Well, hi everybody, John Walls here on theCUBE, continuing our coverage of AnsibleFest 2021 with Tom Anderson, Vice President of Product Management at Red Hat and Tom. You've been the answer man for theCUBE here over the last week, 10 days or so, third CUBE appearance. I hope we haven't worn you out. No, John, I love doing it. So it's great to have you at the event. Oh, great. And thank you for letting us be a part of that. It's been a lot of fun. Let's go and look at the event now. As far as big picture here, major takeaways that you think that have been talked about that you think you'd like people, customers to go home with, if you will, although a lot of this has been virtual, obviously, but I say go home and make that figuratively. But what do you want people to remember and then apply to their businesses? Right, so being a product guy, I want to talk about products usually, right? So the big kind of product announcements from this year's event have been the rollout of really the next generation of the Ansible Automation Platform, which is really a re-architecture turning it into a cloud-native application, an automation application itself that scales to our customer needs. So a lot of big announcements around that. And so what does that do for customers? That's really bringing them the automation platform that they can scale from the data center to the cloud, to the edge, and everywhere in between across a single platform with a single easy-to-use automation language. And then secondly on that, as automation starts to shift left, we always talk about technology shifting left towards the developer. As automation is also shifting left towards the developer and other personas in an organization, we're really happy about the developer tools and the tooling that we're providing to the customers with the new automation platform too that brings development of content, automation content. So the creation, the testing, the deployment, and the management of that content across an enterprise far easier than it's ever been. So it's really kind of, it's a little bit about the democratization of automation. We see that shifting left, if you will, and I know I've said that already, but we see that shifting left of automation into other parts of the organization beyond the domain experts, the network engineers, or the storage experts, et cetera. Pushing that automation out into the hands of other personas in the organization has been a big trend that we've seen and a lot of product announcements around that. So really excited about the product announcements in particular, but also the involvement and the engagement of our ecosystem, our upstream community, so important to our product and our success, our ecosystem partners, and obviously last but not least, our customers and our users. So you hit a lot of big topics there, but so let's talk about the edge. That seems to be a fairly significant trend at this point, right? Because trying to get the automation out toward the data besides, man, it's where the apps are, right? It's where the data is, where things are happening out there on the edge. So maybe just dive into that a little bit and about how you're trying to facilitate that need. Yeah, so a couple of trends around the edge. Obviously it's the architecture itself with lower capacity or lower capability devices and compute infrastructure at the edge and whether that's at the far edge with very low capacity to devices or even at near edge scenarios where you don't have data center IT people out there to support those environments. So being able to get at those low capability, low capacity environments remotely, Ansible is a really good fit for that because of our agentless architecture, the agentless architecture of Ansible itself allows you to drive automation out into the devices and into the environments where there isn't a high capacity infrastructure. And the other thing that we've seen is one of the commonalities that no matter where the compute is taking place and the users are, there always has to be network. So we see a lot of network automation use cases out at the edge and Ansible is, you know, the de facto network automation solution in the market. So we see a lot of our customers driving Ansible use cases out into their edge devices. You know, talk about development too and this kind of this change in relationship with Ansible and DevOps and how that has certainly been maturing and seems to be really taking off right now. Yeah, so for, you know, what we've seen a lot of is, you know, is becoming frictionless, right? How do we take the friction out of the system that frees developers up to be more productive for organizations to be more agile to roll out applications faster? How do we do that? We need to get access to the infrastructure and the resources that developers need. We need to get that access into their hands when they need it and in a frictionless sort of way, right? So, you know, all of the old school traditional ways of developers having to get infrastructure by opening a help desk ticket to get servers built for them and waiting for IT ops to build the servers and to deploy them and to send them back a message, all that is gone now. These, you know, subsystem owners whether that's compute or cloud or network or storage, their ability to use Ansible to expose their resources for consumption by other personas, developers in this case, makes developers happy and more efficient because they can just use those automation playbooks, those Ansible playbooks to deploy the infrastructure that they need to develop, test and deploy their applications on and the actual subsystem owners themselves can be assured that the usage of those environments is compliant with their standards because they've built and shared the automation with those developers to be able to consume when they want. Both sides happy, agile, efficient developers and happy infrastructure owners because they know that the governance and compliance around that system usage is on point with what they need and what they want. That's a big win-win and a very good point. I always like it when we kind of get down to the nitty gritty and talk about what are customers really doing? You know, and because we can talk about hypotheticals and trends and developing and maturing rates and all those kinds of things but in terms of actual customers, what people really are doing, what do you think have been a few of the plums that you'd like to make sure people are paying attention to? Yeah, I think from this year's event, I was really taken by the JPMorgan Chase presentation and it really kind of fits into my idea of shifting less left in the democratization of automation. They talked about, I think the number was around 7,000 people associates inside that organization that are across 22 countries. So kind of global consumption of this, building automation playbooks and sharing those across the organization. I mean, so gone are the days of, you know, very small teams of people doing, just automating the things that they do and it's grown so big and so pervasive now. And I think JPMorgan Chase really kind of brings that out, tees that out, the kind of cultural impacts that's had on their organization, the efficiencies they've been able to draw from that, their ability to bring the developers and their operations teams together to be working as one. I think their story is really fantastic. And I think this is the second year, I think this is the second year that JPMorgan Chase has been presenting at Fest and this year's session was fantastic. I really, really enjoyed that. So I would encourage anybody to go back and look at the recording in that session. And then there's GameSys groups to the other end of the spectrum, right? Financial Services, JPMorgan Chase, global company to GameSys, right? These people who are rolling out new games and need to be able to manage capacity really well. When a new game hits, right? Think about a new game hits and the type of demand and consumption there is for that game and then the underlying infrastructure to support it. GameSys did a really great presentation around being able to scale out automation, to scale up and down automation to be able to spin up clusters and deploy infrastructure to run their games on an as needed basis. So kind of that business agility and how automation is driving that, or business agility is driving the need for automation in these organizations. So that's just a couple of examples, but there was good ones from another financial services that talked about the cultural impacts of automation, their idea of extreme automation. In fact, one of the sessions I interviewed Joe Mills, a gentleman from this Card Services financial services company, and he talked about extreme automation there and how they're using automation guilds and communities of practice in their organization to get over the cultural hurdles of adopting automation and sharing automation across an organization. So a wide array, obviously, of customer uses and all very effective, I guess, in telling their own story. Somewhat related to that, and as you put it out there too, if you want to go back and look, these are really great case studies to take a look at. For those, again, who maybe couldn't attend or haven't had a chance to look at any of the sessions yet, what are some of the kinds of things that were discussed in terms of sessions to give somebody a flavor of what was discussed and maybe to tease them a little bit for next year, right? Just in case that you weren't able to participate and can't right now, there's always next year. So maybe you could give us a little bit of flavor of that too. Yeah, so we kind of break down the sessions a little bit into the more kind of technical sessions and then the sort of less technical sessions, let's put it that way. And on the technical session front, certainly a couple of the sessions were really about getting started. Those are always popular with people new to Ansible. So there's the session that aired on the 29th, which has been recorded and you can rewatch it. That's getting started Q and A with the technical Ansible experts. That's a really, really great session because you see that the types of questions that are being asked. So you know you're not alone if you're new to Ansible. The types of questions are probably the questions that you have as well. And then obviously the value of the Ansible experts who are answering those questions. So that was a great session. And then for a lot of folks who may wanna get involved in the community, the upstream community, there's a great session that was also on the 29th and it was recorded for rewatching around getting started with participation in the Ansible community and a live Q and A there. So the Ansible community for those who don't know is a large, robust, vibrant upstream community of users, of software companies, of all manners of people that are contributing and contributing upstream to the code and making Ansible a better solution for them and for everybody. So that's a great session. And then last but not least, almost always the most popular session is the roadmap sessions. And Masimo Ferrari, gentlemen on my team did a great session on the Ansible roadmap. So I do a search on roadmap in the session catalog and you can see the recording of that. So that's always a big deal. Yeah, roadmaps are great, right? Because especially for newcomers, they wanna know how, I'm down here at point zero and I've got a destination of mine. I wanna go way out there. So how do I get there? So to that point, for somebody who is beginning their journey and maybe they're automated with the ability to manually intervene, right?  So what's the message you wanna get across to those people who maybe are gonna lose that security blanket they've been hanging on to for a long time and take the wheels off and go? Now, John, that's a great question. And that's usually a big apprehension of kind of full automation, which is, that kind of turning over the reins, if you will, right, to somebody else. If I'm the person who's responsible for this storage system, if I'm the person responsible for this network elements, these routers, these firewalls, whatever it might be, I'm really kind of freaked out about giving controls or access to those things from a configuration standpoint to people outside of my organization who don't have the same level of expertise that I do. But here's the deal that in a well-implemented, well-architected, Ansible Automation Platform environment, you can control the type of automation that people do. Who does that? Against what? Managing that automation as code. So checking in, checking out, conversion control, deployment access. So there's a lot of controls that can be put in place. So it isn't just a free-for-all automated, everybody automating everything. Organizations can roll out automation and have access to different kinds of automation, can control and manage what their organizations can use and see and do with Ansible. So there's lots of controls built in for organizations to put in place and to make those subsystem owners, give them confidence that how people are accessing their subsystems using Ansible Automation can be controlled in a way that makes them comfortable and assures compliance and governance around those resources. Well, Tom, we appreciate the time once again. I know you've been a regular here on theCUBE over the course of the event. We'll give you a little bit of time off as you get back to your day job, but we do appreciate that and wish you success down the road. Thank you very much and we'll see you again next year. You bet, thank you. Tom Anderson joining us, Vice President of Product Management at Red Hat talking about AnsibleFest 2021. I'm John Walls and you're watching theCUBE.


Today, we will briefly look at testing of SD models. Today's agenda will cover a few topics or rather the concept of testing of SD models can start with model debugging, model verification, model validation and sensitivity analysis. So, these are broad topics that we look at when we think about model testing. So, how do you want to do model testing? The perfect models are going to be difficult in the case of SD, since correctness of model is relative to the purpose and varies widely depending on the modular user as well as the modeling conventions. However, we need to build confidence of the model that we have built so that we can gain useful insight as well as present our finding appropriate to the purpose on hand. So, this is what we want to do. So, we want to test our model so that we can build our confidence on the model so that we can have some belief in the results that is going to do us. So, in model testing we should be designed so that we can uncover the various flaws or errors that we do in the modeling. Some are pretty straightforward if it is programming kind of errors, but logical errors are a little more difficult and we can use it to improve the model to make it better. However, we do testing to prove model is right, rather than try to uncover what is right model we will come to that later. Sometimes key tests need not be done, modelers fail to document results that is nothing new, it has been there for ages, then always we started computations, documentation has always been issued and modelers and clients of confirmation bias and preconceptions despite evidence to the contrary, sometimes you do not want the results to show what you want to or you are not happy with the results it shows, so expect the model to be wrong. So, we need to address these things systematically, we will start with a few basic steps and go ahead and look at how to validate the model etc. So, the first step towards this is model debugging, we already had an introduction to it last class and some time ago where we looked at a model description and try to uncover the various errors within the model, we already had an experience with that. So, what you want to do is debug the model consists of tracing the errors that prove the model from simulating properly and correcting them, it is pretty basic step. The common errors some of it are as follows, faulty numerical integration method or time step is being used, so one way to counter it is to reduce the time step and choose an appropriate method. So, what is written above on the right side of this arrow indicates how you have to counter that flaw, like if you have to use Renjuketa method, we use R K method, Euler method or the time step is too large instead, so we have to reduce the time step which is an appropriate time step, so that we can simulate it properly. A wrong sign is in stock equations, one way to avoid is to check and avoid the net flows, many times we end up instead of having an inflow and outflow explicitly, we can actually modulate as a net inflow. So, to do a net inflow, then we have to be careful with the signs, so that the model simulates correctly. Same point overflows as values are too big or too small or we end up dividing by 0, only way to avoid check that is to trace the computation, figure out at what point error occurs, look at the table of values and correct the model to see whether that is indeed that large value is it realistic or not. There are functions in Vensim like z, id, z or x, id, z, so this is when you divide by 0, what is the value to return? So, instead of returning, when you divide anything by 0 it will be indeterminate, to avoid that this x id z and z i z z can be used, you can look it up in Vensim's help, when you divide by 0 then what should it return, should it on 1 or should it return some 0, what should it return that we have to specify and Vensim supports that. So, maybe that may be required if indeed division by 0 occurs, what is the code the table function to see where is extrapolating more than what you desire it to be especially in extreme, in that case then we need to give the value such that it extrapolates correctly. So, two types of errors, one is a warning that the computation is beyond the table function that means extrapolating, in some case it may be ok, other is floating point errors where it actually indeed be dividing by 0 or due to some error in computations it is getting a large value that we need to fix. So, when you simulate and we get an error then that is something we need to fix and there could be error in the structure itself like flows are not connected to stocks, a drawing was not proper, etcetera. So, these you need to check the model equations and the structures directly. So, now we can use temporary hacks such as explore function or ceiling function or look at a separate part of the submodel of the entire model to see, understand the issue and fix the actual problem that is actually occurring within the model. So, that is the broad steps about debugging. Closely related debugging is this model verification, overall what we want to under answer is this question have we built the model correctly. It includes all the debugging steps, but also goes beyond to trace it and test the model to see of the all the logic is correctly modeled and captured as per the specification. So, this is what we want to do. So, that entails what we call as model verification. So, model verification starts with basic debugging and goes a little beyond that one also. We have few tools in Vensim itself, one of the two of it we have already used is check units and check model. They are necessary, but not sufficient. That means, even if you give the model and click check units, it says units are fine, still there could be errors inside the model. Based on what values are you giving, what connections you are giving, there could still be errors in the model. So, they are necessary, but not sufficient. So, we need to actually check for correctness beyond what we see here. Over the years people have come up with various checklists that we can go through to see if the model is correct. First is to check units and see if very proper names are given to the variables or it makes sense to us. No constants are embedded in the equations. We should try to mention the parameter values only before the analysis, choosing our appropriate time steps. Stock values can be changed only by flows. Every flow should be connected with a stock. We should try to avoid flow connections. We should try to avoid if then else on min max and other logical statement as much as possible, but the problem entails and we need to include it. We also need to use proper initial values and clearly specify them so that model can start in dynamic equilibrium. And lastly, popular one is to make model aesthetically pleasing. When we as we organically grow the model, we find that it is looking quite complex, but finally it has to be presented to an external audience. How do we make it aesthetically pleasing? So, one easy way is to use curved arrows instead of straight lines. Curves are aesthetically pleasing than straight lines and sharp lines. So, this is also quite important. So, some of these things may seem quite obvious that we ought to do, but many times in our case we do not do that because it seems too trivial for us to worry about, but unfortunately that is the one which ends up causing the errors or causing the various issues in our actual model. So, the one way or rather the only way to ensure that doing proper debugging and proper verification is to practice. So, that is what we are going to do today. We are going to take up a few models and try to practice the debugging. In fact, this time what we are going to do is I am going to lead the debugging, that is I am going to read the description, point you to different things so that you can observe and follow. Even if you are not able to catch up in the model, my suggestion is you go back and look at this video again to see how I am tracing through the model so that we can also follow the similar steps. So, typically how I go about checking the model is what I am going to go through. So, let us and for a so we have three examples we are going to do today's class. Reach out the example the model with errors is already online. You can download them from Moodle and when each scenario comes, we can try to open the model and see whether it confirms with our understanding. I hope I will remember to mention all the points that I am going to check, but let us see. Again these are only some of the cases that you are going to see. So, it is important for you to practice with other kind of models, actually make some mistakes at least from say for example, from the exam point of view. You may not get exact same errors. So, there may be any other form of combination. I try to give as many examples as possible, but let us see. So, first is let us just understand the model. No need to look at the Wensham model yet we have time for it. It is a very simple model. There is something called as masquerades.  It is actually native of North America and invasive species in large parts of Europe and North Asia. That is regions near Russia and stuff. So, let us go with this. Suppose there is a masquerade population area, initially there are 100 masquerades. So, as and when we read the description, we need to visually, not visually, what can I say? We need to imagine how the model is going to look like. As soon we use the term like population, masquerade population area, 100 masquerades. So, it could be a stock. If it is a population, so maybe it is a stock. So, let us picture that. Autonomous net increase in the number of masquerades per masquerade per year amounts an average of 20 masquerades per masquerade per year. So, that means we are talking about some net increase in the masquerade population. So, this must be a flow that is going into the masquerade stock. Suppose that each year, 10 licences are granted to set masquerade traps. These licences are valid only for one year and each person holding a license may set 10 traps. Assuming the number of masquerades caught per trap is proportional to the number of masquerades and catch rate per trap which is close to 0.2. So, minimally 0.195 and maximally 0.205. So, this is the only description given. So, the second part, since we are already talking about net flow, the second part may be something referring with how much is removed from the population. So, this must be the outflow within the model. Explosively, as you can see, there is nothing about birth and death that is given. But if you carefully observe the description, there is a word net given. So, this could mean there is something about birth and death that is happening. In spite of that, an average of 20 masquerade per masquerade is increasing. So, that is what the description that is given. So, now, we need to download and debug this model. Sometimes, when you open the model, it talks about scaling and preferred is 100 percent. So, you get the exact same size. This is the model that you will see. First is the first step is you look at the structure. So, we imagine there is some masquerade population, some new masquerades come in and some masquerades is getting caught. So, they are removed from the population. So, description is not fully complete, but given the description, we can assume that the masquerade is caught and terminated and not caught and released back into the population. So, there are some reasonable assumptions to make. There are some variables like how much masquerade is caught per trap, how many traps per license, how many number of licenses. It seems kind of structurally okay. The next we can try to do is look at the model and say check units. Units seems to be okay. Model, check model. Model also seems to be okay. Then we can quickly trace through the equations. So, new masquerade was about 20 masquerade per year. So, before we go into that, we can actually look at model settings to look at what is the time units. First item, you see that okay. All the description were in years and we have time units also in years. And let us look at this time step 0.0625 Euler method seems fine, seems reasonable, quite low. But let us see we do not know which is having impact. Then let us look at the equations. We just move the mouse, whatever the units pops up below that we can see. Unit seems to actually be fine. To open it, it says new masquerade into masquerade population and new masquerade rate is about 20 which is consistent with what numbers we have. See any change in constants is not that big of issue. We just need to ensure that it is fairly accurate. Units that is a bigger problem. So, masquerade population should be roughly the masquerade cot per trap into the proportionality factor as per the description. And number cot should be number of licenses into number of traps per license multiplied by number of masquerade per trap that should logically give us the number of masquerades cot. So, which is a product of all three, masquerade cot is into proportionality factor, traps per license is 10, number of license is 10 which is roughly the what the description has said 10 and 10 traps proportionality constant is 0.195 what is taken 0.195. So, minimally it is there. Right. So, seems okay let us assimilate it. At least let us see if there is errors. All right. Yes. Okay. We get this error floating point overflow. This is an error and error it says floating point error computing masquerade population at time 4.06. A simulation run length of 10 years at around 4.06 itself is getting a floating point error trying to save results anyway. So, let us click. Okay. Close it. Let us see the graph. The graph is growing. How is the graph growing? No. It seems to be growing hyper exponential. There is difference. Exponential means it has to have doubling times is constant here. It is growing hyper exponential much more than what it has to be. Right. So, there must be some error. There is 1 and 2. Actually, if you look at it, this is a positive feedback system. It has to keep increasing, but this is a negative feedback system. So, it has to decrease. Right. So, only descriptions it can have is exponential growth, exponential decay or equilibrium. Pinflow and outflow is equal. Right. This system cannot have an exponential hyper exponential growth. For hyper exponential growth, your proportionality constant or new masquerade rate or something has to keep reducing or keep increasing. Number of new masquerade should increase or proportional rate should keep decreasing. So, none of the proportionality constants are changing. Here the proportionality constant is 0.195, 10, 10. Right. So, none of the constants are changing. Correct. So, hyper exponential growth should not occur. So, I will try to follow my steps. So, but still masquerade population is changing. You can look at that population is just increasing all the way and what affects the population. Population is affected by both these flows. So, let us include that also in the table. I clicked the time down table and here masquerade population and then suddenly you find that new masquerades are 2000. New masquerade first period is 2000 which makes sense, 20 into 100, 2000. Number cot is 0.195 into 10 into 10. It should be 1, 9, 5, 0 which is fine, but it is minus 1, 9, 5, 0. Let us look at it. What is happening there? Let us look at the population here. It is new masquerade minus masquerade cot. Okay, inflow minus outflow. This is fine. Let us look at masquerade cot.  So, this minus should not be there because it is minus and then you are already in computing the stocks, it is minus of minus. So, it became plus. So, stock value started increasing more than it ought to. So, let us remove this minus sign. Let us click okay. Let us run the model. We did not get any errors when we ran it this time. Still we are getting exponential growth which is fine. For at least doubling time as you can check it, doubling time should remain constant. So, this looks reasonable for this kind of errors. It does not seem to be any other errors using the model, but these kind of small bugs also can creep into the model. So, even though when you ran it, it did give some results. It did not make logical sense. So, expectation is you actually look at the result and then we try to see how we can understand the dynamics and see whether the model inherently can cause it. When we move to sensitivity analysis and other concepts also, we will end up using these models itself. So, save the, what can you say, this version of the model. Now, we may not still be done. It says catch rate per trap is 0.2, minimum 0.195 to maximum 0.205. We can logically see, for example, Muscat population is 100 and this is 20. New Muscat is 100 into 20, 2000. So, instead of proportionality factor instead of 0.195, if it is 0.2, then we get 0.2 into 10 into 100 which will also be equal to 2000, correct. So, in that case, we need to get a straight line. So, we can check if the model is actually producing all the behaviors as per expectation. So, if it is anything beyond 0.2, then what should it be? It should have exponential decay. So, we can check if the model actually producing all the behaviors, only then it is a completely verified model. So, one way to do is without say changing the model as let us instead of MR195, I am going to write 200, click SIM setup, click proportionality factor and write 0.2. It is okay. Let us stop it. Now, let us do Muscat population. I am going to stop this. Fine. Let us not use SIM setup. Now, we will do data. So, MR200, let us change it. Let us go to the proportionality factor. Let us make it 0.2, click play. Now, actually we get two graphs.  It is actually being constant. Another is increasing exponential. You can change it to 205 as a simulation file result name and change the proportionality factor to 0.205, click OK, click run. Now, if we do the plot depropolation, it is very difficult to discern here. I have exponential growth and the other one is supposed to be exponential decay, but I cannot make it out from here. So, in that case, you can just go to our control panel, data sets, remove the 195 data set, 200 and 205 is what we have, click OK, click the graph. Now, you can get a constant line corresponding to proportionality constant as 0.2 and exponential decay when it corresponds to 0.205, which is exponential decay. So, it is able to produce the results that we can expect from a first order system. So, model is verified. This can be used for further discussions and analysis. Just to quickly go over it, so that we have a record how to go about it. So, you revise it, it is quite easy for you.


Hi, everyone. Thanks for coming along to this fourth webinar introducing the institutional underpinnings draft RDM framework. I probably do a terrible job of introducing myself on each of these, so I might actually do that this time. I'm Nicola, I'm the program manager for institutional underpinnings. I've got a number of members of the team here with me as well who'll be helping out. I'd like to start by acknowledging and celebrating the first Australians on whose traditional lands we meet. I think there's a number of us here from all across Australia and New Zealand, but for me in Perth, that's the Wajatmonga people, and I'd like to pay my respect to elders past, present and emerging. So, today I'll be giving you a bit of an introduction to the institutional underpinnings program and the framework that we're developing, and mostly what we're here for is questions and comments. We will be using a Q&A tool to manage questions. I'll give you a link to that in a second. We'll decide whether or not we really need to use it, depending on how many people we end up in here, and a couple of these we've used the tool, some of them we've just used soon. So, we'll see how we go, but yeah, I'll take questions at the end. And yeah, we're recording at the moment. As I said, the presentation part will be shared just for people who weren't able to make it today, but anything that you say or ask will be kept private, so feel free to say or ask anything that you like. So, yeah, we'll be using Mentimeter just to keep track of questions and comments today. It's just useful because it's got an upvote function, so we can get to the most requested questions first. So, you can just scan this or enter that URL, but I'll put this up again at the end when we actually get to question time. Okay, so ARDC is where we are running this program from. Our purpose is to provide Australian researchers with competitive advantage through data, and I would do that by accelerating research and innovation by driving excellence in the creation, analysis, and retention of high quality data assets. We do this under the auspices of the increase. So, this program is part of the National Data Assets Initiative, Institutional Underpinnings is part of the National Data Assets Initiative, and these are a set of programs which are designed to develop a portfolio of national scale data assets to do that work of supporting leading edge research. So, these large data assets is infrastructure, and the majority of the programs within this initiative are actually focused on the building of those data assets. Institutional underpinnings is slightly different in that it looks at the underpinnings that are required to actually put together and maintain those data assets with the acknowledgement that data is created in institutions, it lives and is cared for at institutions, and its institutions coming together that produce those assets. So, in order to create and maintain these important national scale data assets, we need to look to the research data management capability of institutions. So, our aim in this program is to advance university research data management together by collectively developing a university research data management framework, and the idea is that this framework should be able to inform universities design of policy procedures, infrastructure, and services with the aim of improving coordination of research data management both within and between institutions. And it's really important for us in this program that we recognise that universities aren't all in the same place in terms of research data management and they don't all have the same scale and needs. So, we're very careful here to make sure that we're not being prescriptive and saying everyone has to use the same set of systems. What we're instead looking at is trying to work out how we can have a more common approach to research data management. Something to point out is that we talk about the word framework, we're building a framework. This is a conceptual framework, so the idea is that it's a way for us to structure our approaches to institutional research data management development. And it's looking at places where we can collectively build an advance as a sector. We're not talking about a regulatory framework that sort of prescribes or constrains how you provide research data management. So, it's just an important focus to have when you think about the kind of framework that we're building. So, models of research data management do already exist, I'm sure we're all aware of a few of them. So, what are we doing here that's different? Well, we're really focusing on what we need right now rather than trying to create a sort of a perfect comprehensive model of institutional research data management. So, our focus is on addressing current needs and working out where we can make the most of working together rather than just laying out everything that is needed, although I think we've done a pretty good job of laying out what's required. So, we're aware that complete and perfect are impossible goals. So, the focus for the group has been what is valuable for universities right now. So, in this program, phase one has been the building of the framework. We're now in phase two where we're testing and collecting feedback on that framework and we'll soon be heading into phase three where we refine the framework based on that feedback and then present what we've developed back to the sector. So, I'll just take you through what was done in phase one to get us towards the draft framework that we'll be talking about today. So, we focused on Australian universities as major producers of research data. All 43 of Australia's universities were directly invited to contribute and 30 of those universities participated in an initial workshop where we talked about what we wanted the framework to be able to do for us and how we wanted to go about building it and then 25 of those units applied to participate and they were all successful. So, we've got a group of 25 universities who have been working together in this program and something that was really important for us was that participation is at an institutional level. So, we know that universities are very complex organisations but it was really important that although we had one representative, that representative had contacts throughout the various parts of the university that work in research data management and that there were internal structures, committees or meetings or whatever it was that allowed feedback from all of those relevant parts to feed into the program. We also have an editorial committee whose work is to take all of the content that's developed by those 25 universities and to actually get it down into some documentation that reflects all of the discussion that's been had and all of the outputs that have been created. So, we started building the framework by just collecting all of the ideas and challenges and issues that were sort of felt pressing right now to the universities who were participating and we then took those, all of those ideas and challenges and issues and we drew them together into themes which are areas of research data management that are really important for a university and what we did. So, those themes are the elements of research data management that are presented in the framework and for each of those elements we worked together to collectively identify why they were important for university RDM and then we ended up with 16 of those which is fantastic because it gives a really broad view of what's needed but in order to make the most of the resources that we had we had to focus in on a subset of those. So, we, as a group, worked out which were the areas where we could make the most impact by developing those out right now. So, these were the 16 framework elements that were identified and it was these eight that were selected as being ones where there was a current focus, where people were available to provide work into working groups and to develop these out and where we thought we could make the most difference. So, each of these elements was selected for development in a working group. We ended up with 95 experts being nominated from across the participating universities who formed these eight working groups and we, for each of these, the working group over a number of months identified commonalities and differences in need and approach across universities of different scale and research intensity and then they compiled best practice recommendations and advice and they also importantly looked at where currently either best practice wasn't identified where we still needed something to be done in the sector that no individual uni could provide and tried to pull together calls to action. So, what needs to happen next in each of these areas? So, I'll just take you through each of the eight elements quickly just to give you a very light definition of what each of them covers. We obviously don't have time now for me to take you through the content of the entire framework. I also don't expect you to have read it right now for this meeting but I'll give you a bit of background that might also help you to select which of the elements might be most relevant for you to take a look at. So, active research data management is about the universities providing the infrastructure for the management of research data during the life of a research project. So, everything from where the project begins and data is acquired or collected through to the end of a project where that data no longer needs to be frequently accessed anymore. Culture change looks at shifting institutional research data management practices towards where we want them to go, something more effective and this section covers both changes in the attitudes and behaviour of individuals but also how you shape and guide change in institutional processes. Policy, that's what it says on the turn, it's about the policy that lays out the principles by which a university manages research data and this section looks at suggested content for university policies around research data as well as approaches to implementation of those policies. Research data management planning looks at the ways that universities can support researchers in their forward planning of the research data management for their projects. So, this both includes the formal documentation of planning in documents like DMPs but it also looks at how else universities are active in the support of forward planning processes and how that can support good research data management to the university. Retention and disposal is quite an important focus for a number of our universities. It's looking at how institutions make decisions about what to do with research data after a project is over and it's a particularly interesting problem as we look at having to increase amounts of data and what we do with that storage burden long term. Open research and data publication acknowledges that there's a strong movement in research towards open research which includes making data fair and or open and the fact that there's an increasing call from publishers to have research data be in some way accessible whether it be openly or in a mediated way and looks at how institutions can enable and support that. Sensitive data is a broad topic. This group ended up looking at how the levels of protection that are needed are assessed. So, looking at the classification schemes that allow us to assess the level of sensitivity of data that's held at a university. And finally, support trading and guidance looked at how institutions can provide researchers with the knowledge that they need for good research data management be that through training programs, written guidance that's provided support services. So, quite a broad range of topics that were covered. So, we closed up that phase towards the end of last year and we're now in phase two where we're testing all of the recommendations and advice that were produced in those working group outputs and collecting feedback from the sector. So, one of the ways that we're testing this framework is that participating universities in the program are taking an aspect of that framework, an aspect of the recommendations and advice, and they are applying it to a project that they are running locally so that they can make sure that that advice really works for their particular circumstance. So, helping to make sure that we really are providing guidance that works for many different universities. Alongside that, we're also doing this broader consultation with people who maybe weren't necessarily involved in the writing of this framework documentation, which is what we're doing today. So, after this second phase closes towards the end of August, we'll then go into a three month process where we refine the framework based on everything that we collect and then we will present it back to the sector. So, today and this month is really about collecting your feedback on the framework documents. So, as I said, I don't expect you, it's quite a lengthy set of documents. I don't expect you to have read them all today, but you can access a draft, these draft framework documents on the ARDC website. I think that a link may have just gone into the chat. Yep, awesome. And below the links to those documents, you can find a template in an online form where you can submit your feedback. We really strongly encourage collective feedback. So, if a number of people from a group or an organisation have all been reviewing these documents, it would be great to get your views condensed into one feedback template. It's both helpful for us and also means that we can see where particular feedback represents the views of a group. But individual feedback is also very welcome. So, what we're interested in both in that sort of longer feedback template process but also today is your sense of whether the guidance that we're providing out of this program reflects your understanding of university's needs, whether you work in a university or with universities, whether it meets your own data management needs. And that's particularly interesting for us for those of you who may be either working in universities who weren't involved in the development of this or are working in non-university organisations that also have data management needs. This guidance was created by universities but we're curious to know how broadly applicable it is. And we're also interested for those of you who work with universities, what is it that you need that would make it easier to work with universities? Where can we create a more cohesive approach between universities that would make things easier for those who work with universities around research data? So, those are kind of our focuses both today and as you write your feedback. We're also quite curious about how the material could be most usefully presented for you and what steps would be valuable to you following the release of the final framework?


Great weather, great seasons, you have snow, ants on, nice place to be. The scenery surrounding area. Basically there's just tons to do in Burlington. You can go down to the lake, swim, go up to the mountains, hike. We're up here in the mountains. You get to go out still all the time, even if you want. I really like Lake Champlain. The other day, me and my friend Andrea went to a little spot and painted next to the beach. I hiked Mount Mansfield this weekend. Very active, lots of things to do outside, everybody's moving all the time. Everyone is extremely friendly, loves to be outside. I had to get used to people saying hi to me on the street, you know? I love to have the people over here. The people are so friendly. If you ask them away and they don't know it, they would say, oh sorry, I did not know it. They would never say no, or just don't know. Good change of views, everything's laid back. Everyone's very calm here. Church Street. There is no better street than Church Street. That street I've ever been to. My goal is to try every single restaurant in Burlington by the time I graduate. There's always something to do. It's a very happy city. It's actually surprisingly good arts and music scene in Burlington. I moved out here from San Francisco. Kind of continuing that rather easily here. Life is great. Money Waters is a beautiful place, and it's a great place to study. There's the shopping bag downtown where you can get the best $5 cheeseburger you probably have ever had. Church Street. Church Street. Church Street has like the best food ever. It has everything. I love Burlington because of the people. Really open-minded, and I feel like, for real, you can be anything and do anything here, and you'll still be accepted before you are. I also really love people here because there's such a great diversity of them that it's all kinds of people. I love Burlington because I can walk around with a boat net and not get looks. And you still have a huge diversity, not only in campus, but out there as well. Because I guess to be kind of into that, if you're kind of going against the grain, I guess this place might be full of people.


Nikan Nambiar of Tourist Wealth Capital. This is a multi-family office. Hi Nikhil. Hi. I love you to have you. Thank you. You know your company is based out of Dubai and I'm told that you're also headquartered in Singapore looking at investments in India. You're doing some things with family offices in India. Can you tell us more about that, about how exciting the space is and what sort of investments are flowing in the family office space? That's right. Thanks Ashika once again. Like Ashika mentioned, I represent Tourist Wealth Advises. We are a multi-family office at Quarvin Singapore. We also have an office in Dubai for the last few years now and we've seen a lot of activity picking up in the multi-family office space. We've seen a lot of business coming down our way. Dubai being Dubai is a launch prep for Africa as well as in the Middle East itself. So we have a lot of interest. It is a fairly nascent market, so to say, but the space that we operate in is a very exciting space because we operate on a kind of advisory fee only model. We don't charge commissions. We don't charge brokerages. Whatever comes to us as commissions or brokerages goes back into the clients account. So we work on an absolutely unbiased free-from-conflict-of-interest model where clients know that the advice they're getting is purely based on what they need and what they want, not based on the commissions that we're making. So you are managing family offices from India and otherwise also from which other countries? We manage families and family wealth of families based in the Middle East in Africa and in Europe. The Singapore office manages money for the families in Southeast Asia. We currently have representations on our clients from over 24 countries. What is it that you find most exciting about the Indian family office ecosystem? From what I know, everybody's very tight-lipped and I can understand why you would be tight-lipped too, but what sort of scope do you see in the family wealth, you know, peppering that we're going to now see? Tight-lipped is a very interesting way to put it. It is indeed tight-lipped. At times it's difficult even for us in the industry to get information out, but yeah I think the key lies in the fact that it is a family office. It's not a publicly owned office which is why people choose to keep it very very closed and very personal and very private. There are no reports, figures, nothing which get published. We have no idea what goes on until you know who's going what in which family office. Very recently we heard about a very large Indian family office based in Dubai, losing a lot of money, losing about 300-400 crores in the stock markets. Nobody would hear about it unless you're in the industry. We've seen over a dozen Indian families set up family offices in Dubai, over 400-500 million dollars of assets. It's significant wealth that we're talking about, but you won't hear about it. I see, that's interesting. Yeah and these families are very very cutting-edge savvy I would say when it comes to investments. They know exactly what they're doing. They're hiring the right kind of people. They're seeking out experts like us, other people in the market to help them manage and structure their investments. They're in real estate, they're in art, they're in equities, they're in private equity, they're in venture, they're in everything. I see, this is an interesting thing to note. So Indian families are showing a lot of interest in Dubai, is what you're saying? Very a lot of interest.


Beautiful Beautiful means very good or pleasing, having beauty. Bedroom A bedroom is a room used for sleeping.  House A house is a building in which a family lives. Kitchen A kitchen is a room in which food is cooked. Living room A living room is a room in a house for general family use. Relax Relax means to spend time resting or doing something enjoyable. Sleep Sleep means to rest your mind and body by closing your eyes. Upstairs Upstairs means on or to a higher floor of a building. Wash Wash means to clean something with water and usually soap. Where are you? Now you try it. We usually use a preposition like in with a location. Some locations like upstairs have no preposition. I am upstairs. I am in the kitchen. Now you try it.


Hello and welcome wherever you're watching around Australia, Pete Cock, Robbie Slater and Mark Bosnich with you on a Monday evening live on Fox Sports for more A-League action. Willick takes it quickly. That's forward. Trucking that run back to Piscopo, can hit him, plays in Davila and chips the keeper, Wellington 1-0. Just like that, their little Mexican marvel. Scores another for the Knicks. Russell. Beanie in a bit of space all of a sudden. So three on two, he's got Duke for company, Bernier Beanie. He goes one on one with McGean into the box. He's got two Knicks players. He does really well with the cross over to Wilburang for the Western Sydney Wanderers. That's got his first ever A-League goal and it's a big one for the home side. And what a finish at the back post. He just goes sitting from the left-hand side, completely unmarked. Sale just waits for everything to get in order in front of him and Payne launches it forward to Ball who wins a really good header and actually you'll get a second bite at it here. He's got Natta for attention, back to Davila and Lewis who can find McGarry out on the left. Quick ball in, Piscopo looking for the little nutmeg on Bacchus. McGarry, Davila, Piscopo blocked by Gordon out to Devlin. Will he have a go from out there? He will!  What a hit from Cameron Knicks back in front with one of the goals of the season. And what a game. Incredible, terrific play. Sets it up, he's got the time to just settle and you won't see a more pure strike than that. He just gives it violence on the half volley. Trace his corner. Again an equaliser for the Wanderers this time off the head.  Wanderers right back in it. Rufa had some space, went over the head of Duke who was a little disappointed to see Daniel Wilmering so far back. Big opportunity here for Wellington Ball, you can feed it in. Ever so slightly and that was the difference between picking the ball up here and picking it out of the back of the net for Daniel Margoosh perhaps still alive. Great ball in from Lewis, penalty 3-2 Wellington, what a game we have here at Bankwest and the celebrations begin at the south end. Fair play Olly de Villa, there was no histrionics when Hermet went straight over to the ball and picked it up as soon as the penalty was given. Olly was only too happy to hand it over to a confident fresh player off the bench. The Wanderers again with it all to do. Duke off, look response, this is extraordinary. Mitchell, Duke playing the whistle if you don't mind. He didn't seem to be in a lot of contact and he gets his body position in the right, he dispatched it into the back of the net. Quite bring it under control straight away, stretches for it, he hasn't hurt himself right there, back it goes for Kamao who burst free. He's got Muller on his right, Nikolai Muller, the cross but this extraordinary game keeps on going, Wanderers in front. Well he kept his composure and again it's a very very good finish. Last minute, again fix it on, Satirio, Hermet, goodness to use those famous words in the alley. Brief what a game we've had here at Bankwest tonight, goal for the club. Clinton justifiably they'd feel are going to get something out of this classic from the alley. Stretch you can't quite believe that he's been called offside. Shoulder which has got him about half a foot if a little less offside. Evans doesn't have the whistle in his mouth just yet, here is the possible chance, McGowan. What a big header that was at the back, Devlin goes charging in, Backers is there first and we're done. What an amazing game of football at Bankwest Stadium. When you rock up to a game of football you hope you're going to get something that you remember for a very long time. Full time at Bankwest, West at Sydney Wanderers, four, Wellington Phoenix, three.


Realistic Gaming here and it is Tuesday the second happiest day besides Friday of the week because it's not Monday So today we are here on cruise ship and it's a story game We haven't played a Roblox story game in a long time. Oh, like there's a pack of Skittles there I haven't had Skittles in such a quiet while now that I realize that we got the whole squad here And as you can see I dressed up on my beach gear because we are going on the cruise So we got to play the part so it can feel legit and awesome And I can't wait what we're gonna get ourselves into because these games always have a bad twist to them Okay players one. Oh, there's only one player here. Okay, the last one. I'm trying to get a nephew one from our boys right here Okay, you know what? Oh, this one zero players. All right, let's go everybody. And I did buy the water gun All right, so here we are on the cruise as you can see this cruise looks very marvelous Probably cost a lot of Roblox to get on here Jack. Hey there. Welcome to carnival cruise Hey, there's a real actual cruise called carnival cruise Okay, my name is Jack and I will be your host on this floating party. I don't know how you feel about a floating party, man There's a lot of rooms in this cruise.  All right, so at least kicking us out of the fun. We have to go find our rooms now Don't forget to check out every corner. You can be surprised by the amount of secrets there is in this place Also, make sure to pick a room on the second floor. You will need it later. All right, so let's go look for our rooms explore the cruise You did say to look at every quarter. Oh look. There's this is a lunch rub pizza. Oh my god They got those eyeball sandwiches here.   No get away from me guys. This is my money. Oh like the captain's cabin looks like this is a power room We can't go in here. Okay, better not mess with it right now Okay, so the captain's room is down there as you can see Let's see what this room is. Oh wait. We can click on the picture. Oh, we can what is that? It tilts it. I don't know what the purpose of that is but maybe a drop something Well, like right guys. Oh, I'm gonna use the toilet. Wait. Why does everything move when you click it? Oh Close the door man. Come on Like a card Like a credit card or a key card of some sort Maybe we will need that later. All right. Let's go over here Okay So I believe every all like more money. No stop walking backwards collecting the money Or I think everybody could see the same money on the floor all right, um Okay, nice looking rooms like pretty basic, but that'll do man Let's not be ungrateful for what we got. Okay crew story It's like the time has run out. Oh, look at the captain.  Hello Jack. Did you have fun exploring? Yes? I did because I found money on the ground man Okay, that is great now. It's time to play a game Pay attention to the rules. All right. Here we go. Oh look a rubber ducky I'm going to ask for random item that is hidden somewhere around the cruise What so like we're playing hide-and-seek world like a treasure hunt fight or something once you find it bring it to me Okay, that is quite interesting. Okay, whoever finds it first gets 50 cruise bucks. What I think I'm fine I found plenty on the ground man. Are you ready? I have a cookie already, so I'm just gonna let the other people You know what? I'm gonna beat them to it. Bring me a Fork, okay, go. I'm gonna get the fork first. Haha Look at me up first. No, how do you catch it up, bro? Okay? Where's the fork? We're in the world of the force. Oh, they're cheating bro. They already knew where the fork was cheaters You guys are cheaters Look at these guys every I know they played this before actually playing with me. You guys cheated man Axel salad found the first GG's axle. All right Man, I know that boy played this game before rejoining me. He's using them hacks Okay, he found the first time to pick another item.  Oh gosh. Oh Look at this. What a coincidence. They have us fighting for toilet paper, huh? Oh my god.  Look at the throat.  That doesn't do anything No, I'm going first. Oh my god No, okay, you know what I'll just collect this robux on the ground those cruise bugs Oh Okay, I'm gonna try to go into the captain's room Let's see if it opens up Maybe I won't Okay, it does it. Hey What are you doing down here, huh? He also has it. Oh what dude, there's a doll jump here. Oh brother doll jump the cruise That's pretty cool All right realistic fat number one found the first aid my boy Okay, you guys are great at finding yeah, because they I mean I really want those cruise bugs man now for our last item What can it be? Tell us now Bring me a golden ticket. What let real get it. Where's the golden ticket brand hint third floor? Okay, so is this considered the third floor? Maybe not My god, so we keep going down all the way at the bottom dude. He is fast. How does he always get first?  Oh look the golden ticket This is like the Willy Wonka golden ticket to go to the chocolate factory pretty neat My god, I'm not gonna win. I wonder whose hat this is It might be the captain's Or unless you wait, does he have his own hat on I'm not sure Okay, look at him. He just took him the golden ticket He found the first dude this guy is on the road. That's the second item. Oh, yeah, he's the mom of the group I forgot. He's the mom of the each quarter Man, all right, you guys are good at this. Yes. They are indeed All right now what let's change the game All right, I wouldn't know what kind of game he's gonna have us played He had his running around like maniacs on the cruise now went to what is next?  All right FBI. What's this dude? He is FBI. Oh my god blue team on my left side I'm gonna go red because that's my favorite color So I'm gonna side with my favorite color obviously and so is the whole you squad The objective is to eliminate everyone on the other side of the pool Huh? Oh Brian is against me. All right, Brian. I know how you feel man. All right. Show you true colors Okay, make the teams now. Oh, no, it switched me Man, I guess we have to stay on the blue team. At least I'm with our mom, right mom.  I mean the yeet squad is on the other side, too. Oh my god.  Thank you Lacey She got the head. Oh dude.  Oh my god. Okay, that's one way. Oh, I got him I am the dodgeball pro. Wait, is he on our team? Wait, what? Why is red team on the side? Wait, okay. Did we win already? I think we did actually go summer real. I Think we did it went already. I guess so we have to wait till the countdown Plates all the way to zero Okay, nice. Oh, it's night time now Gary I just know for the fact that it's night time. That was really fun. It's night time already. Yeah, I can clearly tell man Okay, after all that running you must be starving. Oh, yes, I am Okay, you can buy any fruit from the buffet any time you want my god 25 Bucks for a slice of pizza better be an entire pizza man Make sure to take a seat for one. All right, man. Stop yapping and let me bro. I am hungry Okay. Oh, wow. We only get one slice of pizza for 25 cruise Bucks. Yeah, I kind of want dude. They got an entire pizza. Oh, there was free pizza and I just spent my pizza My god, let me sit down with my boy right here Yummy. All right. Enjoy. Thank you captain Jack Hey You're stabbing all over the pizza, man. Oh, so make sure you have a bed by now. It's getting late All right, so let's go claim a bed for ourselves Because we obviously need a place to rest unless we just sleep on the ground or we sleep upstairs in the lawn chair I wouldn't mind that but let's just claim a bed. Did you also get a free ticket for this cruise? My god, okay, so something we just noticed that we got a free ticket for this cruise and it's it's like very weird I know why did we get a free cruise ticket? Nothing is nothing this good is actually ever free. Wait. She's right What is that? Oh my god, what what is going on? What? I'm hearing this creepy music. Hey guys, dude What is that? Oh my god? What what is going on guys look through the window? No, I'm gonna close these curtains Is that a girl ship? Oh my god, it must be the flying Dutchman. He's tired of being down on the road.  Oh, no, it's getting way darker.  We need to go get the power room and find help. All right That is a great idea. Oh my god Oh Yo, what was that? Oh gosh, you're right. It's gone for now. Okay. Oh, you guys are awake Yeah, did you not see what just happened man?  I am so sorry What is the guy talking about yo? Jack we are scared. Oh my god. Yes, we are definitely Spoopified right now. Okay. There was a scary ship in the window and we think something got inside Oh my god, that better not be the case man because if it is I'm jumping overboard. Are you guys sure it was just not just the nightmare They never believe us man. I swear Okay, anyways, I trust you guys we need to restore the power so we can search for whatever got in the cruise I was trying to open the electric room door, but I lost the key card Oh, I saw that thing in the in the restroom in the toilet. That is a very odd place Jack Would you help me find the key card? I think last time I saw was in the bathroom. You are correct, mister Oh, dude, what does it say? Hold on? Let me close this give it back Give what back? Oh, I'm sorry close door on you. Sorry. There you go. All right. Let's close this Okay, so they roll give it back What do they mean by that guys? Oh, thank you for finding the key card Can you make me one more favor? Okay, what does he want from us man? We're just we're just trying to enjoy a vacation and he has is doing all these things I can't go in there. Would you help me finding the power generator in there? Great. Thank you I mean, I guess we have no other choice. It's going here, right?  This is cool Oh, oh, it's like an army or something a little off to the course. It's kind of remind me of jailbreak Yo, there's money on the ground. Let me get some money yo Cuz money makes the world go round and round. Okay. Let's go here. Oh no dead end Okay, now let's get back. Okay. This thing shouldn't kill us anymore because they got the power back on Okay, Jack. We saw something in the wall. Hmm. Let's go check it out And this jack guy doesn't seem like he's faced by any of this. I know he has to be part of this man He has to be Okay, now we're in the rest dude. It's gone. I don't think there's anything in here, bro I should have took a screenshot so we could show this guy, but I was it was just in here What so the writing just vanished out of nowhere. Oh, I think you guys should have some rest It's been a rough night. Yeah, thanks to you having this running around looking for stuff And then having each other beat us with those balls, okay I will inform the captain about what happened. Remember we have dinner with the captain tomorrow get back to bed I don't know if I want to meet this captain man. He might be the evil man behind all this But whatever to say tomorrow shall be a brand-new day and Brings his new mysteries. So let's go take a nap. Wow We sleep the night away. Okay, so let's time to sleep guys. Let's just pretend nothing happened like Jack's saying I mean According to him nothing happened, right? I don't know man seems fishy to me Not just because we're in the ocean, but because It's just happening out of nowhere All right, so it's daytime remember. Okay. Yeah. Yeah. Yeah. Why is that still there? That was like from the land There you go. Good morning everyone today is the day of the dinner with the captain. Oh, man They better have some good food. Okay, we got a look fancier. So we got to go with the tux Man, I look good in this tux.  I might just need to get me one of these in real life So I could look fresh like my avatar. All right. Oh, what's up? Oh, I see you in there Well, if you got a fancy outfit, you got a funky outfit. Nice outfit though, okay We look so good now. Let's go to the arcade and look for Jack man I think I like best out of everybody. Just look at me. Oh The arcade Oh, I thought you can like actually play it for you can this place to look so fun Yeah, this oh Roboq not really have it. Why would I pay for that golden ticket? Let me take this kids not letting me Hey, that's like Pac-Man music, right? Oh Bats, you don't have enough red. What a red ticket, bro Only have two red tickets. Oh, she has it. No The mom of the group has the best so she can beat us and we don't listen on the on the cruise. All right, make sense. I Like the music they're played. Okay. He's probably just a bit late. Let's play video games while we wait Yeah, we're playing games inside of a game. Hey, what just happened to the machine? What happened to the machines? Oh, what's up with the music? Oh My god, it's getting dark. No This is dark cloud. Oh my god. Why dude, there's like a ghost pirate right there Guys look over here. Ah, look at the door. Yes. I clearly saw him already. I said give it back Oh my god. What is he want from us? Just give it back. Whatever you do. They're trying to glitch out.   Okay?  Oh, he just got shrieked by the water. Good. How embarrassing. Oh my god They're trying to go after one person specifically I think from what it looks like because they were all looking up on that guy up there This is your last chance Throw the golden necklace in the water around some sink in this ship Oh my god, so we took a golden necklace that we don't even know about like bro We're just out here trying to vibe on this cruise ship and you're out here trying to sink it Come on brother. Like we have nothing to do with this. What is happening? I don't know man. It's just pure chaos. Okay. I'm so scared He said something about a golden necklace. I mean I see a golden necklace right here like look at this There's one right here. There's one right there. Oh that one has a dollar sign. Okay I almost forgot it's almost time for dinner with the captain. We need to tell him what is happening Yeah, he's probably not gonna believe it's like everybody else in this storyline Just makes us think we're crazy. They knocked them over with the door All right doors are open. Let's go.  So I can eat this by myself I guess not okay. You're welcome to my table. I just wanted to sit alone so I can eat more to myself All right, don't eat the chicken bone All right. Oh, look the why does he look mad was wrong this boy and look at his look at his chain It has a skull. That's already a red flag man. Welcome everyone. You are all looking great. I know he's talking to me Exactly cuz just look at me once again Okay, my name is Edward Smith. I am the captain of this ship. I heard you already met Jack Unfortunately, he won't be able to join us right now. He had a rough night and is feeling sick.  He's looking for some kind of golden necklace. That's the necklace He's looking for that's I mean because he's dead and that is a skull it only connects, right?  It's that necklace. What is that in the captain's leg? I Just said it like three minutes ago. Why is my screen blurry? What's going on? I'm sorry. I can't let you take it. He poisoned us. It was a chicken leg. I didn't even eat it. I Knew the chicken was like too good to be true man.  Oh, no, so Jack is a good guy. Okay. I'm sorry for blaming you, man I'm sorry. I'm just a little skeptical about all this. Hey, you're finally awake Jack What are you doing here? Poor Jack. I locked them in here, too No, the night the power went out. I found the golden necklace in the captain's cabin Oh, he's gonna spill the tea sisters get close everybody. He's telling the story when the captain saw me fighting He went crazy. The last thing I remember is waking up in here. Oh my god So he knocked out Jack silly too and he locked them up in the cage with us That is so sad like he was your second man. We saw a monster some kind of ghost pirate. He's looking for the golden necklace Yeah, man. He attacked us clearly the captain probably poisoned the chicken and brought us here. I Just yeah, man. He clearly did. There's no other way. I mean we knocked out. Okay, that is terrible We need to get out of here before the ghost pirate strikes again He might sink the ship if we don't give the golden necklace back So let's just jump overboard and let the captain deal with this man But how will we get out of here? We could just jump out the shape in my opinion Actually, I might have an idea. Let's see what Jack has up his sleeve He most not he knows more than us obviously because he works here I found around a random stick in my cell, but I can't reach the key a random stick Where's the key at? Oh the keys right there. Luckily the keys closer to yourself Take the stick and grab the key with it. All right, man Right, let's see. I got the stick Yes, we got it. It's nice Okay, great. You got the key Dude, that is the one long stick. Oh my god. Okay, open the door Okay, open it Open up, okay. There you go. Thank you. Now. Let's find the blue key. Oh the blue keys over here It's locked. Oh, all right. He made he went through the vets. Oh sneaky sneaky. Okay Nice. So now we got Jack free. This is good. Everything is turning good out as of now Okay, let's get out of here. That is the plan Jack To get out of here once in front. Oh my god. No, there's Gulf Pirates Okay, I think we're gonna have to fight these guys one last time before we get out of here You took the wrong decision. Why won't he let us leave? We did not take it It was a captain leaving the captain and mind-less with him Oh Dude just give us a break. Come on. You are selfish Everyone in this ship deserves the same fate. Yeah, I mean that was kind of selfish But I mean it was selfish of him and to begin with to take the necklace and bring us on here You will not me Poseidon. No, we will not you crazy man. We are taking you. Oh, you and your menu down Oh, yeah, we gotta be careful.  Oh, all right, so he has a life bar We all work together guys. We can take him down easy peasy lemon squeezy All right, there you go. Yes. That's what I was talking about. Oh, what I thought we did Treated him now. He's up there floating the Poseidon can't take your soul He will take the captain's well by all means My body captain. It was nice meeting you. Thank you for the horrible dinner and the horrible cruise And we will never meet again quietly after this cruise. There's no time to lose run to the lifeboat and take a seat Yeah, we out of here Let's go Why did you have toilet paper? Oh? Man, I mean kind of makes sense as you have toilet paper after experiencing all this Let's get out of here Okay, nice. We're finally getting out of this place and off we go.  Oh, is that the bad ending or good? I don't know I mean, this seems like a good ending for us because we lived and bad for the captain But whatever I mean if we would have stood there the Green beard would have seen us like as an RV of the captain, you know He would have seen us as like us siding with the captain and trying to fight him for the captain trying to steal the Trying to see the golden necklace from his treasure. So now I mean we did a good thing not siding with him All right, you guys. Well, this was cruising roblox. It was awesome from not exactly not playing a Story game in a while good thing. They made this. It was pretty awesome. Good ending. I think that was a good ending I mean as I said, it was good for us after all we managed to escape, right you guys Well, thank you guys for watching. Thank you guys for the major support If you guys enjoyed the video, you should have slapped the like button Even near to the channel make sure to subscribe and turn that notification bell out and I will see you guys in the next one


Halleluja Yes, because of time we have limited time and I am here for you today God send me to you so I want to encourage you to be strong in the Lord Amen You are wired in a unique way by the creator of everything If you are wired in a unique way by the creator of everything you are no longer yourself in ideas and in behavior but totally absorbed into the ideas and ways of your creator There is nobody and there will be nobody quite like you Tell you never there is nobody and there will be nobody quite like me Yes Nobody is quite like me I am unique, I am special Are you? If you are unique, let me say you are Thank you, thank you, thank you Let me take you to the book of Luke Chapter 11 from verse 14 If our master Jesus Christ was called names then who are we? The soldier can never be greater than the head Jesus was driving out a demon that was mute When the demon left the man who had been mute spoke and the crowd said and the crowd was amazed but some of them said By Bezibub the prince of demons he is driving out demons Others tested him by asking for a sign from heaven Jesus knew their thoughts and said to them Any kingdom divided against itself will be ruined and a house divided against itself will fall If Satan is divided against himself how can his kingdom stand? I say this because you claim that I drive out demons by Bezibub Now if I drive out demons by Bezibub by whom do your followers drive them out so then there will be your judges but if I drive out demons by the finger of God then the kingdom of God has come to you consider this for a moment almost everyone in your life is more preoccupied more engaged, more committed to themselves than you therefore you know more about yourself than anyone who will ever meet you never forget this It is not what men say about you that really matter in this life It is what you believe about yourself Jesus Christ was slandered He was falsely accused They said he was possessed with demons Countless accusations were heard like stones against Jesus every day of his life but it never affected him because he knew who he was Do you know who you are? Jesus Christ believed in himself that was why no one could change his opinion of himself what he was about, his product When you are doing what you really love to do best nothing can stop you no matter the opposition criticism persecution intimidation blackmail name calling campaign of calamity slanderous remark you will continue to go on and on and on when you know you are who God says you are you will stay focused on your go alone and nothing can stop you Jesus Christ never striked to look good he simply was good he did not labor to appear truthful he was truthful he did not struggle to have good reputation he had character people of God in order not to end up like the masses out there who are merely wandering and unsure of their goals and dreams your purpose must be clear if your purpose is clear your life will have meaning Jesus Christ was called names they say he was possessed with demons that could not stop him he simply continued to cast out demons the mind will always resent what he cannot master wars are thoughts because of ignorance and fear what people don't understand they call names what they understand they destroy in every community there is always a standard of doing things in every profession there is a standard contrary to God's standard when you are really doing what you love to do best nothing can stop you no matter the name calling you will continue to go on people of God Jesus Christ knew he will be betrayed but he continued to do what his father sent him to do because he loved people and because he obeyed his father in heaven he taught us by example to serve people not because we want to be appreciated but because we love and obey God when you are doing good and you are not appreciated don't stop don't be discouraged continue every successful person you see today wants to be admired want to be loved and admired but your enemies and critics will never leave your reputation unsteamed and untanished you must rise above that fact when you are doing good and people do not appreciate it don't be discouraged don't show love or kindness because you want praises from people because you want to be appreciated show love and kindness because you obey God and because you love people no matter how close you are to Jesus you can still be tempted as the child of God stay true to your goal in life be strong in challenges hard times will not impair you but improve you remember our saviour was called names but that could not stop him he continued to do what his father sent him to do because he loved people and because he obeyed his father in heaven in the face of trials stay true to Jesus in the face of persecution stay true to Jesus in the face of name calling stay true to Jesus nobody is quite like you you are created in a unique way by the creator of everything let people hate you but not you as children of God love becomes our protection against the hatred of the adversary humility becomes our protection against the pride of the adversary a little example can have a big influence when you are called names when you are persecuted for Christ's sake don't be discouraged the Lord is with you he will never leave you nor forsake you amen be encouraged to stay true to Jesus in the face of trials trials are the soul in which a man a woman of faith flourishes may God bless his word in your hearts in Jesus' name thank you amen so because of time I am ready to do the work of my father in heaven are you ready thank you


Go ahead and start. This is Alex from Indeed. So he's done some cool stuff in AI and natural processing back in the days of an engineer at Google. But today he's going to be talking about SQL, no SQL, but then a third option that is the middle perfect MPH. So he's going to tell you all about it because I know nothing. So I'll let him take it away. Go ahead. And there goes Paul and Andrew, but I'll just say it anyway. I'm Alex Jim from the software engineer at Indeed. And I'm talking about MPH, a key value store based on minimal perfect hashing. And I'll explain a little bit what that means later, but the important thing to remember is that it's a read-only key value store. So I'm going to go through and talk about the... Can everyone hear me? Sorry. It's soft. It's soft. Yeah. I'm going to talk about the use cases for this and then talk about the implementation and conclude with some benchmarks. So I help people get jobs. You didn't see the shirt. Indeed is the number one job site worldwide with 200 million unique ones through visitors in more than 60 countries in 29 languages. It's not the sales pitch. You can get that at our booth downstairs. This is just to emphasize that we're a global company. We want to serve our users worldwide very fast response times, which means web servers near them. And those web servers need to be talking to backend services in the same data center. And with that comes the problem of data distribution scale. We're pushing a lot of data back and forth between our data centers. We have a lot of different types of data we distribute. The search index itself, our job recommendations, ranking models, company reviews, all kinds of statistics, the deployables themselves and tons of logging. And all of these have different ways to be stored. The typical solution is going to be you do ask SQL or NoSQL. Both are fine with different pros and cons. SQL is a single point of failure. NoSQL can have some synchronization issues. We use both of these in fact, but I want to talk about an alternative today, which is to ship the data directly to consumers. Not a new idea, but often overlooked. So what we're doing is we're giving each client a local read-only copy of the data. This gives very low latency. You can end that or load it directly into memory. You're not accessing any external services. It's simple and robust. No rights, think functional programming. There's no moving parts, so nothing can break in production. And if you do need to update the data, you can just push a new copy, either ad hoc or with a regular schedule. So read-only key value store. The priorities for this is that the data must be small. I want to minimize network usage, disk usage and memory usage. You can't push around terabytes every minute. Read time must be fast. It doesn't help to save in the network if we're spending a lot of time in CPU. But the right time is less of a concern. It's good to write once, read many times scenario. So how do we build a key value store? Pretty much everything is going to boil down to some kind of tree or some kind of hash table. Trees tend to be more compact, but incur a log-in lookup. You might need to hit disk multiple times. Hash tables will take a little more space, but are faster. Your file system will need to be a tree. Something like gdbm is a hash table. SQL databases will use a mix of both. So our solution today is based on hash tables. So what is a hash table? It's a table based on the hash function, which will take the key and produce a deterministic, but ideally random value. Multiple keys might hash to the same value, so you need some kind of collision resolution. And you might have empty buckets. So a perfect hash table is a hash table where there are no collisions. Now, by definition, this can only be done when you know all the keys in advance. So this is only possible for a read-only table. Kind of easy way to get a perfect hash function would be to use a cryptographic hash. So you can make an md5 of some, but then you can't realistically build a table with an index for every md5 of some value. So ideally you want a perfect hash table that maps to a smaller range of numbers. And the holy grail is the minimal perfect hash table. Where the n keys are mapped exactly to the numbers zero to m minus one, no collisions. So perfect storage, you're guaranteed one single seek. Generating a table, this hash functions is kind of complicated, but there's been good research in this in recent years involving solving graph problems. And there are libraries to do this for you in linear time. Now that'll give you the hash function, but you want to store this on disk somehow. And so if the data itself, if all the key values are fixed with, you can just access them directly. You can use the hash function and scale that by the size of the key values and directly look up that offset. But more often they're going to be variable with. So you need a separate table of offsets to index into that. You'll notice here that the metadata, this is the hash function itself. The techniques we use to generate these perfect hash functions are not constant sized hash functions, but in fact scale with a number of keys, but only at about two bits per key. So compared to the rest of our data, this is pretty nice. One problem with this is you can't hear. Yes. You speak up a bit. I'm already here. You can't hear. Okay. Sorry. Now one problem with this is. I'm not supposed to move your mic right now. Hold it. Okay. Is this better? So with this, if your key values are very small, then the offset table here can be a significant size of the index. So we also try another approach here, which is instead of an offset table, we have a bit protector. What we're doing here is restoring a one in the start bit corresponding to each byte in the data file of where each entry starts. And then so if you wanna, if you get a hash.uk and you wanna find out where the kth item starts and you can find, you can look up where the kth bit is in this bit vector. And there exists data structures and algorithms to compute this in constant time. So what, and what we do is then we'll consider the size with an offset table on the side of this bit index and use the smaller one. This has an upper bound of one eighth the size of the data itself. Benefits of this approach, as mentioned, so there's no collision handling. So we get optimal storage to begin with and you're guaranteed a single seek. You compute the hash, look up the offset and read directly from that one location. You also don't need to verify the key, right? So we're talking about a fixed set of keys that we knew in advance. And if you're looking at the key that you know was in that set, you can just compute the hash, get the offset and read the value. So we might not even need to store the key and the data. We can also probabilistically, so if you're not storing the keys and you look up a key that wasn't in the original set, it's just gonna get a hash, it's gonna resolve to some value, it's a false positive. But you could use something like a bloom filter to filter in advance. And in fact, we can do better than a bloom filter. We can store a signature of the original key with the data. And so say we store a 10-bit signature, you then look that up, you compute the same signature for the key you're retrieving. And if they match, you assume it was the original key. That would be for 10 bits, a one in 1024 probability of false positive, which is a much better rate for the same number of bits you would get in a bloom filter. You can also instantly use the same technique to build a better bloom filter for any statics of keys. And the implicit compression, so we might have a very large key space, long strings, and these are now all compressed down to the numbers zero to n minus one. If we want to reference those keys from some other table or data structure, we can just store that hash down. And so the results, the results from the first table we switched to this in production. There's not a lot of solutions that are aiming at this exact immutable approach, but so this is kind of a grab bag, but we're looking at SQLite. And I did say earlier, we're looking at non-SQL solutions, but SQLite is a library that maintains a single file on disk and it's perfectly suitable for pushing to your consumers. We are looking at our in-house LSM trees, they're log structure and merge trees, and level DB, another open source LSM tree solution. The hash tables I described here, disco DB, which is another middle proof hash based solution that I found after implementing this. And tiny DB, which is a non-perfect hash table. And so the data, you can just consider these clusters, this is what we're working with. We've got hash values, eight byte hashes, mapped to a cluster of items. These are all 80 bit integers, they're actually stored as base 32 strings, 16 bytes each. The first table is the map from the hash to the cluster of items, and there's this auxiliary table, which is a map back from the items to the cluster. And so for the first table, the hash to items, we can see that the trees, as expected, are more compact, but the middle proof hash table is in line with the general storing this as text. An important aspect of both of the indeed solutions is we allow a plug-in, a pluggable serializers. So you don't have to store it as raw text. We can, for instance, store the eight byte hashes as eight byte binary longs. We do that automatically for SQLite as well. And for the items, instead of the base 32 bit integers, we can store this as 80 bit binary values. And if you can apply both of those, the NBH tables are the smallest, even smaller than our own trees, using the same serialization. For the second table, this is where it gets really dramatic because we're gonna, even without the additional optimizations, NBH is smallest. But if you can omit the keys, right? So in the second table, this is the reverse lookup from the items back to their hashes. If we, we don't have to store the items in this table. So we can just get that refeed the hash and then look back up in the previous table, whether that item was really one of those hash clusters. So we can omit the key and cut our size in half. And we can go further. So this is pointing to the, the hashes which had a minimal perfect hash function. So that compresses down to four bytes for the zero minus N1 storage. So this is suddenly one-tenth the size of anything else, really dramatic reduction. And then the next thing we're concerned with is the read time. So here, all the hash-based solutions are fastest. NBH was fastest of all. This is the times we're reading from the two different tables. For write performance, this is less of a concern for us. But again, both of the indeed solutions were pretty competitive. In summary, smaller and faster, if you can use an immutable solution to try it out. We've open sourced this. It's on GitHub. There's a link to a blog that has some more details about the implementation. The library is in Java, but also has a command line API. You can just say you can just try it out without that encoding. Any questions? Yes. So you mentioned CDV, and as far as I'm aware, CDV has implementation where you can't have a database as large as in four gigabytes. Yes, so. Because you could use a page if it's an implementation. Is there just another one? No, there's no limitation. I've tested this with more than four billion keys and up to around 10 gig files, you could probably do larger. If you want to do much larger, you could probably want to charge this solution. And actually, we had to leave off tiny CDV from the right benchmarks. It was writing really fast, but it was not generating the valid table. The limit is four gigs, but above three gigs, we're getting data loss. Yes. So how long does it take for you to generate a perfect hash table for like a billion keys? For a billion? It sounds like it would be four billion, I think four billion, like the intermax plus one was about an hour. Okay, then I'll choose that. The minimum hash function generation is very fast. All the bottleneck is in the serialization of disk. What's the feature of the data, like what kind of data? You said immutable data, what kind of email addresses? Yeah, this was actually user clusters in this case. We use it for job recommendations, we use it for anything. It's really good for machine learning type models. You can store the feature values without even storing the feature keys and just leave them out probabilistically. Is it possible to do better? Just wondering, because you mentioned that you're already using zeroes and ones that you're using. I'm assuming rank and select using that? Yeah, rank and select. You mentioned cost and time. So is it possible to do better by using techniques like that on the basis? Are there any, you know, I don't know any low hanging fruit to improve on this, but I'm sure you can find something. Yes. For the benchmark, how many records are you testing that with? This one, I think this was 50 million. So the size, this is megabytes, so these are three gig tables. You see pretty much the same thing. I tried one through 10 gigs, it's pretty consistent. Okay, thanks. Yeah, thank you Alex for one of my demos.


Hello, and welcome back to yet another GCSE revision lesson now carrying on through the a key way worlds and lives anthology Okay, working our way through the entire poetry collection And now want to move on to look at important contextual information that you should be aware of if you're studying this anthology And more specifically the poem name journeys by Roman Monday. Okay, so what I'm going to do as you can see behind me is go Over this very brief mind map of put together relating to both the author and the influences that will have influenced the poem itself Okay, and this is really important because you need to have contextual understanding of what influenced a lot of the writing of Roman Monday and more specifically names journey. Okay now let's begin by discussing the poet herself Okay, so remember that Roman Monday is originally from India She was born in India and she migrated so she left her home country, India and moved to Manchester in the 1970s when she was just five years old. Okay, so she left India when she was quite young she was only five years old and After she settled in Manchester, she stayed there for a while before her family decided to move on to Leicester and now as an adult She's a modern poet. She's still alive. She currently resides in Scotland, okay, so she is a poet that's very much used to migrating and moving between cultures Okay, now when she moved to the UK, this was a very important turning point for her right culturally But also there were specific very negative Instances especially when she was in education so early on as a foreign student that she faced a lot of obstacles Okay, so when she moved to the UK She was initially put in a class for what she in her own words says was a class for the educationally Subnormal, okay, in other words her teachers judged her as being subnormal and basically put her in a class where she needed some form of correction, okay, and she learned English in order to Addicted to to correct her educational sub normality, of course That's atrocious and teachers are not supposed to view and label the student in this way However, this is an early experience that really influenced her writing, okay And of course her writing is very much influenced by her experiences as an immigrant Not only by being labeled in this really terrible way But also more generally as an outsider seeing things from an outsider's perspective, okay So even names journey itself is influenced in this way Now the final thing to bear in mind about Roman Mundair is she not only is Disabled but she's queer, okay so she's part of the LGBT community and She identifies as a feminist a lot of this information and all of this comes into play in her Writing, okay, so this is really really super important to understand when it comes to studying the poem name journeys itself So now that you've got this background information Let's now do a deep dive and a line by line analysis of this entire poem by Roman Mundair