Kevon Tibidow. Rookie Ticket Autumn for the Giants. There's one there. G-Men. Gaming Pierce. Rookie of the Year Contenders. There's Terrell Bernard. For the Bills. Alec Pierce. Rookie of the Year Contenders. Power Players. Jordan Brooks. Gladiators. John L.A. That is Vilas Jones Jr. On-Card. Rookie Ticket Autumn for the Bears. MVP. Chris McCaffrey. Give you this too before I forget. Box number four. Tony Gonzalez. Game Day Ticket. Rookie Ticket Autumn for the Titans. There's Isaiah Pacheco. Jamal Adams. Power Players. Slant Man. Not Slant Man. Blitz Boy. Herschel Walker. Watch Mal Adams. Oh, yeah. There's nice. Blake Willis. Variation. Rookie Ticket On-Card Autumn for the Titans. There you go. Congrats on that, Jason. There you go, buddy. Christian Watson. Rookie of the Year Contenders. Probably. Variation. Pink. Zeke Elliott. 2199. B-Doc. Gladiators. Jelene Ramsey. Josh Allen. I think we're still trying. There's a Ticket Stubb. Josh Pascal. 46 of 93. For the Lions. Still trying to figure out why Micah Parsons and Mack are on that card. The Notable Parents. Derek Carr. Contenders. We need to reach out to Micah and Mack on Instagram. They're like, what is the deal with this guys? Why are you on a card together? They had a conversation and we tagged both of them. Hey, what's with you guys? Tandems, Carr, and Devontae Adams. I'm sure they'd love to be in a group chat together. Jaylen Virgil. Rookie Ticket Autumn for the Broncos. What did Mack Jones do to you? We'll message Mack Jones. What did Micah Parsons do to you? That is Nick Cross for the Colts. Rookie Ticket Otto. Josh and Amonra. That is Jaylen Warren. Nice one there. Rookie Ticket Otto for the Steelers. And Round Numbers. Who's that? Pivotot and Sauce. Fox 5. Power Players. Bobby Wagner. Drake London. Supernatural. I've got like three of those so far. Just Supernatural. Drake London's. Very cool. That is MVP Contenders. Cheetah. Tyrica. Radiators at JJ1. Perion Winfrey for the Browns. Rookie Ticket Otto. MVP Contenders. Derek Carr. Radiators. Bo Jackson. There's Round Numbers. That's Kingsley Enoch Barray for the Packers. Rookie Ticket on. It's like an ice dude. It's a big ice cream out of this. Christian Watson. What's up Alvin? Unfortunately not James. If you order now we'll go tomorrow with Kyle. We'll be over on drip ripping all the Personals that are on the website as well as that come through on drip. So he'll be live over there tomorrow night which will be good. So anything that didn't go tonight will go tomorrow. David Bell on the Draft Glass. 52 of 99. On-Card. Jalen Ramsey. Alvin's been to bed and woke up in the morning and we're still dreaming. That's awesome. When you put that in perspective, I said check out. It's kind of wild actually. Jordan Mason for the Niners. Well so what happened JT is Shopify. We use Shopify. Wasn't communicating with the back end of our website. That is nice. Bailey Zappi. Rookie Ticket on-card. Josh Allen. So I'll tell you once I get these two packs done I'll got you JT. I'll explain kind of what happened. Why we why we finished so far behind. I mean everything sold out. It wasn't like you know we were waiting on spas to sell out or anything. Basically what happened was for the first from about 5.30 to 7. Nobody's orders. Nobody who bought like bought spots their orders weren't showing up. So basically it wasn't communicating like Shopify wasn't communicating with the back end of our website showing that spots were sold out but people were sending us compromises and all that kind of stuff. So we had to wait until like Shopify was going through maintenance. We had to wait till they updated and finished maintenance and then all of the orders came in. So we were like an hour and a half behind at like after the second break. So we just never really caught up. So it's just it was just technology was not on our side tonight. Not on our side at all. There's Kyler Murray. So basically like if you were to buy like a spot in contenders say you bought like the Panthers and contenders it would give you a confirmation number and take money out of your account but it would not show up on our back end of our website that you took a spot. So yeah it was just brutal. Yeah no but yeah absolutely of course we're gonna get through it for sure. Marvin Leo. We can take it out of for the Steelers. Yeah I did what we had to do there. I had to roll with the punches JJ. Well it happens. Happens. It wasn't really in our control unfortunately.  It was just out of our hands. Duos of Donald and Trent Williams. You know it's real late hours. That is a Kaleb Evans for the Vikings you know it's real late hours when this game probably went at like seven o'clock. Yeah. And we're already in the seventh inning of the replay of the late replay. Sure. That's nice. Sam Howell rookie ticket variation. A lot of quarterbacks coming out of here. Congrats on that one there. Jason get that mag for you buddy. That's what the fourth quarterback right there. Willis 30. Zappi. Zappi and yeah geez man nice. Seven of 25. Devontae Adams. Red Alps rookie of the year contenders. Jim Kelly. Power players Nick Boussa. A few more packs to go here so that's a pretty successful break overall I would say. Yeah. Pretty successful half case. Peppy Williams for the Ravens. Traylon Berks rookie of the year contenders. Supernatural Drake one. MVP contenders Tyree Kill. Micah McFadden. Rookie ticket auto for the Giants. And Son of a Knight is your last rookie ticket auto for the Giants. Peace. That'll do it for your break there. Jason thanks again for the support my friend. Really do appreciate it. We'll get them right out to you buddy.


variable time schedule completely independent of behavior often uses an antecedent intervention to reduce problem behavior ladies and gentlemen that was recorded yeah I can read which is a whole nother chapter 25 yeah yeah literally copy a text okay should we actually record something it's going go it's going hello no non-contingent an example that we want to do parades okay non-contingent reinforcement which is delivering reinforcers or known reinforcers non-contingently on whatever behavior it's used as an antecedent strategy for problem behaviors and it doesn't matter if it's on a time schedule or a variable schedule or a thin schedule or a thick schedule or a continuous schedule or whatever the hell schedule it's just done it's reinforcement for the sake of reinforcing if you will so an idea in the classroom is a kid has maladaptive behaviors of dealing with attention the teacher's going to deliver detention rather frequently or more frequently that lowers the value of attention for said kiddo and ultimately reducing problem behaviors another idea would be a guy in a parade just throwing candy on everyone he's just delivering attention non-contingently and to whoever at whoever at any random interval or magnitude or anything he's just giving on all the lovely stuff non-contingent reinforcement


from Las Vegas, it's theCUBE. Cover EMC World 2016, brought to you by EMC. Now, here are your hosts, Stu Miniman and Brian Graceley. Welcome back to Las Vegas, the CUBE's coverage of EMC World 2016. I'm Stu Miniman joined by Brian Graceley. Happy to have on the program for the first time, Ted Bardaz, who's the senior director of product management in the EMC Converge platform division. You're working on some of the big data solutions. Ted, welcome to the program. Well, thanks very much. Thanks for having me, I appreciate it. So, you know, we at Wikibon on theCUBE, we've been covering big data since it was before it was called big data. EMC, of course, everybody knows kind of the storage pieces underlying it, but give us a little bit about your role and what your team does today. Okay, sure. So, our role really for the big data solution is all about delivering a fully engineered and term key platform to really empower companies to get insights out of their data, whether in the enterprise and even external stores, to be able to get insights to improve their business performance, right? To really get business uplift in there, whether that's, you know, additional services or products, better customer experience, reducing costs or operational efficiency. So, if you think about the stack, we have the data lake that can be Icelon or ECS. We have big data systems, the converged infrastructure, the racks and blocks, and then we really have the solution which is really all about the user experience that's really empowering both the data scientists and IT to be able to deliver business value to the business stakeholders and the company. Yeah, so when I look, you know, we've got a lot of experience with EMC solutions and on the VCE side, they really productized a lot of the solutions. Can you talk a little bit about, you know, what does that mean going together? You're all under kind of this umbrella that used to be VCE. We've talked to the pivotal folks. We're talking to the hybrid cloud people. How does your group fit into that whole narrative? It's a, so it's really about combining the different assets and especially in big data, EMC really has, you know, a very strong position in terms of the technology and IP around big data. So really one of the key roles that we have is to take those assets, take the data lake technologies, take the pivotal big data suite, take the converged infrastructure and really focus on the key business goals of the end user and weave those technologies together into a really compelling user experience. That's one that's driving business objectives, right? One that's delivering up against a lot of companies and especially here at EMC World, they're really looking for, how do they become data-driven companies and how do they mix that into how they execute? A lot of the business is changing around them. I was speaking to a company last night, their market was shrinking, they realized they needed to do business and generate a different business model and they really were approaching and saying, how can you help us leverage big data and leverage the data that we have to really allow us to pivot so we can compete effectively? So we wrapped those technologies together in order to make that very consumable and allow businesses to attack those kinds of business objectives. Obviously, you know, typical engagement, you guys are going to stand up the environment, make it very, very easy to stand up for IT, give an environment for the data scientists to get to working, what goes on beyond that? How do you help them, especially for that customer that says, what more can you do for me? What's a typical engagement look like and what are some of the outcomes they're starting to see? Okay, so it's great that you picked up on it because we have the data lake, we have the data systems, the big data systems and I mentioned the big data solutions, but we also have our big data services and our professional services that really has programs that go in as we engage a particular customer that has a big data workshop where they sit with the customer for a week or so and they really sit down and identify what's possible and what are really nice high value targets that they can go after. They take that to a proof of value concept where they actually bring in the data scientists, they bring in the data and they actually prove out the delivery, the ability to take those insights and really to deliver a positive business value and then they stay with that customer to bring them into production. So one of the ones just before I came here, we had Pichanga, which is a customer who purchased our big data solution. They're at Casino in Temecula and they've brought the business data lake in and really looking at one of their key objectives was how do they understand what they call their gamer? How do they understand their gamers, what they're playing, how they're playing, so that they can really engage them to give them a better experience, give them additional products and then also get them back because a gamer always has a choice to what casino they can go to and then the area, right, there's choices there. So they really, as an example, they really wanted to get deep into the analytics on the information that they had from their game card, from their gamers and to be able to understand how they better serve that customer and then how they get them to come back. Can you unpack for us the key stakeholders in the environment, who's driving the engagement, who's working on the engagement, who benefits from it? Okay, so I think there's really three key constituents. I think the real drivers that we're seeing as we're getting into the workshop is really coming from the business and the business vision area. So like with Pichanga and like with other customers, there's someone sitting on the business side that's really thinking about particular outcomes that they think they believe they should be able to achieve based on what they've heard about big data. There's quickly a marriage that occurs between that and the IT teams, right? Because it isn't, hey, let's just do big data, right? You have to set up your environment, you have to create the right environment for that, both in terms of setting up the right infrastructure to run these big data tools, but also in terms of setting up the environment in order to empower the data scientists, right? So our key, a typical engagement, we'll find a business that's going to approach us in terms of, hey, we think we have some ideas on how we think we should be able to use big data, get the workshop going, quickly transfers over to the IT delivery, IT ops and the IT team in terms of what is the environment and what really needs to be stood up. And then the third thing, and I know I really enjoy the Wikibon reports, I'll give you a throw there, but you know, the dearth of data scientists, right? Even as we were doing the Pachanga talk, you know, they had said, hey, if you're going to go after this, recognize you're going to need lead time in order to get good data scientists. So it starts with the business value, quickly comes up to the infrastructure and the IT visionary married to the business visionary, but with a key focus on really empowering data scientists so they can really ring the value, the insights that are going to deliver value to the business, and those are the key constituents. Yeah. Big data, the term, the concept has gone through a lot lately. You mentioned data scientists, you know, for a while, very, very hard to find, very much in demand. We're seeing technology changes, you know, Hadoop to Spark, real time. But what part of big data has sort of, you know, done, solved problem and what part is still sort of challenging for customers? So I think that it's really kind of a very interesting market and that it's nascent, right? That technologies are changing, Hadoop, Spark, you know, what's going to be next. I think the key thing and some of the key challenges and some of the things that we're looking at are really one is empowerment and self-service of the data scientists. So one, how do we just get it so that when they have that insight that they want to go after that there's not, you know, 15 different tickets to IT that they're waiting for and then eventually maybe they go out and do shadow IT. So one of them is just getting the environment set up. But some of the other ones are really around the data and curating the data in order to apply the analytics too.  So a lot of what we're looking at is really both the self-service environment, so that data scientists is really empowered to get going with an insight in the data sources to be able to understand them. And with what they want to achieve, stand up that environment. But then give them a very efficient path in order to understand how the data's coming together, how to model it and look at your analytic models, be able to connect to additional data sources, sample them, take a look at how it completes your model and take that through the process so you can't apply your analytics. The analytics are changing so fast that you can't just focus, you can focus on one. But, you know, I think what's more important is really focusing on the environment that allows it to be stood up and allowing them to prepare the environment with the data that the analytics really want to run on. So Ted, looking forward, what do we expect to see kind of down the road from the EMC Big Data Solutions team? So I think pretty quick, you know, as we just talked about the ingestion and the data curation, you'll see some really nice work with some partners that we have. And so we're targeting, you know, sometime around Strata Hadoop, New York to really bring out some of these capabilities. We're deploying them now in a services-led opportunity so that we can really learn from customers and real-world use cases. So what goes in the box is reflective of what really happens. Secondly, I think that a lot of the customers who want to leverage Big Data have asked us to flex into the cloud. So really taking our solution and putting it on our hybrid cloud environments to be able to allow them to flex out, to be able to run their critical, really data proprietary or connection on-prem, but still allow empowerment to Big Data, but if it's going to interfere with that mission critical work to be able to support them out in the cloud. And then third, it's about, you know, insights are great, but it's about actioning the insights. So the third thing is really blending in with our native hybrid cloud capabilities so that you can have your data scientists on one side who are self-empowered, can quickly connect to the data, bring it into the environment, see these insights that are going to deliver business value, but then marrying those data services that data scientists is using to over to native hybrid cloud so that you can take those and actionalize them, right? You can build an embedded system in your operational model. Let's say if you're doing predictive maintenance in an oil field and you want to tie that into a service truck to go out and service a well, you know, based on that. Also dashboards, of course, and reports for insights on strategic business decision-making, but then also really a lot more that we're seeing customers really gravitating to is how do they reach that end-user customer? How do they get that mobile app? How do they get that application that really creates a much tighter relationship, right, with their customers that's really targeted at how they buy, what they buy, when they buy on the devices, you know, anywhere, anytime. The culture, right, that's happening right now is people are expecting immediate response. And the notion of building these insights and getting some more of this real-time capability into a platform that can deliver cloud-native applications that can really reach the customers and satisfy that sort of frequency or that rate that they want to run at, that's going to be key, and that's what a lot of customers are looking for. All right, well, Ted Bardas, appreciate you sharing with us how we're closing the gap from just storing information to actionable insights. I look forward to talking with you more in the future. We'll be back with more coverage here from EMC World 2016. You're watching theCUBE.


So I will not give that much of an empty-based approach, because that's not our core business. We do empty, but we use your standard approach. But I want to speak a little bit from the perspective of the Integrative Moment film, because there has been quite some discussion over the year. There also ought to archive these kind of models. So Lundi Scale was also a thing there where people have been thinking about what to do. So what are we speaking about? Well, these days in structural biology, it's very common that there's not a single technique that's going to give you all the answers. To combine data, you need to use simulations in combination with all kind of experimental data to get to your model. I think one of the nice examples is the work of Andres Salli, where he's been modeling in several stages the nuclear core complex. And in there, you would find atomic-stick representations, you would find things that are more coarse-grained at the same martini type of coarse-graining, but you would also find proteins that are simple spheres or cones based on whatever knowledge is there. So it's a really newly-scaled kind of effort, and it was for a long time no real way of representing those data in a systematic manner. So this was very much linked to the software that was used for that. And also visualization of these kind of things was problematic. So the developer of Canera are also very much involved in this effort. So can we actually use a file format or use a description of the data and the system that allows also these relations? So I should know that I'm leading the coding structure, and I should be able to visualize it. It's no longer a simple sphere that pertains to atoms. So in principle, if you look at the field and the related software, the software has an integrated modeling but also docking and field docking, which might be doing a big issue regarding the data. There is no real consensus on the data format. I think most software in the field is still using the PDB as the old PDB format as a consensus. Some of them can handle MFC as well, which is officially the new format of the PDB. There is no efficient way of storing large data sets, or for sharing. It's not really arranged. And if you look at the software also, different software will have different ways of sharing things because it depends what you are doing. If you are doing docking, you might just deal with rigid molecules, and the only thing that you need to store in principle is the transformation matrix. So rotation, translation, and you're done, and you can use the entire set. So that's very compact. And if you look at publications, if you are looking, there may be a PDB file attached to a supplemental directory. So that's the thing. And usually, there's never the full data that are shared in terms of communities. And it's very rare that you find actually the settings for people to do docking. So at least in the docking field, it's not very common. So while we are running the problems also, we are participating in experiments like Capri where you have to do docking, scoring, and all of that. And the scoring part, we get PDBs from all over the community, and we run into problems that normal PDBs are equal. There is some standard software that are not producing the proper PDB format, and this might just give you trouble. There's many software that are actually truncating those PDBs right after the coordinates. You would not have occupancy key factors or even the fields that are coming after that that also contain useful information. So because of that, we started developing, actually that's not the PDB that I wanted to do, but these PDB tools, which is a simple manipulation of PDBs, but also simple validations. And we use that also in our portals. So we are operating. So Hadoq, the main usage of Hadoq is through a web portal where people submit data. But we have to do a heavy validation of the data, and commit a voice to your portal, or extend it. So people have been submitting work documents to the portal. They edit the PDB file in Word, and they don't realize what PDB file is. They don't know that it's a text file. And then they submit a word of human, and of course it doesn't work. If it doesn't work, please fix it. But even if PDB doesn't support PDB anymore? Well, it's still there. So you can still download it from the site when the official format is MMC. So everything is on our portal also. We should support that and see if it's as good as output, if you want to do things properly. But I think there's a lot of software out there which is still not yet ready to handle MMC. And so what you will see now is that people are dealing with MMC, but they are converting back to the old PDB format, and then you're dealing with that software, which is perfectly fine if you are looking at small objects. If you have more than 9,999 residues in your system, then you screw it up. Or you have to start playing with chains and all of that, which is doable. So in terms of what we are doing, in terms of data processing, the server has been operating now for a few years. And they are two stages. So when people submit their data, but also when they get back their data, and this will be the start of the result page, we do provide for us to get a complete data structure, but it's based on a directory structure of PDB, but also since the start we have been providing a parameter file, which is actually a self-contained text file, which contains the parameters of the data. So even if the users don't see all the options, for the single interface the portal is just giving to PDBs and a list of residues, and that's it, they get this file which they can download before the run starts, which contains probably 500 parameters that they could in principle change, and it contains the coordinates and it contains the data development. So that's a self-contained file, which we are always saying if you want to save one file, save this one because there is also an option in the portal to upload this file as one file upload and rerun the simulation. So we're also advertising if you want to provide a supplementary value or something from your modeling, do give this file because someone else can take it, come back to the server and hopefully get the same results unless we have changed things on the server or you're running a different model. So that's a simple text file, so now we are moving to a JSON version of this file in a new server that Mikael has been working on, and also in the context, so HTA5 was mentioned just before by Eric, so in the context of the deep learning project, we are also storing data in HTA5, so maybe that's something we have to consider for the future. So one of the problems that we have on local systems is that we are generating lots of small files, so it's not like MD where you have large, maybe compressed files, but a few files that are very large. So thousands of thousands of small files is what we are doing, and this is causing a stress to our system at some point. So we have to think of ways in the future to reduce the number of files. So now that one of our data sharing, there are a few repositories where you can come with a few terabytes of data, and I don't think that's enough to accept terabytes of data. So that's one problem in the fields. So they want an initiative, so this was published in 2016, that's the SP Grid initiative, Structural Biology Grid, it's in the US, and they were funded to provide the data repository, and the first end there was to actually store the primary image from X-ray physiology, so actually what the detectors are recording. So the PDB is the archive for the structure and also the structure factors, but the structure factors have already interpreted data from the images, and they wanted to collect here the raw images, so there's a very long list of orders here, but they also accept structure models. So we have been using that to publish actually our data set, so when we do some new work and create a benchmark and then demonstrate what we can do on a given system, we upload our data here, and that one, it's about, there's one here and another one, so the most recent data set that we uploaded is this one, it's about membrane recording complex, it's a benchmark where we provide so all the input files, so the input file that I show you which is self-contained is provided also but also all the models that come out of the docking and this particular data set says here storage requirement 1.3 terabytes, so that will be uncompressed, so they do compress the data, but so we are able to put on this repository our models, so I don't know if they will start accepting trajectories, that's something we will have to ask for that, but they do accept, at least they do accept our models, it's not like the docking community is dumping all their models there, but for us it's a good way of doing things because we can indeed put a terabyte of data in there and it's fine. There's not so many metadata associated with that, so what you get is kind of, so they use our scene, they provide a script to do the things, but the metadata are rather limited and you have a DOI also, so actually when we publish the paper related to this work, we provide a DOI to the data set, but that itself is not really machine searchable, for example, you will find the data set and the publication of the lab name, but you will not find all the details of what is in the data set, and there is no specific structure of the data, so we do provide our own dietary structure, which is related to the way Hadock works, but another software might provide something completely different. So for us it makes it easier to share it like that way, because the format is not even and not brought anything. Okay, so now for integrative modeling, since a few years ago there is a new site from the PVB, which is harvesting integrative model, so the PVB itself will only accept, say, hardcore explainable structures, although there is some models in there, some of those models are coming from Hadock. There is a dictionary which has been defined, so there is a GitHub site which is freely accessible where you can see what has been defined in a model in order to allow the deposition of those integrative models. For example, defining that the molecule has a code shape is something that needed to be added to the model, because PVB's MMC format will not handle these kind of weird particles. What also went in there is we want for Hadock, so we have been adding things in there or requesting additions, but there is much more than that. I can on this, but I want to be able to say that mutation of residue x is important for the binding, so that's information that will go in there. And there is a website where now we can actually deposit these kind of things, so this is an hybrid explainable tool, modeling structures, and we also try to connect in there all the data associated with the model. So this came up together because there has been a task force from the worldwide PDB that has been set up to think about what we need there, and this was a meeting which was a big three years ago at EBI, so I'm actually in there, where different people from different aspects of the fields have been thinking of what is needed to be put in this model, so it's kind of what we are doing here at a smaller scale here. And the recommendations from that, and this was published, a recommendation, so okay, we need to archive the models, the experimental data and the metadata. We need to have a flexible model representation so that you can mix atomistic with cross grain with this weird shape or whatever that you want to describe. You need methods for validation. That's not simple. Build a federation of models and data repositories. I'm going to say a little bit more about that. And you want also to establish publication standards. So what should people report when they publish these kind of models? So what are the, what is captured in the model? So you will have sequence chemical information. You will have structural data repositories, experimental repositories, so the model doesn't capture everything, so in data repositories where you will put your data, you will just link to that, but it will be part of the file itself, of this MMC5 integrative modeling file. So you will describe the chemical entities, so the small molecules. If you have a cofactor in your system, whatever it will be described here, it will describe also the starting models. So there was a discussion about which PDB and 3D you use as starting points so this information will be there. And spatial reference that you use to build a model. So you have a few cross grain from MS, they are going to be described there. Yes. One of the problems the open force field initiative has had is that none of these formats that describe the chemical molecular components describe the chemistry. They describe the connectivity, but they don't really tell you like is this a double bond, is this a single bond. Do any of these file formats have a path forward that you know of that will describe the... I feel like in MMC there was a way of describing actually the force field to some extent. So this is working progress. So this MMC, this integrative modeling force field, the MMC format itself is constantly, the format is not changing but the fields are either to represent new stuff as we needed them. So it was very much starting from the work of Sally so everything that was there was to model or to describe what was coming out of the integrative modeling platform of under Sally in and then we started also contributing and we say well in our model we need to be able to describe a number of arbitrary residues that are part of the interface and this was not in the model of Sally because they were doing things differently and this has been added. So this is very much progressing so the model was not defined from the start and this is what we need at that signal we add stuff as we need. This could be a starting point for something else where you say we need to add those additional entries there. This model, this integrative modeling and SIF format is kind of decoupled from the BDV one so the BDV is very hard to have things say it's a kind of procedure to do that and this is much more flexible in a way it's a different repository but there is a... so it's evolving basically and you can look at what is in there already so there is also a software library that supports the dictionary and they have APIs to that So currently what is linked in all of that so there are connections to EMDB that would be a crime SASDB for the SAS data VMRB for MR data there is mass spectrometry cross-linking type database what people can see FRAT data is also a database for that so the idea is not to store everything in that particular repository but to link as much as possible to existing ones but if nothing is existing then it's okay to add new entries so the example was to be here there is a little bit of a mutation which is coming from this table in article X so you can describe that in the model so we have been starting and actually Mikkel has made the work to enable support in HALO for this format so we want to facilitate the position of models in this PDB archive or PDB dev archive so the new HALO portal is not creating this kind of models and the idea will be that the layout of a docking typically is not one model but an ensemble of models which can be associated with energies and there are the first three models of that so we want to capture all of that in one file that we provide to the user so that the user can add a little bit information to the file but then go for the reposition because the reposition system now it's not like the PDB where you are guided through all the fields that you need to enter this is not yet at that stage so we should support as input this NFC file and we should support as output of all those models so we have now built it as output of the server there are different options at this time it's still a fair model a fair structure but ultimately we want to add one download parameters where we capture all the models that we presented to the user at the end which could be different clusters and with all the associated energies clustering statistics so one file should contain more and hopefully that will also allow you in camera camera X to visualize the complete document run in one go because camera X is also working very much with this format to visualize clusterings statistics and all of that so opportunities if you think also for integrative model PDB DEB as a repository it's funded actually for US brands and this time the PDB Europe is also involved in that so there is storage there if you think of MD we need also a different model possibly to share the data which is probably the pilot data model which is probably a good one because you need to involve also the data infrastructure providers not the data generators but the people who are willing to store the data so in all case we use as big grid I don't know how long they will be happy to accept models maybe at some point they will say no more we will have to see we have this European Open Science Cloud we are European so maybe there are opportunities there to do things because it does provide networking, compute and behind these data as well so we are working in this European Science Cloud and we have this series label agreement so we are only using compute actually in the Science Cloud these days but we have for example a 250 terabyte of dedicated storage of course that's not going to help you as a community because this is one of the data sets so that's peanuts but maybe to organize the data astronomy is using those resources different communities are using resources so if you have a good use case to say well we would like to operate some server or portal to collect the data maybe we can make a run for it and that's it I just want to acknowledge a few people here so I got a number of some grid that is the one who is really leading this integrating modeling MMC format so she is the one to contact if you want to have your double bond described in the format because it is required if you decide to build on that and then Berman was the former head of RCSB and John Westbrook is the boss of MMC when it comes to the PDB pretty much so these are all the PIs from the work by PDB so for the UK there are people in mind of Samir so he is involved in this initiative as well although most of the integrated modeling initiative is happening in the US so Anversa is very much leading this Tom Bordert Kamera and Radix it was very much involved and on the other side was also part of this so Miguel was doing all the work actually and the idea is we need to promote by providing ready to kind of ready to deposit files promote the sharing of the data so we will do it ok