Hey everybody, this is Brett and this 2015 Chevy Tahoe LTZ is stock number 12310ZA. We're here at Summit Automotive in Fond du Lac, Wisconsin, you're new and used SUV headquarters. This 2015 Chevy Tahoe has the 5.3 liter V8 gas engine. This Tahoe has been fully-safetyed and inspected by our service shop per the state of Wisconsin inspection process that has a fresh oil and filter change. All the fluids have been checked and tapped off and this one is 100% ready to go. Really amazing condition on this one. We're going to go inside under the hood, start it up in this video. White Diamond Metallic is the color and we shoot all of our videos in 1080p 60 frames per second. So if you have HD capabilities on your computer, tablet, smartphone, or television, I highly recommend turning them on right now because it is your best way to check out the quality, condition, and options of the vehicle before seeing it in person. And if you like the video on how we do things here at Summit Automotive, in the upper right hand part of the screen is a subscribe button to our YouTube channel. Click that and then click the bell notifications and you'll get updates every time we do videos here at Summit Automotive. This one comes with the 20 inch chromed alloy rims and they are in really nice condition. It has a set of Nitto Terra Grappler G2 tires. These are 275, 55R20s and they have right around 50 to 60% of the tread left on them. Front fender is in excellent condition. I didn't see any dents or dings on there. It does come with the LED headlamps or LED running lights, projector lamp headlamps, front bumper parking sensors, and the factory fog lights. Front bumper is in excellent condition. I didn't see any major dents or scuffs or cracks on that. Comes with the chrome trimmed grille with the black bow tie. Looks really good and the hood is in excellent shape as well. I didn't see any major dents or dings on there. Passengers side front fender, no dents or dings on that. And the passengers side front rim, no scuffs or scrapes. Really nice condition. White diamond has a little bit of metal flake to it. I was like showing just how much like my sun simulator right here. It's got just a little bit of metal flake. Looks really good in the sunlight. And as you go down this side of the vehicle, take note of how clean the body is, how reflective and mirror like that paint is. We take these HD videos so if you are far away or even if you're close by and just cannot make the trip down but you're still interested in purchasing the vehicle, you can see the vehicle, hear the vehicle, and have confidence in the vehicle that you're looking at before you even get here. So when you do get here, there's absolutely no surprises and you can make a smart and informed buying decision from wherever you're at. And if this video helps you make that buying decision, let your salesman know that you saw the video, that it was helpful and that Barrette sent you. Back rim is in excellent shape and the back tires have just as much tread as the front tires. Frame and underbody, it's in pretty nice condition, just a little bit of surface rust there but nothing too bad. Does have the power running boards which are in excellent shape and the lower rockers are in nice shape as well. Coming around to the back of the vehicle, rear bumper is in great shape, it does have the full towing package which includes a receiver hitch hand, seven pin wiring, no major dents, things, cracks, or scuffs on that bumper and the rear gate is in excellent condition as well. This is a power lift gate, so that goes up like so. We do have the hitch cover for this vehicle, we can keep them inside the vehicle so they don't go walking off on the lot.  I'm always amazed at how fast they go down and up and they go down really nice and flat. And then off of there we have the storage area underneath and that's nice and clean as well. These cargo nuts always get in the way. Anyways, to get this down you press this button right here and that gate will power down and then it does have the flipper glass, there's your button for that and that goes up like so. You can see that the shocks are doing a nice job in that and that the rear defrost cables are connected. Shuts nice and solidly and as you go down the driver's side just as clean as that passenger's side, no dents or dings on the rear quarter and for full disclosure this back rim is in excellent shape as well. Now on the rest of the side of the Tahoe, very nice. I didn't see any dents or dings. The paints in really nice condition, it does have blind spot monitoring, heated mirrors, directional signals, chrome trim on the back and I believe they power fold in. You can see those running boards work nicely. Inside you get the really good looking, kind of a brownish almost brick colored leather interior. No rips or tears on those seats, get the weather tech floor mats, auto headlamps turned off, four-wheel drive, factory brake controller, power telescopic and tilt steering wheel, power pedals. You can turn those running boards off, lane departure warning, stability control and the parking sensors you can turn off as well. You get the memory driver's seat, the Bose sound, the nice leather trim on the doors as well as the wood grain trim and then these mirrors do power fold in. I always like showing both sides so that you know that both sides are working properly. We'll hop inside, check out the miles, the radio and everything that this interior has to offer. See this one has 77,190 miles, instrument cluster is very nice and clean, comes with the heated leather wrapped steering wheel, Bluetooth and information center controls on the right, cruise controls on the left, heated steering wheel button and forward collision warning controls, you can turn those off and on. Six-speed automatic transmission with the optional tap shift, this one comes with the Chevy MyLink system, AMFM and Sirius XM radio capabilities. Of course the factory navigation is on there as well and there is your Sirius XM and then you have all your different apps that you have right there. You also get a storage compartment behind there with a USB plug-in and then it does have a CD player right there. Dual climate controls, heated and cooled seat buttons and then your rear air controls are right there. Passenger side format and seat are in excellent condition as well. I don't think this vehicle's ever been smoked in. There is your DVD player or screen I should say, does have the power sunroof, home link buttons for your garage door security systems and lighting systems, sunroof controls and map lights up there as well. On-star and SOS buttons in the rear view mirror. We'll take a quick look at the back seats and then we will start it up and take a look under the hood. The back seats are just as clean as the front seats. You do get the quad seating back here. You get those weather tech floor mats throughout on this vehicle. Passenger side seat is in excellent condition as well. No rips or tears. The headliner is exceptionally clean and this one does have the Blu-ray, it's actually a Blu-ray player on that's the screen. You get the rear air controls, heated seat buttons, 110 volt, 150 watt plug-in, Augs jack, USB SD card and another 12 volt power point. Third row seats are in excellent condition as well. Turn the lights on back here, brighten that up a little bit. No rips or tears on those seats and they are in excellent condition. You got that weather tech floor mat keeping your carpeting looking like new and we got the seat too far up to get that closed so that'll have to wait. Bottoms of the doors all look really good. You have that weather tech floor mat keeping your carpeting looking like new back here. Those seats go down and up like so. Bottoms of the doors all look really good on this vehicle and we'll start it up and take a quick look under the hood. Starts right up. No check engine lights or anything like that. I would personally like to thank you for checking out the video today and hopefully from this HD video you will have been able to verify the quality and condition and the options of this vehicle inside and out. This one actually does have the HID headlamps so they are super bright and under the hood we have the 5.3 liter V8 gas engine and Jimbe's very clean runs very smooth. Once again this vehicle has been fully safety and inspected by our service shop. Has a fresh oil and filter change. All the fluids have been checked and topped off and this Tahoe is 100% ready to go. There is your emissions sticker and I would highly recommend this vehicle from a quality and condition standpoint. You don't see too many Tahoe's with this many miles that are in nice of this nice of condition inside and out. And to see more pictures of this Tahoe or one of our other 150 new and used cars, trucks, STVs, minivans, Wranglers, half tons, three quarter tons, one tons you name it we got to go to that website right there www.summitauto.com full pictures and descriptions of every single vehicle from two locations all at summitauto.com. If you'd like to check out more HD videos you can go to youtube.com slash summitauto. Remember to like, subscribe, and share on this video and all the videos that you see there. Click the bell notifications. We'll get updates every time we do videos here at Summit Auto. In fact in a second you will see a link to subscribe to our YouTube channel in the upper left. A link to more Tahoe videos like this one in the upper right. A link to this vehicle on our website in the lower left and a link to one of our latest YouTube videos in the lower right. Click those, check us out. We're super excited to help you with this ultra clean 2015 Chevy Tahoe LTZ and White Diamond Metallic. Thanks again for checking out the video and remember to like, subscribe, and share.


All right, thank you for attending from napkin to the cloud WebAssembly journey. First, I want to take a quick detour and explain a little bit of who I am and why I'm doing this. I created the open-source project WasmCloud and I'm also the author of Programming WebAssembly and Rust. So what I want to talk about today is a journey from design to production and I want to comment on how that's different when using WebAssembly as the underlying technology. To do that, first I want to start off with a real quick two minute tour of what WebAssembly is and what WasmCloud is. Then I'll talk about the application that we're going to build and that I have built for this demo, what the conceptual design is, and then we'll talk about the actual building. And in this case, I'll show some code and I'll compare and contrast the difference between what I designed and what we ended up building. And the point there is to see if there is a noticeable gap between the two. And then I'll take you through a demo of the application that we built and then finally there is a Q&A period at the end of the session. So quick tour of WebAssembly in the cloud. There's a couple of things that we typically want in our cloud-native workloads whether we've been using Docker or we've been just straight up running processes. There are a number of things that are fairly common needs that we have such as security, predictability, speed, and size. And by size I mean lack of size. We want small workloads. And coincidentally what we get from WebAssembly is a number of those things. So WebAssembly is secure. It's predictable. It's fast. WebAssembly modules are small and I'll show during the demo just how small that can be. It's portable. WebAssembly can free us from dependency hell. And it has what I like to refer to as beneficial limitations which means there are things that you can't do in WebAssembly that you can do freely in other environments. And I think that's actually a good thing. So if we get all these things from WebAssembly and there is this great overlap between what WebAssembly gives us and what we want in our cloud-native workloads then maybe we should explore using WebAssembly for cloud-native workloads. So WebAssembly is a stack-based virtual machine and without going into too much details it just refers to how that virtual machine processes its instructions. The important point though is that it is a virtual machine. It's a binary file format that has a text representation as well. WebAssembly is CPU agnostic. It's operating system agnostic. The modules are fast, small, efficient. And this is probably the key point here which is that they are entirely dependent on the host runtime. So in the case of a web browser the host runtime is some kind of JavaScript engine. So in Chrome it might be V8 and so on. But in the browser your host runtime is done through JavaScript. When you are outside the browser there are a number of different WebAssembly host runtimes available to us. We have WasmTime from the BiteTone Alliance. We have Wasm3 which is a popular C-based library that also has Rust bindings. And then we have higher level libraries that build on top of engines like that specifically WasmCloud. And this may be a controversial bullet point here but I firmly believe that WebAssembly is the future of distributed computing. So WasmCloud. WasmCloud is an open source project that I started probably a little over a year and a half ago based on these assumptions here which is if we want all of these things from our cloud native workloads and WebAssembly can give them to us then maybe there's an open source project that can create the tooling and host runtimes to bridge that gap and to give us what we need. So WasmCloud is an actor runtime and for those that are familiar with it that just means that it treats WebAssembly workloads as though they are actors as part of the actor pattern. WasmCloud makes it so that your portable business logic runs anywhere. So that could be at the edge in the cloud on IoT devices and also in the browser. WasmCloud is secure by default. And in the demo I'll show a little bit of how that security works. It eliminates boilerplate. We want to strip off all of the code that we write day in and day out in service of boilerplate that really has nothing to do with our business logic and our true functional requirements. WasmCloud supports a rapid feedback loop. We have a rebel in one of our command line tools. WasmCloud also provides a self-healing, self-forming mesh called the lattice that connects your host runtimes in clouds, IoT devices, edges, and more. It provides a single flat topology network that you can use to manage and observe your active workloads. So let's take a look at the combination of WebAssembly and WasmCloud. We saw earlier that WebAssembly provides security. Most of the security from WebAssembly at the core comes from just the fact that it contains no bytecode operations for interacting with the operating system. It can't do things that the host runtime doesn't allow it to do. It's portable. All the instructions in WebAssembly are CPU and iOS agnostic. WebAssembly is fast. It has a small size. And then WasmCloud builds on top of this by giving us access to loosely coupled capabilities and those capabilities might be web servers, database clients, message brokers, those types of things, blog stores, seamless distributed compute that runs anywhere is a feature that we add through WasmCloud. You can horizontally scale your actors and your capability providers. Again, I mentioned the actor model earlier. And we also do contract-driven design. So when you build a WasmCloud actor, you're writing against an abstract contract. So you might be writing against the key value contract or abstraction or the web server abstraction or some database client abstraction and not the actual database itself, which means all those things can change at runtime without you having to rebuild or redeploy your code. So let's take a look at the sample application that we built. And the idea here was to track and document the journey that starts with having an idea and finishes with that idea running in production. And to take note on how that changes or how that experience might change using small composable WebAssembly modules rather than our traditional throw a microservice into a Docker image approach. So the application that we're building is called WasmCloud Chat. And it's a multi-channel real-time messaging application. So instead of a simple hello world app, this chat application has a full backend. It records all of the messages that go through it. And it has multiple inbound and outbound channels including Message Broker and for our demo we're going to use Telnet. So this is essentially the napkin sketch or the blueprint for what we wanted to build for the sample application. So you can see that we have some users coming into the backend through the Telnet channel and some coming in through the broker channel. And in the back, in the true backend, we have functionality lumped together in categories called Presence, which is who's online and how long have they been online for messages, which is essentially the message processing and storage rooms. So that's the chat rooms. Think of those as channels and Slack and authentication and authorization. And again, this is a completely abstract concept here. This is to represent the idea that we had before we started to implement it. And probably I sort of knew what to expect before I went down this road of trying to build out this application, which was that in the past my plans immediately go bad as soon as I try to turn them into an implementation. And whether that's because of tooling or technology or something else, there is always a very large gap between my original idea and what I'm forced to build in the end. So let's take a look at the journey of how we generally go about converting our ideas into something that runs in production. So we start off with this amazing idea and we're inspired and that inspiration gives us just enough energy to get over and around that next curve. And so we have this idea that we then convert into a design. And the design is that abstract design that has very little to do with the actual implementation and it's just a rough sketch of what it is we're trying to build. We then do some early experimentation on this idea and then that early experimentation invariably results in us having to throw away everything that we've done, including some of our original ideas, and redo what we were building. And that's maybe because we learned some valuable lessons or we got some technical things to interact, but this iteration of experimentation and redesign is pretty common, including another round of refactoring and redesign. And during that process we might actually get something out into production and deployed but it's certainly in many cases nothing like what we wanted to build back when we had our amazing idea. And this of course leads to despair. And so what I'm hoping is that through the combination of WebAssembly and other cloud tooling we might be able to change this journey for the better. So we start off again with our amazing idea and then we get to an initial design, our napkin drawing which I drew on a slide earlier. And then again we go to early experimentation and I think this is where the paths diverge. The result of the early experimentation is going to be different this time. And that's where we're able to quickly and easily deploy and test our experiments in different environments including production and production simulated environments. And then the iterative process after these successfully deployed experiments is now instead of complete refactors and redesigns we're just able to tweak things, change the knobs on our scaling and deployments and the shape of our final production environment to deal with scale and expected volume and load. And we haven't had to throw away any of our initial conceptions this way. And this hopefully leads to joy. So back on the original journey path of microservices when we build our services with hard service boundaries. I think if you've built any microservices this pattern should look pretty familiar. Each one of these represents one of the potential units of deployment that we might want to build. And if we were building this as regular microservices, a small fraction of each one of these services on the screen is our business logic. But then we now have all of these embedded dependencies. Each one of these has an RPC client in it. Some of them have message broker clients. There's a telnet server in one of them. There are database clients in others. There's caches. All of these non-functional requirements. And as alluded to earlier, the problem with these is that these are now dependencies that we own and they are tightly coupled dependencies. And even if we've managed to compile these, we're still in a form of dependency hell because if we want to change how we get our telnet services from one approach to another, we have to refactor and rebuild and redeploy. If we want to change one of our database clients from Redis to Cassandra, we have to refactor and rebuild and redeploy. And that entire cycle happens a lot more often than we expect. And so these hard service boundaries are very much like containment walls and not in a good way. And so hopefully we can do better. And so with WebAssembly and using Wasm Cloud Actors and a bunch of beneficial open-source runtimes, we can get flexible service boundaries. So one deployment option here would be to have a single runtime process that has all of our actors in it. So we can choose on our laptop during early development to have a monolith that's the most convenient and easiest to work with for that time. And then as we experiment and we start meeting different shapes to handle different loads, we can split that. We could split it into two runtime hosts. And now we have our actors spread in different ways across the different hosts and we can pick and choose which ones go where. We're not locked into any binding between an actor and a host at compile time. And finally, we could also choose the Super Microservice where one of our hosts is hosting one actor. And we could choose that for a number of reasons. But the important point is that this choice is now, at least in the world of WebAssembly, a runtime, an operational choice, and not an architectural design choice that is baked into the overall implementation of the system. So let's take a look at how we built it. And I'm going to go through some rust fairly quickly, but the main thing that I want to show that I want you to keep in mind as I go through this code is not what the code looks like, but what's missing from the code. And so in this one, the first thing that an actor does is it registers the message handlers. Actors are reactive and they receive messages and they emit a reply to those messages. So in this case, one of these actors is simply registering a handler to process messages. And again, let's take a look at the code more with an eye towards what's missing. In this snippet we can see that it's publishing a message to the backend. And this code is actually from the Message Broker channel, which acts as a proxy between the outside Message Broker and the backend inside our chat system, which is far more complicated than a Hello World sample. But what's missing is actual communication with a tightly coupled broker. That publish function just takes the topic, a reply topic, and the payload to publish. The choice of which broker is doing the publishing, how that broker does the publishing, and what configuration we use in order to enable that broker to publish. That's all done at runtime. We could completely swap out RabbitMQ for Kafka for Nats without having to recompile this actor. Or even redeploy. We could swap those at runtime. Similar scenario here with data services. So in this one, we are adding a room to the chat back end. And in order to do that, we need to communicate with a database. And in this case, we're communicating with a key value store. But again, what's missing from here is that the key value store isn't actually defined here. We're referring to the key value abstraction, but we're not talking explicitly to Redis or to Cassandra or Memcasty or EtsyD. We're simply saying set this key to this value and add this value to a set with this key. And again, the binding of the provider is done at runtime. So now I'm going to take through a quick demo of the chat application that we built. And I'll show all of this code in action. And more importantly, I'll show the incredibly small size of our unit of distribution and our unit of compute and how flexible it is and the options that we have without needing to recompile anything. And again, before I get into the demo, I just want to have this slide up here real quick as a brief reminder of the architecture that we're building. Everything with a gear and in one case a padlock is an actor written in Wasm Cloud for this system. And I'll go through that in a second. So let's get started with the demo. I've got a couple of terminal windows open here because in general my demos are pretty devoid of graphics. I'm going to be going through some console stuff and we'll be using the Telnet channel on the chat example. So the first thing I want to go through is looking at some of the actors. You saw some of the source code for the actors in the slide deck that I went through earlier. And I just want to show you what that sort of looks like in the shell here. So what I want to look at is first how small these things are. So if I take a look at the signed version of our actor which is just a .wasm file, you'll see that it's actually only 702K. And when you think about the unit of deployment for most microservices even if we're using a language that's known for fairly small self-contained binaries, nothing produces binaries as small as 700K. And we're able to embed them with the cryptographic signature that tells the runtime what these modules are allowed to do. So if I inspect the claims on this module, you'll see that what I've got here is the name of the actor which is called Telnet Channel. And the actor has an account, a module, expires can be used, and so on. And if you're paying close attention and you've seen Jason Web Token before, you'll recognize that these are similar fields where we have an issuer, a subject, and then some other fields for how that token can be used. But more importantly, this Telnet Channel is capable of using the key value store, messaging broker, logging extras for random number generation, and the Telnet capability. And it's worth pointing out that nowhere in that list of capabilities is there a specific mention of vendor projects. So we don't mention Redis, we can use the key value store, and so on. So that's the Telnet Channel. And we also have in the actor list, we have authorization, a broker channel. So anything that is using, let's say Nats, can use Nats as a gateway into the chat system. We have the messages actor, a presence actor for determining who's online, rooms, and then again the Telnet Channel. So what I'd like to do next is start up the Wasm Cloud a host. And I want to start all of the important actors. I want to start all of the capability providers. And then I want to configure those. And we do that through manifest file. And first looking at this manifest file may seem a little bit overwhelming. I'm only using YAML here for an example. You can also use JSON. There's no requirement there. So the first thing we have on lines 5 through 7 is a list of actors that we want to start up in the Wasm Cloud host. And then on lines 9, 11, 13, 15, and 17, you'll see we're actually using this thing called an image ref for capability. And what that means is we're actually able to load a capability provider from an OCI registry. That means that we can store them the same way you store Docker images and we can retrieve them the same way you retrieve Docker images. And so we have a number of our first party capability providers sitting in our Wasm Cloud OCI registry in Azure. And then starting on line 18 we have links. And link definitions essentially consist of the actor, the provider that we're linking to, and then the name of the link, and then set of parameters. So we think environment variables. And so if you see here we've got the broker channel actor as being linked to the front-end version of the Wasm Cloud messaging. And so by using these two different link names we can actually have two different instances of the same capability provider but with different configuration parameters. And so in this case we have a NAT broker configured with a front-end connection string and one configured with a back-end connection string. So as we go through here you'll see we configure the telnet actor by configuring it with logging extras access to the telnet provider and access to a key value store. And you'll see that key value store is configured to communicate with Redis. So if I start Wasm Cloud with this manifest file you'll see a whole bunch of log spam that should look fairly familiar to anybody who has spent time looking at microservices, standard out logs in Kubernetes or any other cloud environment. Most of this is informational, not really worth going into too much detail but you can see how we have a discrete log of all of the actors, all of the providers that are running. If an actor stops and starts we'll see that here. If a capability provider stops and starts we'll see that there as well. So the first thing we now have is we know that we have a telnet provider running and because we configured it we know it's running on port 8500. And we got a fancy ASCII art welcome message. So we'll log in here, I shall. Those are the list of the commands that we support. And I mentioned earlier the back end system deals with things like storing and retrieving messages as a stream, creating and deleting rooms, joining rooms and all of that sort of thing. And then the channels are responsible for the actual communication. So right now I'm using the telnet channel and I typed a message there. And since there was no one listening, if there was no one listening to a real-time chat message in the forest, did it actually happen? And if we go into our Redis CLI we'll see that it indeed did still happen. So I'll take a look at the stream for the general room. Don't worry if the Redis syntax isn't familiar, it's not all that important right now. But you can see what happened here is I have a stream of messages that has been going through the different rooms in my chat back end. And this most recent one we have each message has a unique ID. The text was hello from KubeCon. We can see the origin user is a WazenCloud chat URL. There's a timestamp on it. And the origin channel is the telnet broker. Now assuming that we have other channels running, we might have as an origin channel you might see the NATS broker or you might see an IRC broker or even a Slack broker or a Slack channel depending on the integrations that we support. It's designed to support any number of integrations written using WazenCloud actors. But in any case, the moral of this story isn't that I've been able to build a chat application. The moral of this story is that we've been able to build the chat application by composing tiny units of compute and distribution that literally consume no more than one leg each that are cryptographically signed that have a verifiable secure provenance that can be deployed anywhere and can connect to capabilities that are also deployed anywhere. I can choose to run this entire thing as a monolith which is what I'm doing in this one terminal window. Or I could choose to run it as any number of processes as I want. I could run 30 copies of one actor and 12 copies of the capability provider that it speaks to. And the WazenCloud runtime takes care of distributing the function calls between those and makes it all seamless for you. So the end result of the experiment that we did to build this chat application was that thinking about the problem that we were trying to solve was almost directly in line with how we solved it when we went with building actors and connecting them to capabilities versus other avenues that might have been higher friction had we decided to go with the traditional microservices route. So if I could ask one thing it would just be to take a look at the tutorials and kick the tires and see if your next microservice project might be something that you might want to make as your first WebAssembly in the cloud project. Thanks.


and I've been in hemp, I want to say since 2015. In the last four growing seasons, I've been really looking at these different insects. Tree frog. What I find really interesting about it is that these plants are bringing forward a bunch of diversity. I mean diversity in terms of pest management. So you got ladybugs here, and they're always mating inside these male plants. I don't know why. Then something I've noticed was these Japanese people started showing up. I started like getting rid of them because they were just coming in droves. And then I wrote a grant to the stair project and I was able to secure a grant. So if anybody wants to know anything about how to secure a stair grant and need someone to like, you know, can you look over my applications before I turn in? See where should take my information, okay? And what's interesting about the stair grant is that I'm using a lot of different integrated pest management tools that are sustainable. So I'm not going to sprain my field. I'm using Japanese beetle tents to catch them. I'm using Dr. Bronner's unscented magic soap inside a five gallon bucket and knocking all the Japanese beetles off. It takes about 40 minutes to an hour to cover one acre. So by hand. And then some things I'm also doing is I'm adding this stuff called Beetle Be Gone and I found it in Denver, Colorado. But basically you either put it in the soil because the larvae, that's where they start and then you can also spray it on your plant. And what I'm finding really interesting about this research at the stair grant is I started at the college nomination but then I transferred it over to another program of reservation. What was interesting was that in the station we're not as prevalent as they were at the college. And so this next year I have to figure out okay I'm going to go back to the college and figure out why that is. And what's interesting too, this isn't a hemp plant at all. This is actually some native species plant that's sitting around. Well I noticed that a lot of the Japanese beetles are flocking to these native plants. So like mullin and these other various different plants that are kind of growing in my home's quarters. And it's just fascinating to figure that out. In terms of my research and what we're understanding is that Japanese beetles potentially might not be hazardous to hemp plants but they could also be attracting Japanese beetles.  You've got the Japanese beetles mating in the female plants and you've got the reproduction of all these different insects going on at the same time. So it's very fascinating and what I'm really trying to get home about is we're talking about the environment. All these plants and all these insects coming together there's really not a lot of research on it. So like young people in this room who want to understand how hemp is being grown and what you can do to deal with the IPM management of hemp there's a gold lining there. So the other things about hemp is this root system. Now, I got this root right here. This was over one growing season and what I did was I basically watered every other day from the time I planted up until the end of July. This is the root system. Yeah, just three months. Why? When you don't water them and you just let them grow freely, dry farm. I mean it doesn't look as sexy as they did before. I ran into a couple of doors in a way here and you broke on them. We got caught on a couple of tourists, you know. Cowboys. There's a lot of other things too about it being a carbon sequester. There's a lot of information out there. Some stuff in Europe says 2.48. There's, brings in about 22 tons of carbon. There's some stuff in America that's even less than that. So it's still to be determined how much you can recover from the atmosphere. But we know it can pull from the atmosphere. Economics. So I was granted a generous grant from the Native American Agriculture Fund. The study happened to develop a feasibility study for my tribe, as well as the other regional tribes in the area. But I'm not just going to stop there. Because look at, a feasibility study and a seven-year observational analysis of the American hemp industry. This feasibility study is going to be available in 2023. And I would recommend it to anybody who wants to copy of it. You let me know when I'll give it to you. Because I'm going to put a lot of information in it as soon as we put it all across the market. The college nomination is my partner. She's been my partner since 2015 when we first grew up and got rated. The USDA NEFA. We got one of those big USDA some hemp supply chain grants. And we're actually in the process of developing a hemp research center on the college nomination. And that's going to be open to all tribal students and non-native students who want to come and learn about hemp. So if you want to know more, you want to develop genetics because I have a lot of genetics. And I'll be teaching as well. Please enroll in the college nomination and devote your expertise, your brilliant mind to this because we're looking at seven years of catching up on hemp research, all right? And then we talk about CBD and the market and all that stuff and everyone's like, well, we can't really find a place to sell it. Oh! The USDA Biocertified Biobased Product System that's through the USDA allows you to have a federal procurement opportunity to where if you're able to develop a value-added product and sell it through this program, you have a niche. You got to compete with a lot of the people. I'm going to be honest. Well, when you look at it, you can make it perfectly. You can sell your CBD if you want. You could develop various different automotive products. You could create a biogram with a plastic product. You could create something that a national park needs. Maybe you could do something with oil mitigation. Maybe you need something to do with finding plastic trash bags that aren't plastic, but they're made out of hemp. You guys got to look at the USDA Biocertified Biobased Product Program and if you guys don't know how to start something like that, there is a woman in Glenwood Springs, Colorado. Brilliant! Her name's Barbara Filibon. You need to go see her. She has 30 years of experience. Glenwood Springs, Colorado, Barbara Filibon, environmental textiles. She's had a hemp-based company that has been successful for the last 20 years. She just got her certification for 20 years being a part of the Biocertified Program. So any tribes are looking for something that they can actually get a niche in the market, you've got to go through the Biocertified Program. That's my honest opinion after seven years of being in this industry. Climate change. I love climate change. So, you're asking yourself, what's this field here? It's all hemp. This was planted on July or June 7th, 2020 into the month. First week in July. July 23rd. You have plants growing up to 14 feet tall in a matter of less than 90 days. This is a fiber variety. This is Anka and Altena. And what's really interesting about it is we didn't use any water. We did not use any water. We let it just drop with rainfall. And I want to say it was about 10 inches of rain that year. It's really all about the soil, gang. I'm really going to be honest with you. It's all about the soil. If you guys know a guy by the name of Will Allen who ran growing power for years, he told me the same thing back in 2011. It's all about the soil, Mark. If you got good soil, you could grow anything. And he was right. I can't believe it. Because I didn't use any water.  It was a jungle. You couldn't even find me in there. I'm going to be honest with you. Amazing. But this is something I'm talking about in a sense of you don't need any water for it. We're coming into an area. I know some of you out there who are from the west. You guys are running out of water. What are you even doing? You don't have anything. No water to grow. Why? Because the hemp seed has everything you need for the human body. So we're going to need some amino acids and one tablespoon packed 10 grams of protein. So we're talking about trying to figure out what we need to do about food. Man, get some hemp seeds. Throw a little chocolate on me if you don't like the taste of it. Got it made. I said something I said earlier about a carbon sequestration. Totally. When you talk about this plant growing back year after year, it does. No, a winter axis over winter too. So the beauty of it is that this crop that I grew in 2021 I didn't touch the field at all. It came back in 2021. So it's really interesting in the sense of you have a crop that just keeps on giving. And not only that, these sprouts here are amazing. So when it comes to using as a garnishment on a piece of meat or with some mashed potatoes that can't tell you enough. It tastes like basil and hemp if they were to come together and make a bacon. That's what it tastes like. Not that I know what a bacon tastes like. So Tribal sovereignty. I really thought about this for a long time because I'm like, when am I going to talk about tribal sovereignty? That is related to that. Well, M.S.I.C.R.C.R.D. played a big role in making sure that tribal sovereignty was upheld and affirmed in the 2018 Farm Bill. We wanted to make sure everybody in Indian game country had the right to grow and we did not have to worry about DEA raids or FBI coming in without warrants because that's what they did to us in the year 2015. Now how do we look at the future? Because this is obviously on the past. I'm currently developing genetics. I took three land races from Ukraine, Romania, Southeast Asia and I developed this variety here. It's called Coyote Otter 15 and remember it's a minor John's meeting since my name is P.S.I.C.R.C.R.C.R.D. so a daughter and John was Coyote. So it's Coyote Otter 15 and why is it Tribal sovereignty? Because now I've got to pay anybody ain't no money to grow this crop. And that's what you guys all got to think about when you come down to this whole you need a certified seed to grow him. No, they just want to create a monopoly. That's what it comes down to. And when you come down to it, so it really comes to it, you all come see me or you go see when only Duke bought the collection that I pulled from. So when only Duke or myself have a seed that's available in the Indian country and you go and you come talk to us historical perspectives. Another one I was thinking about what I'm going to talk about. In 2018, right before we were victorious with the farm bill we were looking at trying to figure out what's the connection of tribes and man because in my culture there's this word called which means heaven. So when you go talk to the elders they're like no, no, no, that's god. Well, I'm a stubborn monotony man and I'm not going to stand for that even if it is my elder. So I'm going to go look and I'm going to dig and I'm going to dig and I'm going to dig and figure out if that's really true. And sure enough, I go to the Library of Congress, I find this book, Anthropological Papers of the American American Museum of Natural History, Textile Fibers Used in Eastern Aboriginal North America. Look at this, you got these, all these different definitions. Now, Indian hem, dog mane, you start looking through it, it's just a directory of all these artifacts that are all throughout America. I found this bag in a Milwaukee public museum. It's got a thunderbird on the back on the front. It's got a water panther on the back. Made out of hem. They have prisoner ties from the Sac and Fox, they're in the Milwaukee public museum. Why don't you New York City, you look at the Aboriginal foe string on the Franklin tribes at the American Museum of Natural History. It was lost. They didn't happen. But there's documentation that did happen. So, you know, my whole conspiracy thing was like oh, maybe they just came in and took it because they didn't want Mark to find out that, you know, hem has been growing in America for a long time. I'm not saying it originated here. Let's just put that out there because there's a lot of haters out there in the world that don't like me. And they'll say, oh Mark, you grew hem all this whole time. No, no, no, no, no, no. I'm just curious if it can't do the trade routes or if it can't move with the colonists. That's all I want to know. Because regardless, our people were using hem. This is something I really wanted to hit home with you guys. If you guys haven't had a chance and you got some money to spend, you need to go to the National Agricultural Library in Beltsville, Maryland. And you want to go to the Special Collections Division and you want to ask for the Leicester Dewey Files. Because you have diagrams of how to develop a Decodercator. So you're going to spend a million dollars on it. No, no, no, no, no.  And I want to make sure that you all go inspired today and you go tell them that we need help with developing our Decodercators. People are taking pictures. Great. If you need more information, let me know, okay? But you can see it. These are just little they're just spinning inside. And then when you bring that hemp through it breaks down. I brought a hemp break today because I wanted to show you guys just how really simple it is to do it. Because it's really more than anything. Once you see it then you can figure out, oh okay I can probably develop a machine that can just do this without anything. People can do it. Because guess what? It takes six hours to process 15 pounds of hemp with this thing. Trust me, I did it. Like I said, so much information and there's more information in Washington, D.C. If you go to the National Archives there's more information about this stuff. It's just out there. But for the record, they are classifying some of the stuff because I've had some documents classified on me. So go out there quick. That's my contact information. This is my phone number and my direct line if you guys need to get a hold of me. That's my presentation you guys. I just want to say for being here and being present it's really nice to see this room packed. And now what I'm going to do is I'm going to start processing this hemp. You guys want to come up, you guys want to process it with me. I'm going to take questions while I'm doing that. Because I know we got it in time in this room. But I'm not taking these hemp stocks home. So anybody that wants to help me process these hemp stocks, please do. Because that's where they already drive with the hemp stocks hitting me in the face from time to time again. I'm not going to do it again. So with that that's it. So when you guys want to process this stuff sometimes you can do it in a bundle. It's really easy. Let me start going. It's called X59. It was developed in Canada I want to say. And it doesn't really have a lot of great fiber within it. It's just kind of really broken up. Because what happens is when you start growing hemp for seed the plant starts hollowing out. And so you lose a lot of fiber. So if you really want to grow fiber we go back to my talk earlier about when the hemp fiber was ready by like July 23rd you're going to want to basically cut it all down and start readying it in the field one to two weeks after that. This one here is a Chinese variety. It's either Yuma or Jin Mao. It's a beast. We go back to climate change again. These plants can handle a tornado storm. What's going to happen is they're going to be standing and then once that tornado rips through they're going to lay down. But they're going to grow back up again but they're going to be curbed. But then their root system right here expands and strengthens so they can withstand those storms. Another reason why you should grow hemp because when we deal with these crazy storms they're going to be coming through because of climate change it's going to be a good problem. Resilient. Mark What did you say about X-59? X-59 usually grows about 4 to 5 feet tall and what happens is that it hollows out so once you start growing basically you don't want to put it right back here and start laying it down and cracking it. Hold it. X-59 grows about 4 to 5 feet tall it has a really nice cola so it gets to all that seed but what happens is that you don't want to use it for a fiber material once it goes to seed but it's a grain drop regardless but basically it hollows out so you don't get as much material once you've run it through the process. So the big thing about the Chinese varieties is if anybody grows Chinese varieties in America you do not want to test it if it's sexed. Once it goes sexed it drops. So if it comes up as a hot crop wait a couple of weeks until it sexes and starts forming the seed and then it will decrease. That's a big thing you need to understand. I brought this green stock for a reason. One, it's a part of a genuine X-59 but two, it's a hard green material. You don't want this for processing because what you're going to do is you're going to really mess up a machine if you're going to be pushing it through. So what you're going to want to do is you're going to want to lay it in the field and you're going to want it to rep and what it's called is Reading is a whole process of you're basically breaking it down you're letting the environment mother nature take care of it for you. What's going to happen is you're going to go back in the soil so put the soil in a better status of being good in terms of good quality soil when you leave the stuff out of the field and sometimes you've got to lift it and let it degrade because you're basically degrading five materials in the outside and you want to make sure that when you do that that it does not get too moldy because it's a pain to deal with when it gets moldy. And another thing, biochar anybody that's in this room that feels a fertilizer and does not have fertilizer available you grow hemp, you burn this stuff you put it in your field I guarantee you're not going to have any weeds because I grew some varieties this past here and I use biochar it's a T.E.K. thing you know, like let's get down to it biochar is just like this new thing no no no, we made that we created that stuff and what we want to do is that the biochar has so much great material and you mix it with that soil perfect for just fertilizer a natural fertilizer um I wouldn't, I would she mentioned pond ready I would not recommend pond ready because what are you going to do with the water after it's done and you're going to create another whole environmental hazard because all that stuff, all the enzymes everything is breaking down up in that water and you just dump it out somewhere else and we'll say we go into the soil you have to think about that when you're dealing with this stuff I also process a lot of hemp using a hammer mill and this is what I got from it material is not separated out at all it's broken down significantly so you have to figure out a way to separate this stuff you should not separate it and use that for textile or like a composite, a bio composite and check by mixing it together what's really interesting is that Europe have BMW, Volkswagen, Audi they create all their door panels on their hemp what they don't use on the assembly line they basically sell it wholesale and they get shipped to Canada and they make these amazing briefcases real sturdy that's another thing you can think about I really want you guys to understand that when you come to Canada there is no blueprint on it we make it up we use our creativity our thinking that's something John Trudell talked about before he died he said you want to be a thinker because the fingers create the solutions in the world be a thinker that is the biggest thing that I'm going to ask you guys to walk away with is to be a thinker be a thinker so that you can come up with a really good idea to create something with this hemp because try the people we've always been the most creative this is what we can do to the world to create a hemp economy because no one else is doing it because everybody wants some money we've got to do it from the heart and we have to do it for the planet and we have to do it for the next seven generations so that's that's all I got to say


Okay, so I'm going to talk to you about anonymisation theory and practice and this comes out of a whole set of different work both applied work in the field, working with various organisations on their own particular data situations and theoretical, statistical and technical work dating back to 1996, both here at Manchester and at other institutions. Okay, what am I going to talk about? So, we're going to divide the talking to two parts, I prefer the title, first we're going to talk about what anonymisation is and then we're going to talk about a practical approach to anonymisation using the anonymisation decision making framework. Now, the theory was developed in the most recent piece of work, starting in 2012, springing out of the UK anonymisation network, and what we did was we brought together a group of people, about 30 people, had a series of workshops over 18 months and these were people with various expertise that was relevant to the question of what is anonymisation. Turns out to be quite a difficult question to answer. And over this period of that 18 months, we built up an understanding from the different perspectives from different sectors, all sectors of the UK economy and different disciplines, both legal, computer information technology based disciplines and statistical mathematical data analytical disciplines. And with all of those inputs, we came to a consensus answer and that answer forms the guidance that's in the anonymisation decision making framework. I'm just going to talk now briefly about three different concepts, privacy confidentiality and anonymisation. Now these often get used interchangeably and used to in a confused way. So let's talk first about privacy. Privacy is primarily about people. It's not primarily about information. Privacy concerns a whole range of things outside the information sphere. Privacy is about personal control of your own spaces, access to your resources, access to your property, access to your person. It also does concern access to your information. So control and personal autonomy are very important in understanding what privacy is. It's a complex term. Confidentiality concerns information and data. And that's the key distinction between people and information. And confidentiality is about keeping data in a particular state regarding assurances that it will or won't be shared in a particular way. Anonymisation and is a technical process for keeping a confidentiality assurances. So we anonymise data in order to protect confidentiality. Now we may as a consequence of that have some benefits to privacy. But these are consequential. They are not part of the primary process, which is a protection of confidentiality. Now I want to talk about confidentiality risk, because again it's something that is often talked about in a confused way. The only mature model of risk considers two key components, which is the likelihood of an event happening and the impact of that event will have on individuals or society in general or whatever the environment is that's in consideration. So likelihood is often the sole focus. Impact with confidentiality risk is often ignored and this itself presents a problem. When considering likelihood, another form of confusion arises. The distinction between could and will. So often when asking questions about an anonymisation situation and confidentiality risk, organisations find themselves trying to tackle could questions. And the problem with could questions is that they are almost impossible to solve. So an example is when I leave the webinar studio and go back to my office and then I leave the building and go home, what is my risk of being hit by a meteor? Could that happen? Yes, it could happen.  However, is that likely to happen? Well, no, it's not likely to happen. And crucially, it's so unlikely to happen that I'm not even going to think about it on the way home and we make no decisions whatsoever on the basis of my likelihood of being hit by a meteor. So it's a risk that I'm going to ignore. And that's very important. We'll come back to that later, that concept of ignoring risk. So there is an important way of understanding likelihood. Now, impact, on the other hand, is something that tends to get ignored. And there is a tendency to treat confidentiality risks, the impact of them as apocalyptic. So we think about some breach of confidentiality as if it was a nuclear power station blowing up. That's clearly nonsense. So a mature understanding of risk will actually think through, OK, what are the impacts? What are the costs? And therefore, what risk in terms of likelihood does that warrant in terms of protection? And given the benefits that are coming from the sharing of the data for taking all those things into account in the rounded form. Part of this is thinking about how that risk is constructed. So a very helpful equation dating back now to 1991 is this one from Marsha Tao. So the probability of identification is the probability that an attempt has occurred to re-identify somebody multiplied by the probability of an identification has occurred given the attempt. Now, one of the things that happens is there's a lot of technical approaches which focus on the last term in that equation, the probability of an identification given an attempt. But we can have a significant impact on the overall probability by manipulating the probability of an attempt. And this is often not taken into consideration. And certainly within some privacy models such as differential privacy, that is just completely ignored. It's treated as if it's one. And there are some circumstances where that's clearly wrong. So one needs to think about things in the round. And the realization decision making framework is about tending to the whole of this, the whole of the equation and indeed the whole of the notions of likelihood and impact. So in our model we consider a much bigger system of consequences and precursors. So the precursors are the things that lead up to that make the events a possibility that enable event to happen or reduce the risk of an event happening. And then you have some concept of what the event is. We'll talk about later. It's important to be much more precise about that event than there's a vulnerability in the data, which data focused approaches tend to have. And then what are the consequences? What happens next? So there's been a breach. What happens next and thinking about how that plays out. But what is anonymization in this context? Anonymization is a process. The word's involved because it's important to notice that it's not a state of the data. We don't talk about anonymization in terms of an end state. We talk about processes by which personal data are rendered non personal. And this was a key understanding that was arose from the workshops that I talked about earlier on. The legal definition of personal data is tied into a technical process which we're calling anonymization. We convert personal data to non personal. It's very important. Now we need to be very careful when using success terms and the success term in this case is anonymized. Now why is that problem? Well, because it's denotes an end state. We're there. We've reached the goal. And actually the situation is a lot more fluid than that. We're living in an environment where data resources are changing constantly. The data environment, as we call it, and that's a term I'll bring out in more detail shortly, is growing. It's changing. New data forms are being created. New data is being created every second. So therefore considering that one might have reached an end state in an anonymization process is slightly ill-conceived. Now we do have to use the word anonymized in certain circumstances because partly because there's constraints of the English language make it quite difficult to talk about data without using the term from time to time. When we use it, we use it in a very specific way. We use it in the same sense as the word reinforced is used in reinforced concrete. So we don't expect a building that is made from reinforced concrete to withstand a meteor attack. We might expect, though, it would be reasonable to expect that a building made of anonymized concrete would stand the rigors of its expected use. So reinforced as in reinforced concrete. Now the problem with anonymized is that everybody grapples with that. And the meaning of the question is how do I decide when my data is anonymized? And this leads to some unfortunate adjectives, one of which is truly anonymized. And because they want to say something more than people normally say when they use the word anonymized. And of course this is meaningless because truly anonymized is just anonymized. And we get some sort of inflation of this going on without any meaning. And the other day I heard this term, unfortunately, really truly anonymized and that's clearly right. So avoid the use of the word anonymized if you can. And if you do be careful about how you're using it, use it to me. I've reinforced these data against privacy attacks. Okay, I want to distinguish between two terms, de-identification and anonymization. Now just to say, as an aside for this, that a complication here is that in different jurisdictions the terms are used differently. So in Australia, Canada, and the US, the term de-identification is used to mean what we mean by anonymization here. And de-identification here, we mean the removal or obscuring of direct identifiers. And it tackles one part of the normal definition of personal data as containing the Data Protection Act and indeed the Data Protection Regulation, directly from those data. It's where you can look at an item of data and go, oh, there is that person without any external information being required to do that. So anonymization on the other hand tackles indirectly from those data and other information. So when you bring other information to bear in order to make a re-identification, and obviously that's the much more complex problem to solve. So here's the tenets of our approach. Anonymization is not about the data. Now that may seem slightly surprising, but it's actually quite critical to understanding an appropriate and what we call functional way of delivering anonymization. Anonymization is instead about data situations and they arise from data interacting with data environments. Now that's a term I introduced earlier and I'm going to explain what I mean by that. So here's the formal definition that we produced in an article in 2014. It's a set of formal or informal structures, processes, mechanisms and agents that either and there are various things that can happen. They act on the data or they provide context for those data or they define, control and interact with those data in some way. Now this boils down to four things. Agents, which are usually people, but in the days of AI that could be computer systems. And security infrastructure, governance and critically other data. So those four elements make up any data environment. You can describe a data environment using those four elements. And the interaction between those four elements and the data that you're specifically concerned about is what determines the risk. The risk is not inherent in the data itself. Now anonymization as a term or its alternative de-identification in those other jurisdictions gets used in four different ways. The first of those ways is the concept of absolute anonymization. This is beloved by some branches of computer science. What it means is that there is zero possibility of re-identification under any circumstances. Now this is a straw person. Let's kick this into touch straight away. Essentially re-identification is about using information in the data. Information in the data is exactly what you need in order to carry out good and proper purposes analysis and so on using the data. So the exact thing that gives you the data value is exact thing which allows re-identification to happen. They go hand in hand. So you cannot have zero risk of re-identification under any circumstances unless you have even no data or completely trashed data. So absolute anonymization is not a practical possibility. Formal anonymization is the other side of the coin and it's de-identification as we defined it earlier. That's a simple dealing with the direct identifiers. This includes the concept of pseudonymization which is the replacement of the direct identifiers with a pseudonym. So typically here we're talking about names and addresses, ID numbers and so forth. Things that directly identify people. Now this is an important thing to do if you're engaged in the process of anonymization but it's very, very rarely is it sufficient. Now statistical anonymization is a more sophisticated set of ideas and it's primarily derived from the research field of statistical disclosure control. And it's about a set of technical process applied to data in order to reduce the risk of disclosure which I shall talk about a little bit more detail in a moment. Part of disclosure is identification. Now the problem with statistical anonymization and SDC is that it tends to be overly focused on the properties of the data themselves and does not tend to consider the environment in which those data consist. Functional anonymization on the other hand essentially states that you cannot determine whether the data are anonymized or not without just by looking the data alone. You need to consider the relationship of the data to their environment. Let's go back to that notion of disclosure. Unintended disclosure is disclosure of personal information unintended by the data owner consists of two possible processes. Identification and attribution. Now the key thing here is that attribution is the act of disclosure. So identification is the association of some data with a individual population unit which is normally a person for the purposes of this discussion. Attribution is finding something out about that person and that total system creates a disclosure. Now this is a scheme for just visualizing how identification happens. So on the bottom row, which is labeled target file on this diagram, we have a de-identify data set. It consists of a set of demographic and other variables, but there are no identifiers on the data. So we don't have name and address. At the top here we have a thing called the identification file. Imagining here a scenario where we have an intruder. Now there are other ways in which breaches can occur, but we'll stick with the idea that we have a malicious intruder. Now this malicious intruder has this identification file. Now this could be an actual database or it could be a set of information that's just in the intruder's head. Now the intruder knows the name and address of a particular person and they also know some other stuff about that person. And that other stuff overlaps with the information that's on the de-identified data set. In those purple boxes they form what are called key variables. So they're variables which are in common between the target and identification files and can be used to link the two together. Now there are all sorts of complex processes. Anybody who's ever been involved in data linkage will know that is a complex process. We're not going to go into the details of that here. But there are mathematical systems for working out the risk of an identification and a match actually being a true link. And the link here is the link between the name and address which we determined has been sufficient to identify the person. And the target or sensitive variables over to the right here in blue which the intruder, the attacker did not know about before. So that's the disclosure. So identification, the identification process here. Now there are various things which affect and we're going to talk about this very briefly but again it's a very complex and detailed field. The power of individual variables. So whether they differentiate the population. So you notice there was data birth on the previous slide. That has a greater power than age because age is captured as a set of bins and a much larger group of population in each of those bins than particular dates of birth. The skewer variables also important so that creates small categories, for example, ethnic group, we have minority ethnic groups, there are much smaller subpopulation and therefore greater risk of re-identification. And so there are a number of things to take into account. The quality of the data is also important. So lower quality data is actually at lower risk of re-identification. Because the data by definition might be wrong and therefore the intruder will make errors in carrying out matches. And then of course the availability of that data in the environment is actually quite important. So if you're collecting information about something where generally that information is widely known, so demographics are the obvious example, then that's an available key variable. Now we're going to go on to a problem now. This is to demonstrate the notion of attribution and this is a table of counts. Hopefully this is something that is familiar to most of the audience. And in this table of counts, we have professors and pop stars and we have various income bands. So the question which we're going to have a poll about from the moment is what is the problem with this table from a disclosure risk point of view? Where's the risk in this table? So we're now going to present the poll. Okay, so you will see that there are four possible answers. Don't answer it yet because we'll show you the table again. You can have the small count in the bottom right hand corner, which is the five. The fact that income is a sensitive variable or you could have the zero in the top left hand corner or you can answer don't know. So I'm just going to put the slide back up again. So we're going to close the polls now to have a look for about 10 seconds and decide what you think your answer is and then we'll put the poll back up. Okay, so if you can now answer the poll. Oh, oh, we can't cancel the poll and start it. Okay, my apologies. Apparently we there's a technology problem which didn't technology didn't work how we were expecting it to. So only a few people got to answer the poll. Anyway, and now most of you have answered, most of you who answered the quick answers were all towards the low end, the low counts of five in the bottom right hand corner, and that is very common. This is where people tend to focus. Now I'm going to run a little scenario here and explain why that's not the answer. Okay, so we're just putting the table up again. Now, imagine I'm at a cocktail party of professors and pop stars it's a real rave. And I go around that party and imagine that I also have this information about all of the people the 305 people at the cocktail party and I have this information you won't worry about how I've got this information but now it's this percent I have the table. Now I go around that cocktail party and I hear somebody say at the lecture I gave last week. Now, what have I mean to learn about them from that partial information. I've immediately learned that they're not highly paid. So I've learned something about their income, even though they've not chosen to disclose that information to me. And similarly, if I hear somebody boasting about the 10 million pound income they had last year, then I've identified them as a pop star. So the problem in this table is created by the zero. That's the immediate thing you you you're drawn to because there's nobody there so how can anybody be at risk but the zero creates the problem for everybody else in the table. Now, as it happens, we'll see in a moment there is a problem with the five. It's less direct. But we're going to we're going to imagine a gatecrusher is going to arrive at the party. Here he is. And I have to say he's always gatecrushing my parties. And so that now leads us to this situation here. Now we're not going to make a mistake of putting the poll up again because I'm going to give you another poll now. Look, and the question now is, have we now solved our problem? Have we solved the problem with the table because we now don't have any zeros in it. Okay. Okay. And the vast majority of you have identified that we haven't solved the problem. And so probably probably you're thinking, oh, this is a trick question or maybe or maybe you've identified what I've identified. The thing is, I know who this person is in the top left hand corner. It's Brian Cox. So I can just say, oh, there's Brian over there. So I can just do the next thing, which is take Brian out of the table and hit and hit and we get back to the original table. Okay. So we now have a zero again and I can still make those inferences. So this is called a subtraction attack. And this is the reason why small scale counts are a problem because the smaller the number in the same or the more likely it is, I know all of the individuals that are in that particular cell. And therefore I'm going to able to knock holes in the table and then start making inferences about people I have partial information about already. So that's why there is a lot of discussion about small cell counts, not because of the identification problem, because there isn't any particular difference between identifying somebody in this cell, the low pop star cell, then in the low professor cell. Because in order to say, ah, that person is in that cell, I have to already know all of the information in the table to place them in that cell. So it doesn't actually do anything to the person you're identifying. So I already knew that they were a lowly paid pop star. And I haven't learned any new information from that identification. So the process of identification doesn't cause a problem for the person identified. It might well cause a problem for other people. Okay, so that's the complication. Okay, so I'm now going to move on having to give you two simple examples of the sorts of things that are thought about in the disclosure risk context to talk about the anonymization decision making framework. And it's a much broader set of considerations than disclosure control. So what is the ADMF, anonymization decision making framework. It's a system for developing an organization policy within an organization. It's a practical tool for understanding particular data situations. And critically, it's not a checklist.  You have an anonymized data set. It's a live active system. There are feedback loops, things that you do at stage five or go and affect what happens at stage one. What it is critically is a system for thinking about data situations to enable you to effectively anonymize. Okay, so what's your real responsibility? And this is another critical output from the UK anonymization network workshops. And this understanding, this definition has been agreed between ourselves and the Information Commissioners Office. What do you want to do? You've got to understand how a privacy breach might occur. How a breach of privacy might occur. And that usually is a pre, there's a precursor to that, which is a breach of confidentiality. Understand the possible consequences of that breach. Reduce the risk of a breach occurring to a negligible level. Now, what do we mean by negligible? Now, you remembered earlier and I talked about meteals. Now, the idea of that, that analogy is that I ignore that risk. I ignore the risk that I'm going to be hit by a meteor. So what does that mean? That means that's a negligible risk for me. So here's what we mean by negligible. This is a risk that a reasonable person will ignore. I'm hoping you'll accept that I'm a reasonable person here. So a risk that a reasonable person would ignore. And it's a framing concept for thinking about risk. Now, the really good news here is that it is relatively easy to get your risk down from moderate to high to negligible compared to the issue of getting it from negligible to zero. So negligible is a much less demanding standard than zero. Now, there's a 10 step process for delivering this. I'm not going to go through this slide because each of these points I'm going to cover on subsequent slides, but it's just to bring that all together in one set of slides, only a single slide. It's a 10 step process. First of those steps is describe your data situation. Is it static or dynamic? Now, by static, we mean that the data was sitting in a particular place. And we really want to just do a risk assessment of that situation. By dynamic, we mean that the data is moving. Maybe it's been shared between organizations. Maybe it's been released to a certain set of users. Maybe it's been published on the internet. That's a dynamic data situation. The second point here is then you have to define your environments. What are the environments? So what's the existing environment? What environment are you moving it into? And then, how does your data relate to that environment? That's the data situation. Now, here's an example of a dynamic data situation. So this is actually quite common. So organization X is collecting data and passing that data to an environment two, which in this case is a local authority, but it could be another organization. Now, you notice here that we've used the term anonymized subset. And this is to indicate that the organization X has used a set of processes before passing their original data over to environment two, the LA, which have sufficiently reduced the risk of re-identification, either in transit or within the environment two, so that it's negligible. So we have reinforced the data. So LA uses that anonymized subset under a disclosure agreement, a sharing agreement, sorry, and then releases a set of aggregate tables into the open data environment. So publishes a set of aggregate tables. Now there'll be again a risk analysis process on these aggregate tables. You remember I mentioned earlier on about the problem of subtraction attacks and there is a kind of standard developed over the last 10 years where cell counts below 10 really need to be justified. So the kind of standard expectations is there'll be no cell counts less than 10. And so for aggregate tables of counts, that is where you should probably go to in your first consideration of what those tables of counts should look like. Now for different data, the numbers might be different, but that's something to bear in mind. Next thing you need to do is understand your legal responsibilities. What legislation are relevant and how does it interact and how does individual pieces of legislation interact with regulation? So a recent example which I'm sort of grappling with at the moment is the regulatory responsibility of pharmaceutical companies to publish information via the European Medicines Agency concerning clinical trials. That's a transparency regulation. But against that there are privacy demands arising from the JNR Data Protection Regulation. Now how do those two pieces of legislation interact? And we have similar examples in the UK legislation and indeed elsewhere. Also you need to think about what happened to the data before it reached you. What consent processes were involved? Who has some stake in the data in terms of upstream involvement in the data processing? Know your data. Now one of the things you need to think about is that upstream consideration of where the data come from, how are they collected, who are the data controllers, who are the data subjects. And that can sometimes be complex. This is the example of GP records which are personal data with respect to both GPs and indeed their patients. Complex issues there. Then you think about what's called a basic data specification. So is the data about people and is the base data personal data? Now these two things are not the same. They often are related but there are instances where one might not be the other. I'm not going to go into the details of that. There are some examples in the book which we'll give you a reference to at the end. The type of data, whether there's mixtures of types of data which all create specific problems. Are the individual data aggregates or again mixtures? And then we go into the detailed data specification. What variables are involved? Are these standard key variables? Now in the book, in one of the appendices, you'll see there is a set of standard key variables which are used to represent different types of scenarios whereby a breach might occur. And these are often the first port of call for thinking about your data situation in terms of these types of considerations. Is there any sensitivity, vulnerable populations? What's the quality of the data? Does it have any special features? Is it time-linked, hierarchical? Are there multiple sources? And all of these were impact on the risk. Now understanding the use case, it's really important to take this into account when you're doing your anonymization process. What will the data be used for? Sometimes it's easy to define that. There's a specific use case in mind. But in other cases, the notion is more general. This is typical, for example, with open data. What information data is actually needed for that use? Now users will always tell you that they need all the data. If you ask a user, they'll say we need more data. What do they actually need to deliver the outcome that they're after? And that is what they should be given, the minimum amount. There's a principle of data minimization, which applies regardless of identification risk. Always give the minimum data that will deliver the utility required. One issue that often comes up is, are all the data needed or will a sample suffice? And that's quite important because sampling is a really good way of controlling risk. It creates uncertainty as whether any individual population unit is actually in the dataset and should always be considered in any data share. Who will hold the shared data? How will access to it be controlled? These are the governance concerns that are actually quite important downstream that well-formed governance is created around the data share. Then think about ethical obligations. And obviously these map onto legal considerations and data collection processes. And that's what I say about all of these components interrelate with one another. So it's a system of thinking, not a checklist. What is the relationship between the data subjects and the data? And in some senses that's the fundamental ethical question. And that breaks down in a variety of different ways. What are the loci of consent? Who is consented to use the data? And who should have consented to the use of the data under what circumstances? And what are they consented to? And was this actually genuinely informed consent? Related to that is what is the intended or expected use of the data by what might be called reasonable data subject. What would a reasonable data subject actually expect you to do with their data? And that might be something beyond what they have actually consented to. This is tied up with the notion of a contextual integrity that's employed by Helen Nausenbach. And in writing to that, how are the data subjects aware of the data and the intended use? So that again relates to that relationship between the data and the data subjects. And there is plenty of data which is collected without even the data subjects knowledge. CCTV images for example, being one example. Then we go into the technical processes. Now the thing I'm going to draw your attention to here is the first bullet point, scenario analysis. Don't go straight to the data. That's a mistake that's often made. Think first about what is it that we're concerned about happening specifically? Who is going to be doing something to these data that we don't want them to do? How will they do that? What resources would they need to do that? What's the motivation for doing that? What's the goal they're going to achieve? Now even in the book we describe the system for doing scenario analysis. It's a 12 point system. And it helps you develop that framework. And what we get as an output from a scenario analysis is a set of key variables which you can then do to produce a structured risk assessment. If you're doing something completely new, something that somebody hasn't done before, so you've got no background or precedent to think about the risk against, then you may need to carry out a penetration test. So that's an actual simulated attack on the data. And so an example that I'll give here is the work we did with the Office of National Statistics where they were intending to, or considering, apologies, considering releasing a whole load of data, about 200 data sets that were previously available under end user license and the open government license. So we carried out a penetration test thinking as if the new data situation was open data. And I won't go into the details now. There's a paper on this in the Journal of Fisher Statistics which essentially describes the process and the legal analysis that we did, which essentially showed that actually the risk was too high and therefore ONS made the decision not to carry out that transformation. You can also do a thing called comparative data situation analysis. And this is very useful for sharing data. So if you have evaluated your home situation, where the data is sitting now as being safe, safe enough, you're happy with that, then eventually you're setting a skull standard of which any other data situation can be compared to. And that's actually a much simpler exercise than carrying out insight risk analyses. You can compare the components of the data environment with your own data environment on a one-to-one basis and it becomes a lot easier then to think about where the additional risk factors are if there are any. Identify next what the disclosure control processes are that are relevant. And you may want to be restricting access. Now these are various forms of controlling the environment rather than controlling the data. You may want to further restrict who has access, how they access the data, where they do that access and what they're allowed to do with it. You may want to employ controls on the data as well. I mentioned sampling earlier on. You can also aggregate data. You can suppress some data. You can perturb the data in various ways, adding noise. Now that can be inputs, but if there's an output process you may also want to apply controls to the output of those data before, for example, they're published as per that situation we were describing earlier. Finally there's a set of things that we also think it's important to consider to do with the impact. First thing is identify who the stakeholders are and think about how you'll communicate with them at what stages. Who needs to know about the share? Do we need to inform the data subjects? The wider public, is there an engagement process that's usually done here? Do we need to talk to the users? Now actually talking to the users is really important if that helps you define the use cases in terms of component three earlier on. But you might want to engage in a public relations exercise. You might want to engage in a public engagement exercise where you actually ask for the public's input. And this, for example, is very important in setting up the administrative data research network where there was an extensive series of focus groups carried out across the country. And that both defined the operating procedures for the administrative data research network but also gave us a firm method of going forward knowing that with sample public opinion and come to the view that it was generally in favour of what we were trying to do. Also, you need to work out what is it that people need to know. IUQ, for example, can actually publish details of your anonymisation process. It's not a straightforward decision. If an intruder knows what an anonymisation process you've conducted, they may be able to use that to increase the risk of them successfully re-identifying something. Now what happens next? The key thing here is it's not another release and forget system. You need to continue to monitor risk. Monitor risk because the environment will change. And so you should be constantly reviewing the risk associated with any decision about data. Finally, you need to plan what to do if things go wrong. Now remember we're only putting the level of risk as negligible. That's our acceptable level of risk and that has agreement with our local information commissioner. So here we're on solid ground, but if you're not working in zero risk then that means that the event that you're hoping to prevent could happen. And therefore you need a breach policy. You need to avoid the lure of catastrophisation but think about what happens next. So what will you do if there's a breach? Will you communicate with the intruder? Will you communicate with the media? And so on. This is very important. How will you control the breach? How will you react to it? How will you deal with it? Be active, be planned. Okay, so including remarks. So the ADF is a tool which allows you to think constructively about your date situation. It's moved much closer to a harmonised idea of anonymisation. It's gaining traction across the world. We have consultations going on with a number of countries and only last week the Australian edition of the anonymisation decision-making framework was published. It's called de-identification in the decision-making framework. At the point of my comment earlier on about different terms being used in different countries. But essentially it's based on the same set of concepts. Now I mentioned that an open, I say a consortium should say open access book is available from our website. So if you've not downloaded the book yet you can go to our website. It's free to download. And it gives you a lot more detail on all the things that I've talked about today. Okay, thank you very much. And now we'll open up to questions via the comment system.


Meta-QTL regions with small genetic and physical intervals could be useful in marker-assisted selection. DTY 12.1 was present in 85% of the lines, followed by DTY 4.1 in 79% and DTY 1.1. The shortlisted candidate genes can be cloned to unravel the molecular mechanism regulating grain yield under drought. This article was authored by Ahmed H.U., Tixit Shalob, Vikram Prashant, and others.


Hello and welcome to the session, let's discuss the following question. It says using differentials find approximate value of the following up to 3 places of decimal. So let us now move on to the solution. Let us first define a function y in terms of x and let's take it to be y is equal to cube root of x and here we define or we take x in such a way so that we can easily find out the cube root of x. So we take it to be 0.008 and we take delta x to be 0.001 so that x plus delta x is equal to 0.009. Now we know that delta y is equal to f of x plus delta x minus fx so it is x plus delta x to the power 1 by 3 minus x to the power 1 by 3. Now x plus delta x is 0.009 to the power 1 by 3 and x to the power 1 by 3 is 0.008 to the power 1 by 3. And we have to find the value of 0.009 to the power 1 by 3 so this implies 0.009 to the power 1 by 3 is equal to delta y plus 0.008 can be written as 0.002 to the power 3 and we have its power 1 by 3 so this is equal to delta y plus 0.002. Now we know that delta y is approximately equal to dy so delta y is equal to dy by dx into delta x as dy is equal to dy by dx into delta x. Now x is y is x to the power 1 by 3 so dy by dx will be equal to 1 by 3 into x to the power 1 by 3 minus 1 that is minus 2 by 3 into delta x and delta x is 0.001. Now this is equal to 1 by 3 into x to the power 2 by 3 into 0.001. Now again substitute the value of x we have 3 into 0.008 to the power 2 by 3 into 0.001. Now again this is equal to 1 by 3 into 0.2 to the power 3 and its power 1 by 3 into 0.001 3 gets cancelled with 3 and we have 1 by 3 into 0.2 that is 1 upon 0.6 into 0.001. Here we have power s2 so we will have 0.2 square and 0.2 square is 0.04 and 0.04 into 3 is 0.12 and this is equal to 1 upon 120 and this is equal to 0.008 approximately Now 0.009 to the power 1 by 3 is equal to delta y plus 0.3 and delta y is 0.008 so this is equal to 0.008 plus 0.2 so this is equal to 0.208. Hence the answer is 0.208 so this completes the question and the session. Bye for now take care and have a good day.