Wel i'r cyfnod, a gweithio'r Wolffesyn Cymru i'r cyfnod yr Bio-Soldat Cymru. Yn mynd i'r Mike Bradley. Rhywbeth yma'n cyfnod o'r Wolffesyn Cymru, a rhaid i'r profesiad yw'r Bio-Soldat Cymru i'r Unedig Pwgolig. Felly yn y Llyfrgell Gweithgol. A gydag yma yna'n ymlaen i gael y piler o'r labn, ac rhaid i'n gweithio'n gweithio'r cyfnod o'r ffordd o'r ffordd o'r ddweithiau, a how they might relate to your problems and needs in powder handling. So first of all we've got a test rig here. This simulates the flow of material particularly fine powders when we're doing the filling of road tankers and rail tankers. A lot of people have problems with getting just the right amount of material in the right condition in logistics tanks such as I described. I that rig we've got here, we place a significant quantity of powder in the top section, drop the material through, we can measure its condition of aeration, adjust that if necessary, catch the material in the bottom, see how it flows, how it settles, and what the bulk density is which is critical to filling those 10% we then re-circulate the material through a screw-convir here, so that bring some material back up to the top so that we can recirculate and do further tests. So I'm going to show you our pneumatic conveying test rigs. Pneumatic conveying is one of the areas that we're historically best known for. We have one of the world's best facilities for pneumatic conveying pilot plant testing and quite a number of Wolfson sent, ex-Wolfson send of people have become quite important in this area of industry ond. Felly we have here a blow tank test rig, which is very similar to what we use in industry. Much of our pilot plant equipment here is at the, shall we say, the smaller end of the industrial scale. So we can do testing which is realistic, which is scalable to what would happen in the plant. So this is very similar to what is used on a road tanker or a rail tanker or indeed a land-based blow tank, where powder is put into here, pressurised with air, and then the material is driven out around the pipelines. We have test pipelines which run around our building inside the building and also around the yard outside, something like 140 metres of pipeline of each of three different sizes, again commensurate with industrial sizing. The material then is received in the receiving hopper, which is on the top of the rig, so that we can measure the flow rate of material. We can adjust the air flow, adjust the powder flow, measure the way in which the powder behaves, and that gives us the properties we need to predict how it's going to behave in a full-scale pipeline. And then we've got a second rig over here, which works in many ways very similar. We have a blow tank which puts powder into the pipeline, supplied also with air from the same compressors. One of the differences on this rig is that in the midsection here we have what we call a full stream cross-cut sampler. And the advantage of that is that we can take samples of material between conveying runs and before and after conveying, so that we can actually measure change of the material during conveying, moisture uptake, particle degradation and so on. Rotary valves are a very important part of many pneumatic conveying systems, and to many users of pneumatic conveying systems they describe them as the bane of their lives, because there are so many different design options that need to be selected from, there are so many different potential problem areas with them, and there are so many different effects that they can have on the material. So a study of the science of how rotary valves work, how to select them, their interaction with the material is a very important part of our research and consultancy. One of the important things about most powders and bulk solids is that they are affected by ambient conditions. Temperature and humidity affect their moisture content, the way they flow, the way they behave, and very often ambient conditions vary in factories and in external storage piles and so on, but also many materials are processed at different conditions apart from ambient. So quite a lot of our work we use climate chambers in order to condition material and measure their properties at those different conditions. So in this chamber here we can dial in temperature and humidity from north to 100% humidity and minus 40 to plus 180 degrees C, and we have in here a machine which measures the flow properties of the materials and so we can condition the material, we can undertake the testing at those controlled conditions. One of the most important keys to success in bulk solids handling is understanding the behavior of the material. Measuring that material behavior is what we call characterization, and characterization instruments is something we've done a lot of development of here at the Wolfson Centre. One of the things that happens with powders when they move, they have a tendency to separate. This is a mixture of mung beans and couscous that have a size ratio of about 3 to 1. Many real bulk solids actually have a wider size range than that, and you can see that what has happened, as the material has been filled into here, the beans being larger have rolled towards the outside, the couscous being smaller has stayed in the middle. So if this is something that we've deliberately made a mixture of, or indeed if it's just a natural material with a range of sizes, this can cause us immense problems with processing. So what we've got here is a characterization instrument that enables us to measure that tendency of materials to separate. So this was developed through a project funded by UK Research Council, EPSRC, a number of years ago, and it's a segregation tester. This is what we call autosegregation of materials, and it's the same process that happens when you see sand and stones on the beach. You get the pebbles at the top, the shingle partway down the sand at the bottom, and this is the natural tendency of materials. So we put our test material into this little mixer here, we mix it, we allow it to flow out, form an angle of repose here, and then we can sample it, and that gives us a measurement of this natural tendency to segregate. And that tells us either if that's going to be a problem in a process, we need to either change the material, or we need to change the process in order to reduce the tendency to segregate the material. Another important thing in many bulk solids processes is the breakage of particles. When you buy a jar of coffee granules, you expect to get a jar of granules, not half a jar of granules and half a jar of dust. So the breakage of materials when they're handled, and reduced perhaps from pellets into dust like this, causes a lot of problems in many industrial processes. So what we've developed here is another characterization technique which enables us to measure that particle breakage. It's what we call a degradation tester. So we feed the particles into this spinning disk here from which they flow through the disk, they're fired against these targets here, and then we pick up the broken bits afterwards, the broken pellets or whatever else they may be, granules, and we do a measurement of the degradation. From that we determine what we call the breakage matrix, which is a physical numerical representation of the tendency of the material to break. And then from that breakage matrix we can predict how these particles are going to break down in handling, whether it be through a pneumatic conveyor, a transfer point in a belt conveyor, drop onto a stockpile or any other part of a process. And then we can use this to evaluate the improvements to maybe the strength of the particles or the harshness of the process can be reduced, which again we can evaluate using this tester. So let's talk a little bit about dust. Dust causes immense problems in every industry that handles and processes bulk and powder materials, whether we're talking minerals and mining, quarrying or at the other end pharmaceuticals, food, anywhere there are particulate materials there will be dust. Dust causes problems with health. If you breathe dust in it can be very harmful to health, a recognition in recent years of the dangers of breathing particulate materials, especially what are known as PM5s and PM2.5s has revolutionised the attention this area gets. Not only from the perspective of inhaling of dust, but also dust explosions. Dust explosions kill many people as well. And the expense of tidying up the mess created by dust and the annoyance that it causes to neighbours is also a huge problem in many industries. So three different things here I'm going to talk about that relate to dust. I'm going to start over here first of all. This machine answers the question how dusty is the material that I'm going to be handling? So this is what we call a dust emissivity test. It's a characterisation technique where we place some dust inside this rotator, place our bulk material inside this rotating drum and as it turns so the material tumbles around inside we draw air through and we collect the dust on a filter in here. And the quantity of dust collected gives us an objective measurement of the ability of that material to emit dust. So that's very important to us if we're handling let's say a new cargo that we've not come across before or if we're manufacturing a material that is going to be used in a factory a particulate material. They need to know how dusty is it going to be. So that's how dusty a material is. Obviously very often we use filters in order to capture dust so we have a filter test rig here. This enables us to run tests and undertake research on the performance of filters, how good they are at capturing and separating materials and not allowing dust through and indeed how easy they are to clean. So the design of the filters, the type of material used, the design of the baghouse itself, these are all critical things that we undertake a lot of research and testing on. And then over here still related to filters, this is our filter media test rig. So in here we can put samples of different types of the filtration medium that go into these filters and we can make an objective test at how good they are at stopping the powder, the dust from getting through and indeed what pressure drop that they cause. And so this gives us the fundamental information that enables us to evaluate the materials that goes to manufacture these filters that we see here. So you've seen the pilot plant area where we have the more industrial scale of test equipment. Now I'm just going to show you briefly around our laboratory area where we do small scale bulk experiments and characterization of materials. So first of all I'm going to take you over to these instruments over here. This instrument here is what we call the DVS or Dynamic Vapor Sorption Analyzer. I mentioned earlier that most powders and bulk solids are affected to some degree by the effect of humidity, moisture uptake and loss. And what this instrument does, it measures how the moisture content varies with ambient humidity that the powder is exposed to. So as you can see on the graph here, along the bottom we have the humidity of the air and on the y axis you can see this is how the mass of the powder changes because of uptake and then loss of water. So here we see placing a sample of powder in the DVS in order to undertake a measurement of its response to airborne humidity. So once the chamber is closed up the computer control on this instrument automatically ramps humidity up and down with stocks for a suitable period at step values of humidity and it observes for the stability of the material mass of that humidity and how that changes before it moves on to the next one. Then from that we can construct what we call the moisture sorption curve of the powder which shows how the moisture content varies with humidity. So here we have an instrument that measures the density of particles. We have two different types of densities with bulk materials. We have what we call the bulk density which is the volume that an assembly of particles occupies in relation to its mass but of course part of that is full of air. So we also need to know the true solid density of the particles and that's what this equipment measures. It's called a picnometer. So let's talk about powder flow properties. This instrument the PFT or Powder Flow Ability Tester developed here at the Wolfson Centre and used now worldwide manufactured by Brookfield Engineering. This measures the ability of a powder to flow or not flow in a process and one of the things about powders is when you have a powder that is fine or that has a high surface energy or that is moist it demonstrates what we call cohesion which is the ability to stick together. Let me just demonstrate this. We're all familiar with making a snowball. This isn't snow or may look like it it's the same sort of colour. This is actually a pharmaceutical powder and you can see it's in a loose condition here. If I pick this up in my hand like many powders and I squeeze it when I open my hand it maintains a structure a strength here and this makes the powder hard to handle. So what we measure in terms of powder flow properties is the relationship between how hard I've squeezed the powder and the strength of the resulting aglomerate and the relationship between those two is what we call the flow function. So the way in which this instrument works is we place a powder sample in the test cell here with this placed we start a test under computer control which compacts the powder shears it in order to consolidate it at a controlled stress and then we change to a different stress and we shear again to measure the strength of the powder. Under automatic control this runs about 40 different tests at different values of consolidation stress and test stress. The data comes up on a graph over here which shows the effect of the stress the measured strength of the material versus the test stress that we use for a range of different consolidating stresses and on here what we see is what are known as the yield loci for the powder for different consolidation stresses. They're fitted with Moore's circles as shown and then from that analysis we calculate what is known as the flow function of the powder and the flow function is the unique fingerprint of the powder that relates its strength to the stress that has been applied to it. So by using this instrument and making that measurement of powder flow function we can then determine how large an outlet is required on a hopper or a feeder or a silo to get reliable flow with this material or alternatively we can use this the other way we use this very frequently and many of the users worldwide use it in this way for powder formulation optimization in other words adjusting the formulation of their powders and the manufacturing of their powders to generate as it were user friendly handling properties and that's one of the most popular uses of this but it's also widely used for quality control as well checking from batch to batch with powders that powders have consistent flow properties and those consistent flow properties often mean then that the the powder has consistent processing properties in its use so it's used for for example measurement of the coffee grounds that go into the pods that go into into coffee makers because a consistent flow ability here indicates a consistent particle property which means that then when you make the coffee using the pod you get a consistent flavour from the coffee also used for many other industries as well in pharmaceuticals in in aggregates inquiring mining and so on as well so here we have the so-called powder spreadability tester and this relates to additive manufacturing or 3d printing manufacturing of components by taking powders and fixing the grains together to make a component rather than taking a block of metal and machining away what you don't want is very is a very fast growing trend in manufacturing lends itself very well to high value components and small production runs and so on so that's the powder spreadability tester moving on we talked yesterday about segregation and the ability of particles the natural tendency of particles to separate by size we referred to what we call free surface segregation where when you have a heap of particles the larger ones tend to roll to the bottom the smaller ones than to stay in the middle there is a different kind of segregation which occurs commonly in many processes called air induced segregation and this commonly happens where a powder blend may be for a pharmaceutical or food manufacturing typically is dropped down a shoot from one process to another and the counter flow of air causes the fines to be stripped out and this instrument captures and makes an objective measurement of that trend of the powder to separate by size so within this we place the powder in a hopper on the top here and it runs an automatic program that turns on an airflow drops the powder and then we separate the parts of this column and we measure the size distribution or chemical analysis or maybe taste or smell or whatever it else that is we're interested in between those separate segments so the machine works automatically it runs a test in a standard way and then that provides information to us really about how easily that powder separates and again we can use that either for improvement of processes or for improvement of formulations to reduce that problem in manufacturing size and shape analysis of the particles within a powder or bulk solid is very important because that controls critically many of the aspects of their behavior we have four different methods of measuring particle sizes and shapes here at the Wolfson centre all of which have their own advantages and disadvantages so the machine we have over here this is the optical size and shape analyzer this uses air to disperse particles onto a slide it then takes pictures of all the individual particles and produces for us an analysis of the distribution of the sizes and also the distribution of the shapes as well and then over here on this side we have a laser particle size analyzer so this uses diffraction of laser light the particles go into this dispenser here and in the machine the particles are projected in an air stream across a laser sheet and the diffraction of that laser light enables us then to determine the size distribution of the particles within that sample this is particularly useful for where we're dealing with extremely fine particles often for coarser particles we use sieve analysis and we have a sieve analyzer so the sieve analyzer is operated from the computer here and then this then gives us a simple print out of the size distribution of the particles within the analysis as we see here the principle of sieve analysis for size distribution measurement is to use a stack of sieves something like this with different size holes so we place them on top of one another we shake the sieves and the particles of different sizes stop on those different sieves now the old-fashioned way of doing this of course is to weigh these sieves put them together put the material in shake it and then take the part and weigh them again that's very labor intensive and very often we have dozens and dozens of sieve analyses to do for a project so we use a computer controlled robotic sieve analyzer here and the way in which this works is that we place the sieves inside the machine and we have a variety of sieves of different sizes in here largest at the top the smallest at the bottom and when we're ready to run what we do is to load the sample sample is pre-wade over here we place that in the machine and then we start the machine under computer control at the end of the cleaning cycle the machine brings all the clean sieves back together ready for the next analysis so here we have another method for size analysis by sieving that applies particularly to particles that are too fine or too cohesive to drop through a normal vibrating sieve under gravity and this we call our air swept sieve the way in this machine the way in which this machine works is that we have a variety of different sizes of sieves here but we can go down to much smaller sizes than on the ordinary shaker sieve this enables us to sieve down to about 12 microns and the way in which the machine works so as well as having the vibration on the sieve that goes in here it also has in here a device which projects an airflow through the sieve while the vibration is being applied and that enables us to encourage a flow through the sieve of particles that would otherwise either ball up or stick on the sieve and there are many advantages of sieve analysis one being that it's a particularly direct and reliable way of sizing particles but obviously this extends the reach of that technology so some other different characterization techniques as well which we use here quite widely this is the poured and tapped bulk density tester so we put a sample of powder in here and after tapping it we see how the bulk density varies and this is a common test used in many different industries to determine the bulk density for the equipment design but also to look at how bulk density changes with tapping which gives us a measure of the powder behaviour so we take the measuring cylinder and we would weigh out a certain quantity of material and having weighed this material we would put it in the cylinder here read off the volume as poured place it on the machine and we would allow that to run for a designated number of taps it's interesting to note that different industries have different standards for the number of taps used and then we can see the change in the volume that occurs here and hence we can obtain both the initial poured density the settled tap density and the ratio between the two which is often known as the housing ratio then we have the so-called texture analyzer here this is essentially a computer controlled press which enables us to apply a vertical force a vertical movement and measure the force so we can use this for compacting materials again to see how for example the bulk density varies with stress but also for larger particles we can put a fixture in here where we can actually break the particles and measure the individual particle strength which is important in many instances moving on this is the particle attrition tester in a small scale so this we use to measure the tendency of particles to break during impact again so inside here we have a rotating disc particles are fed in through the through the funnel into this rotating disc here they come down the channels accelerate out and then they hit the targets in here we then pick up the broken particles and we can do a size analysis and therefore just see how much the particles break down so this again is a good method for measuring the breakage matrix of particles which we can use that information then to predict the level of breakage within a certain process or again we can use it to aid formulation by changing the structure of the particles in order to make them stronger more resistant to break down mixing is an important process for many particulate materials lots of particulate products are made of particles of different species that are blended together and this is one of a number of different types of mixing technology that we use that we test here at the Wilson Centre this is known as the turbulent mixer so the sample for mixing goes into the pot here and then that's put on the machine in order to blend it and as I say this is just one of many different mixing technologies that we experiment with here at the Wilson Centre because different types of materials require a different action in order to mix them effectively a very important aspect of bulk solids analysis is sample subdivision when we receive a large sample of material maybe from a customer's plant or perhaps from our own pilot plant this is much too large a sample to analyse whether we want to do sieve analysis flow property testing or anything like that now if we just put a scoop in and take some material out that is not going to be representative of the average of what's in the larger sample because in this larger sample we will have segregation the particles will naturally be separated by size so we need to find a way of subdividing this to obtain subsamples that are fully representative we use this machine here which is known as a spinning riffler so we have a hopper here a little feeder at the bottom and a number of bins here on the turntable material goes in the top and when we run this the material is fed out of the bottom of the hopper flowing down here in a first in first out discharge pattern or mass flow as we call it as the bins go round because they rotate continuously each of these bins receives multiple cuts through that large sample so each of these eight smaller subsamples is fully representative of the average of what we put in and therefore when we analyse this the results are meaningful in relation to the larger sample that we started with here we have a fluidised bed test rig fluidised bed processes are used in a very wide range of industrial applications where we need reaction between gases and solids catalytic cracking of crude oil to produce petroleum products is one of the best now but there are many many others as well so what we have here we have effectively a a cylinder glass tube in this particular case and in here we have our powder then from the bottom we introduce the gas as the gas flows up through here it causes movement and dilation of the powder and the intimate contact between the powder and the gas then gives us a very good reaction so whether we're looking at heating cooling chemical reaction or anywhere else where we want close contact between gas and powder for process purposes this technology is widely used and we can set this up to simulate the movement of the fluid bed and the process that is going on inside so you've had the short tour of our facilities here at the Wolfson Centre you've seen our extensive pilot plant facilities and our labs as well for characterisation and so on all of this equipment is available for use for industrial purposes for design projects for troubleshooting and so on if you come on one of our short courses you can come and see this in person or indeed on some of the courses you'll get your hands on and actually get to use some of this equipment and of course if you have requirements to deal with bulk solids where there is currently limited knowledge then we get involved in research through lots of different means as well so thank you for your time and bearing with me and I hope we get to meet sometime


I think that I can do something with this here tube. I have to excuse my bad lighting. It's raining out, so it's real dark. That's also why I'm working on this. So my question here is, is this going to melt if I have like a conveyor belt running along and rubbing? I think it might be okay. Maybe if a lot of the material I'm moving is going to be wet, or at least, you know, damp. I think it should be fine. All right, I'm going to try it. Oh, this side, this side, that was a bigger one. I did get a little bit of chipping and cutting it with a saw to put the chunk broke out. But that's fine. Okay, well that fool is starting up. Let me think about what I want to do here. You know, I think I can just melt the ends. All right, the bread's on, and I think that looks about right. I don't know. Good enough. All right, so a rotary thing goes here, I'm going to attach a pipe from here that goes down the side, all the way to the other end, and then another pipe at this end that attaches to the little bearing here, all the way down there. I have lots of stainless steel round pipes, and I also have aluminum square tube. The square would be a nice shape for this, much easier to attach things. Am I going to have a problem with the aluminum and corrosion? I used that square tube on this here. These parts here would be splashed by the most salt water, and they looked 100% fine. All these ones up here, they're pretty well protected anyway, and what a cool roof. Yeah, all these look, it looks like it's brand new, except for, you know, some paint or whatever, but I'm not worried about that. I don't see any signs of corrosion on this, so I think this stuff should be fine. Well, that's awesome. This stuff is nice and light, and strong, and great shape, and this piece is not a full one. I took a little piece off the end, however, I think it'll be long enough. 213 noodle units, so 106.5, oh beauty, that's a good spot right there, however, I don't want to cut the pipe directly in half, because the pipe here will just come up to this spot and bolt into one of these holes, and I'll make some kind of reinforcement thing, so this isn't swiveling on the end of there, but this one only comes up to there. The other one, I want to come up to the bolt for the bearing, so this side needs to be like two noodle units longer than the other side. All right, yeah, I'll just measure one this way, I'm going to add one to that one, subtract one to this one, it'll be two noodle units, that should be good, put the pipe right there, another bolt up there, it'll keep it from, all right, now I can attach my pipe here, that's pretty good, all right, where's the other one, yeah, other guy, okay, here's my bearing and everything, so I just need to drill a hole in the pipe, put it here, put a little spacer so the pipe isn't hitting this, well I guess before attaching anything else, I need to do the roller at this end, hmm, oh I guess I'll just make another one of these for down there, keep this 90 degrees aligned, suckers go there, and it goes way down the other end, not entirely sure how much adjustability I need down here, yeah, I can move this, there's another spot up here where I can connect it, you know, so it's connected well, and if every two centimeters is not enough adjustment, adjustment on this piece, I have a hole that goes between, so if I move the bolts from there to the other holes, it offsets them by one centimeter, so I can adjust everything down to one centimeter, if that's not enough, I'll put another hole in here somewhere to get it down to half a centimeter, I don't know, we'll see how it goes, thinking before I make the belt, I'll put this on the shortest length, that's actually the second shortest length, because probably I'm gonna have to stretch, so yeah, see, this thing still fits, now I need a belt, okay what do I have here, this stuff is really tough, might use that, definitely don't want to use the dark blue because I don't have that much of that, let's see, not that, not that, this, I'm not sure if this is thicker than this other hole, no it is totally, this is totally thicker, all right I gotta mark every nine imperial noodle units, and I don't want either of these edges on the outside, so we'll fold them in, so this is going pretty slow because I'm doing triple stitch, which does two stitches forward then one back, then two forward and one back, or you could say it does forward back forward, forward back forward, so on each spot it does three stitches, one forward, one back, one forward, now why is this, what's the point of this, why is this better than just running three straight stitches, okay if you have straight stitches, even if you have three straight straight stitches, you have, that's what this first stitch is here, you have threads that run along the cloth, and every time there's a hole, you know they loop around each other, but you basically have two threads running the length of the cloth, and if the cloth stretches more than the thread can stretch, the thread will break, but with a triple stitch, you don't have straight threads going all the way along, it'll go forward, back, forward, forward, so your your thread like loops back on itself over and over, so if the cloth stretches more than the thread can stretch, it can just kind of like uncoil itself a little without actually breaking, all right let's keep going, all right let's see how it does, I didn't sew this all tangled up, and that is on the loosest setting down there, so I should be able to tighten this, yeah I need to attach some wires to here, 12 amps of current, that is not that much, I don't need any fat wires, what do we get? okay now I need some electricity, all right let me just connect one of these batteries, it's not the right voltage, but should make it move some, oh great, that's actually pretty strong, thinking I might want to rubberize that top wheel up there, the top roller, because when I put my hand here, I could stop this from moving, but the roller was still turning, so it just didn't have enough friction to you know overpower me, doesn't necessarily have to overpower me, but yeah there's definitely a lot more, what's it called, strength that can be gained with some traction up there, also it's going to go a lot faster because that was a low voltage battery than what the motors made for, so I guess, well think about rubberizing the wheel, maybe I'll just give it a real test first, I gotta think about what I want to do, maybe I'll wait till it's not so soaking wet and muddy out, I guess I'll need to make some kind of frame here, I can hold that end up, and then this end, and yeah it's still a few things to do, but I think totally works, so that's good.


And I'm good to see all of you here. I'm so glad to be able to talk about recent work I've done to formalize a data quality assessment framework for the chief government data steward in New Zealand government. I recently started that office was recently initiated in the past two years as well as a chief digital steward focusing on data, looking at capabilities across agencies. And they were looking for someone to come bring experience and industry knowledge into their advice bureau. They have a website where they keep lots of different kinds of advice on data governance, data management, and particularly things like Open Data Program, our flagship advice bureau. So this program or assessment framework was done in a year, a deliberate write-up of my work at the Transport Agency and modified and adapted to an all of government context. Further to context, I plan to talk about this introductory material three aspects to bear in mind in the design of this particular framework. It's meant as an exemplar, not as a to-do list. So it's a abstract from a data architecture perspective. It's a process model. Essentially the topics, you could say it's biased in the sense that it's quite data governance oriented, but discussion here of data governance and data management and the differences in roles and responsibilities, which is practice-based. The second area is that it's important for this to be realized that this is in the context of data quality as a program, not as a particular project. Mainly it's a journey and developed in cycles of capability. That's because we recognize across agencies that they're at all different levels of maturity in both data governance and data management. And that lastly, in particular, as I say, it's a process example. It's meant to show the highest level results or outcomes of developing these processes. So all agencies are doing some sort of data quality issue management and remediation. They probably call those activities by different names and they're likely performed by IT. There's not necessarily a recognition that there should be business stakeholders involved in remediation or people involved in the process of delivering critical information for the agency's mission. Here is to bring forward an example process which is based on standards that articulate best practice for such a process. In order, the data governance data management conversation really is to highlight, there's an important separation of concerns here. Data management, make sure that information is managed properly. Data governance ensures that data is managed to achieve business goals. What does this mean? It means that governance is really focused on oversight and goal setting. And management is more focused on provisioning or should be focused on provisioning and monitoring. It's often a lot of finger pointing as to which part of your IT business organization should be fixing data problems, data quality problems. And that's often to do with a loose recognition of the different hats or different roles that are necessary to really have both sides of lifecycle managed appropriately to assure good data quality. So governance is responsible for resourcing, authorizing and creating policy where data management is more about delivering system projects, performing monitoring and providing the technical talent to data projects and possibly provisioning, working with IT to provision data platforms. But they don't have a lot to do with the business mission or understanding the outcomes or the opportunities that are possibly there for data and new products and new services that are supported by quality data. It does make a few assumptions as well in terms of fundamental capabilities. And some of our agencies are quite low in their capability. So they will have a hard time understanding this but basic catalogs need to be there in terms of, I guess with data and scope as we put it. A lot of data catalogs are there as lists of data but we also need to manage data as an asset and understand the risks and business services associated to that data to make it more conversational with the business owners, process owners. Also a capability to manage and the production and distribution of data products resulting from good data, treating data as a valuable input, meaning the whole life cycle, not just capturing the data but what happens when it's put into a warehouse. What happens when it's turned into an analytics product? What happens after it hits a dashboard and influences behaviors in business partners or business functions? How does that full life cycle get addressed? And really it's to say that there's this important conversation between the two sides of the house, the governance side and the management side. These are emerging fields of course. So everyone will have a different level of capability. The second point data quality looking at it as a program rather than a project is quite important because of all those coordination activities. I mean, my program does outreach and training work to get people on the same page, even have the same terminology for data quality concepts and to get issue reporting done in encourage issue reporting. For many years data quality problems are left on the cutting room floor and people have given up on where to turn because IT data management don't know how to resolve things and there are no standing governance groups to have conversations with. So sometimes you have to bring up these basic services and get issue reporting working across different groups. And I guess what I'd say too is I developed a pilot project to go through the whole cycle and learn and everyone in that process learned and I use that they are ambassadors to the process for other teams to get going on their own projects for data quality improvement. Really important through all that was to build the right relationships and those relationships have to be enduring from one data quality process to the next one because many of the same people are involved across the enterprise and many are specialists to just a particular project. So the person who's the quality program manager has to be able to create and manage relationships across a wide variety of stakeholders all those shapers of the data and reuse those relationships hopefully to the next quality projects. Next to the data quality is a process concept. Here is the process by the way this is the data quality framework. So I'll talk more to it in detail shortly. Just as a high level idea of this process there's three core components they're the colored boxes with feedback built in to ensure sustainability. This is important stuff that I learned actually in my informatics work at Landcare Research about building sustainable systems ensuring that there were actual outputs from a process that became inputs to another and work through all the people who are involved and who can build and improve those feedback loops is just as important as those who can build the fundamental processes. Each one of these three are complex. However, at the highest level you want to be able to enable prioritization of quality issues I don't explain that shortly. You want to be able to actually drive quality improvement through good requirements, data quality requirements. Now measuring without requirements is sort of a lot of busy work of measuring quality understanding the requirements in the context of the business will narrow the level, narrow sorry the number of measures that you have to do make them more relevant and keep them in use to actually report the health and status on data sets. So these mechanisms here are kind of the outcomes of three complex layers of processing that happen kind of across the data quality program. These are based on international standards I'll just point that out upfront the data governance ones which talk about three layers where you evaluate this is why this assessment framework they're evaluating priorities you're evaluating value and risk and so forth. You direct activity through requirements direct measurement activity in particular and do the monitoring, continue the monitoring in order to get that trend analysis and you'd be able to tell if getting better or worse at quality hopefully better as we are measuring toward the requirements that the business specify. This was also informed by industry models really important 3T industry models I use the 10 steps framework by Danette McGillfrey which was published in her second edition last year. Her 10 steps framework takes you through really important things about understanding the business context of a problem working through the environment considerations like the data platform how the data itself is managed and passed from one process to another whether or not there's more sophisticated ELT or ETL or however you wanna call it processing going on moving data from primary operational systems to analytics platforms or data lakes or data warehouses and all of that lineage stuff is really important to understand where the data has been and how it's been transformed. A really great framework as well to sort of enable agencies to start where they are and recognize the roles that they're already playing in this framework is called the non-invasive data governance framework by Rob Seiner. It's very helpful to listen to Rob a few times he's at the university. He goes through what he calls you know everybody's a data steward discussion and it talks about the wider involvement of your specialists that work in analytics and work in business analysis as well as those that crunch the numbers and do the measurement of quality. And that's a really simple but really important message we tend to keep the data quality stuff in the background or down to the individual's responsibility and it does involve some checking with your peers and other perspectives on how you're doing with the measurements themselves like using consistent measures for example or using standard measures for example, very important. That's where the conform dimensions of data quality come in with Myers work. He took 16 different data quality dimension type measures, brought all the definitions and terminology together and came up with a list which is very helpful. I think 28, you know, you don't need them all but you can have quite a good choice amongst very well researched and utilized data quality measures. This resolves an issue that we have witnessed that agencies are using lots of data quality measures but they're not very comparable. They're not using the same terminology. They're not using the same formulas. They're not using the same concepts. It's confusing to be fair. These concepts have developed over 25 years but everybody picks a flavor and they sort of ignore the rest. It has been a dialogue within its own discipline for some time and Myers has helped to rectify that into a single set of useful conformed measures. So I'm going to move now to what I promised, talk about the three components in this model and a bit of the feedback loops. At this point though, are there any questions or comment? More clear as mud, cool. Right, next then I'm going to shift to these three components. Just remembering we're talking about prioritization of issues, improving requirements and performing standardized evaluation and reporting. As I've mentioned, each of these is kind of complex. So the sentences here, I wrote these sentences here for your takeaway. So I'll say them briefly, which is the data quality issue management, impact analysis and value assessment, each have their own processes, which you can have as much or as little process as your organization can tolerate based on your capability. It's important though that you recognize that you have to have some fundamental way of tracking information about quality issues and tracking those issues and working them through those people who shape the data who can help resolve those issues. There's been significant research in again, 25 years to show that 90% of the data issues are resulting from conflicting business processes or from outdated data structures that have simply been acquired and moved from one business to another without redesigned, you know, coping with what is rather than reshaping and redesigning things to meet new needs. These are all environment factors on the data which need to be analyzed. Mostly you can get a lot of information out of your architecture artifacts, but really it comes down to planal systems analysis work. Basically, we get the reports and the logging going, then root cause analysis, which as I said has, there's some good literature included in the framework here, detailing 15 typical root causes and looking through, you know, who you an interview would actually get to, the facts and knowledge of your particular data environment. Getting through a business impact assessment which means you're talking to business people or people are responsible for the mission of the organization. And yeah, lastly, promoting your issues for remediation recommendations to your governance groups who have the authority to resource and make necessary changes to the operating environment if those are in fact the cause of your data quality problem. Working through the requirements is really important, the second one. And it talks about this section and there's a whole paper on this asking the right questions about data quality requirements as well as system requirements. When systems are built essentially requirements are gathered but it's typically about the user interface or the reporting needs and not a lot about data quality issues such as, you know, onward sharing issues of resolution, issues of how to aggregate certain fields properly, solving it sort of once for all. These kind of things and get solved ad hoc much later and then varying fashion. So the requirements gathering aspect is quite important. It says here, you know, typical uses for the data tolerances for completeness of precision in the data and requirements for currency, you know, for monitoring or decision making, all of these requirements could be gathered in the papers written for business analysts who are next to the business and can get the interviews working such that they get these kinds of answers that are relevant for onward use of the data. And evaluation and reporting mentioned before 19157, that's a data quality center for geospatial information which lays out a framework for evaluating quality and then a specific set of reports that consistently report how you measured the quality, the context, you know, the scope of the data used, the purpose, the reason you needed to measure the quality, you know, any trend, connection to trends, obviously you need a bigger picture, you know, then a couple of measures to talk about how the quality is currently or what we call how well the data is conforming to requirements, which requirements, et cetera. So this area here, consistent measurement, consistent evaluation and consistent reporting, this is the biggest problem in general when getting at any trends of data quality and libraries of tools exist to assist us. So all the paper does is bring those forward and you can choose what is relevant for your particular organization. Next, talk about these feedback loops. So again, this is the model. My dialogue or my conversation box is in the halfway in the way of my slides. So I'll do my best here on the right side, but the really important conversation at the outer loop is between what I call the business domain governance group or the data governance group and the enterprise data management team. For the reasons I said before, you know, there's a separation of concerns there, the governance group should be providing the improvement plan for the data, including resourcing. The data management team should be responding with the communications plan, showing how they're achieving the plan, sorry, progress to plan, is it where? It identifying the stewards and keeping the stakeholders informed. And it's a very simple feedback loop, but it's amazingly difficult to achieve this level of clean communication. And this alone has mitigated an enormous number of quality issues in our crash system that transport. We had all kinds of messaging going back and forth between parties that thought they could fix things, never really a clear plan, never really a clear sense of progress to plan and quite a bit of confusion on the stakeholders side as to what exactly was going on to fix the problems. A lot of noise, in other words, not a lot of signal. So this helps quite a bit to clarify what is planned, what's been done and who needs to know. Likewise, I should say inside, I'll call them the inner loops in this framework are far more interesting. Essentially the prioritization of issues can help inform and refine your requirements as well, okay? So that's helping to develop an evidence base that's a bit more effective. You develop your evidence base of issues by logging, doing your impact analysis, having those discussions at the business impact level will help a lot in prioritization. This will help inform your requirements. Better requirements means you have more relevant criteria and metrics which assists in effective and efficient performing of standardized evaluation. And outcome from that is also, as I put it here, enable and comparable assessment with performance of standardized quality measurement in turn will enable more robust and relevant health and status. And that's what we're looking for at the management level, in the governance level, they wanna know what's the state of things, how healthy is this important data set? You've got us to identify as a key asset to manage. What am I looking at? I need to look at the health and status of it and I need to understand the articulation and articulate the value and risk of it being non-conformant. The value of it working for us on the risk if it doesn't. These are the business decisions that the governance group needs to have in focus with the help of the business analysts. I note they're in this, the entities that are conversing here. So that in the first loop, the business domain group talking with the enterprise management team and these secondary loops, so the inner loops is quite important that you're involving the newly arrived data analysts and data scientists. For many government agencies, this is new stuff, right? Another whole team messing around with the data. Those people are finding because they're creating new data products every day, they're finding your data quality issues. They're the ones that need to be involved in reporting issues to someone and they're not sure where to turn. They can also run these metrics. They also are doing it every day. They're running metrics and doing quality assessment on data to see if it's suitable for their projects every day. Knowledge is going on the cutting room floor because they have nowhere to report their bumps and bruises with the data. Any problems they have keeping to themselves. So giving them these mechanisms to report information to be involved in the conversation of metrics and the involved in the conversation of requirements is actually utilizing their knowledge and experience more effectively and more effectively. Likewise, business analysts have a relationship usually as I mentioned, has a relationship with the initial stages of a data resource being developed because they're building new systems. They're involved in the design and the collection of requirements. They don't often get to see the round trip. You know, what happens after the system's been built, how the data gets used in new products and services. So this will involve them also in terms of the priority conversation, involve them in how the data's meeting the business needs and give them the opportunity to describe and work through some of this health and status information to make it more effectively understood by all those middle business process managers as well as the overall data owner. They're the interpreter between those various business services and the data management function. So far, any questions? All good, basically. All quiet? Yeah. Okay, we're very close to the end now, right? So two more slides. So I just want to point out that I heavily use standards to develop this process. I'll back up a second to this process. Just to say, you see, it's highly, this is quite abstract for a reason. All the standards point to the same three capabilities you need, how you develop them, how you deploy them is based on the capability of your own organization. But this is the outcomes of having good logging, good analysis of issues, so you can prioritize. The outcome of requirements, I should have probably put something like improved with a passive voice. If you want improved data quality requirements, you really want current data quality requirements. Currency is maintained through knowledge and relating use of data to the measurement of quality of data. And likewise, being able to do any kind of standardized evaluation is critical for trend analysis to understand how the data is doing. These standards here, I provided and they're in small print because there's a bit of information. But importantly, they've influenced the design of the principles and components of the modules, of this framework. I used a couple from the governance, particularly the data governance standard. Came out in 2019. Three from the data quality suite in ISO 8000. Two from the geospatial domain. One is mentioned when 9157, which is our data quality general requirements recently revised and available now as this, which means public comment. Probably going to full, I don't know what it means, completely revised by the end of 2022, ready for purchase, I suppose. And I used this other one, which was the quality assurance of data supply. And I use that because in transport and in many public sector agencies, they actually don't produce their own data. They buy it. And they don't really do well explaining what they need in the purchase agreement in terms of quality. Especially if it's ongoing, we have traffic loops, we have, gosh, we have ongoing data collection, which is subcontracted. We have hundreds of thousands of dollars involved in those contracts. And surprisingly, apart from saying it needs to be to us at a certain date, there's very little quality requirement built into the contracts. This helps to actually help you create some of those words, those phrases that need to be in your supply contracts. Let's see. And also the toolkit coming up. So toolkit wise, a lot of people ask me about this. So many architects like this less than my practitioners I'll say. But a lot of people want tools. I created the simple set of tools to come with the framework. So the framework involves the diagram, explanatory notes for the diagram and rationale for the design, as well as essentially people in process oriented tools, not technology-based. We can always buy technology stuff to do data quality measures and automate, but we really have to get the fundamentals right in terms of people in process. For people, it's record keeping support in terms of templates for how to do your data quality issue management and the guide for data governance groups on how to have those effective conversations to get relevant policy developed and remediation plans agreed and supported meaning resource to repair important data quality issues. In the process area, this metrics or measures standardized that customized, I'm sorry, but consolidated group of measures provided by Myers. And there's a whole set of measures as well for the geospatial information through 19157. And finally, a guide for the relevant standards which details in this previous slide, how exactly these standards informed the framework. There are some considerations, I guess I wanted to wrap up with, to say, what did I learn out of this? I think it was important in terms of principles to maintain a flexible approach to realize that this was an exemplar and not the perfect framework to make it outcomes oriented rather than very specific itemized process lists. You can come up with your own process lists from the standards as well as what you're already doing. The really important thing is to realize where you already are and your capability and that you can map your capabilities currently into this exemplar process. The goals, very important principles two and three was really about it must do a lot to improve the remediation activity that's clear up the communications, that's make the roles right, that's make sure measures are associated to requirements, make sure that the health and status information flows back, back up to the data quality, data governance group, make sure that the data management group is comfortable with their new relationship to these business data scientists and business intelligence people. I mean, there's a whole lot of improvement there for communication and remediation that the framework addresses and enable or make sure of comparable assessment as a very important principle to this. Hence the sticking to industry defined standards for measures. The design goals here is already outlined with people centered approach rather than technology. Yeah, continuous improvement is a critical aspect because the first time out with a pilot you'll get a few ways around the ropes around those links and then you realize we're a little bit short in this capability we could have done better over here. So it's always good to view it in the context of building up better capability and that it's a shared responsibility that all these roles have an important point to play and that data management and data governance don't have to be at odds. No, they just have to realize where they're sharing where they're sharing the responsibility for the outcomes of the data quality process. I found it helped a lot to start with standards and to start with industry practice. You're starting with your peers as well. The challenge I thought was to get some data governance groups off the ground and to get them to take responsibility for remediation plans because this was something that was new to our organization so they had to find a way to not only make the time to meet but make the time and the effort to look for resources to actually invest in the data and invest in remediation plans. I'd say for anybody taking on a data quality program you need to think about your own organization's culture and the governance activities that would be practical so you can make real improvement but look at it from the business process point of view rather than just the technical aspects of data creation, data storage and so forth. All these people are shaping the data as your organization has moved into analytics and other data products, data sharing arrangements. And yeah, try to keep your, if it's possible making data quality a program rather than the project was quite important as I say because I was able to retain all these stakeholder relationships and redeploy those relationships and not wear everybody out to look at every problem. I carefully balance the talents against the problems and try to make it realistic for people to have in their work scope. So this will be published soon on the New Zealand Government Data Capability resource website, this is the address data.gov.nz. We'd love to have feedback on the framework and to say that the actual guides and stuff will be shortly available. Data lead at stats.gov.nz will be the home of the formal documents, currently it's in soft launch. So it'll be formally published soon. And if you wanna get in touch with me at any time, happy to speak to this again in your own organizations or over chat, over video. Here I am at Transport. Thank you.


The study assesses demographic factors associated with COVID-19 vaccine acceptance, hesitancy, and refusal among the general Pakistani population during the pandemic. The results show that older people, females, and less educated groups are at a higher risk of COVID-19 infections due to vaccine hesitancy and refusal. This article was authored by Ayaz Ali Samo, Raheela Bbisate, Jitanda Velacha, and others.


Good evening. This is a watermelon. To be specific, it's Watermelon 01, an iconic model with a surprisingly rich history. Most people know it from Gary's mod, though it technically comes from Half-Life 2 and it's appeared in tons of other Source Engine games as well. It's also always had a bit of a meamy reputation due to its comical nature, and to a lot of people it is synonymous with goofy G-Mod shenanigans. But what if I told you that this watermelon here was also the key to one of the most interesting and bizarre pieces of Lost Gary's mod history. Something intoxicating that once captivated a cult community and was seen as a staple of the game, but was removed for mysterious reasons over 15 years ago, and has now been relegated to complete and utter obscurity. Today, I want to talk to you all about the phenomenon that is let's go back a little bit. The year is 2004. The blockbuster Half-Life 2 just released, and life is… good. A scrappy young British guy named Gary Newman, who's living off proceeds from a dating site, gets his hands on HL2's mod development kit and, with some inspiration from another project called JB Mod, creates this little thing we know today as Gary's Mod. Now, you might already know this, but at its inception, G-Mod wasn't much other than a white room with a gun that could pick up props and make ragdolls do nasty stuff. However, Gary's continued support for the game and adding new maps and features helped it quickly gain a following on online forums like Something Awful, and did eventually completely overshadowed its predecessor JB Mod, becoming by far the most popular Half-Life 2 sandbox mod on the market. Gary worked hard on the game non-stop for about a year after its launch, before he finally hit his first major burnout and became bored with the project. 2005 very well may have marked the end of G-Mod's development had it not been for him suddenly discovering the programming language Lua. Lua's support would allow G-Mod to easily hot-load custom game modes and weapons, and today is remembered as one of the biggest factors in the game's success. Gary saw its potential from the start and became excited to release it in a new update and see what the community would do with it, and in order to get the creative juices flowing, he and a couple of his pals even whipped up some simple Lua-based game modes and maps to show off his examples of its power. All of this content was unveiled with G-Mod 9 in October 2005, but curiously, none of it exists in the game today. We'll talk about why in just a second. And while none of the G-Mod 9 game modes are particularly complex or impressive, they are all unique and fascinating relics of a G-Mod era that has long passed. For example, this instagib mode called laser dance where your gun kick back sends you pummeling through the air after each shot is kind of unique. This long shot mode, where whoever can get ahead on the other from the longest distance wins, is actually pretty fun. And it's interesting to see how these primitive versions of zombie survival in hide and seek might have inspired similar custom modes that are popularly played in the G-Mod community today. But standing amongst this crowd of gimmicky experiments was one clear standout by the name of Melon Race. Or Melon Racer. The two are mostly interchangeable. Melon Race is a game mode designed by Gary Newman himself, and it's the only G-Mod 9 game mode he designed more than one level for. It's remarkably simple, and from the title alone, you can probably get a pretty good idea of what it is. All players on the server take control of a watermelon, and the first person to make 11 laps around this small bizarre race course is declared the victor. Sounds pretty simple, right? Well, don't be deceived. Beneath this outwardly simple premise is a surprising amount of depth. Take the game's controls. Your only options to move are to propel forward and backward, steering with the mouse. It's easy to pick up momentum once you get the ball rolling, but it's just as easy to lose control and splatter your melon against a rock or a wall, which kills you and resets your lap from the beginning. This creates a balancing act between speed and precision, and with such a limited control scheme, it actually creates a pretty fair challenge that scales with how competitive you and your friends are. But if you're like me and you don't have many friends, don't worry, because it's also possible to play the game mode alone and just see how fast you can make a single lap around the course. This on its own is almost more fun than the game itself to me and has eaten many hours of my time. It doesn't look like I'm alone either, since Melon Race to this day has an actively maintained speedrun.com page. Getting back to the story itself, despite how simple Melon Race is, the game mode is actually very fun and, dare I say, addicting. It's almost flappy bird-esque in nature. And because of this, it actually amassed a pretty active following back in the day and even had a custom map scene. I was able to track down a couple of these, and while, unsurprisingly, most of them kind of suck, they're still interesting time capsules to explore, and go to show how much people resonated with the game mode back then. Unfortunately though, this Melon Race community was never given the chance to flourish that it deserved. By the time 2006 rolled around, GMOD was becoming quite popular, and had caught the attention of Valve themselves. They approached Gary Newman with a deal to sell GMOD on their digital distribution service Steam, which he initially denied out of skepticism anyone would want to pay real-world money for it. However, after some negotiation, Valve and Gary eventually came to an agreement, and development began on a new commercial version of Gary's mod to be sold on Steam for $10, with the proceeds split evenly between Gary's Team Face Punch and Valve. This new version of Gary's mod was what we know today as GMOD 10, and while it made the game much more secure, stable, and user-friendly, it also unfortunately made some big sacrifices. Namely, apart from Sandbox, every single game mode that was included with GMOD 9 had been suddenly removed. Was it because the team had issues porting them to a newer branch of the Source engine, or considered them too rough to be part of an esteemed commercial release? Maybe there was trouble getting permission from some of the game mode's creators to package them in a retail product? Well, no one seems to know for sure why, but when GMOD got its official release on Steam in November 2006, Melon Race and all the other wacky party modes from the previous build were completely gone. Now, GMOD has always been a game with a strong custom content platform, so it didn't take long before modders began rebuilding these modes on the newer builds of the game. There were a couple of Melon Race revival projects I was able to dig up that made their own neat little changes to its formula, like adding their own courses or even power-ups. However, none of these remakes ever managed to relight the spark that the original game mode had, and as new GMOD updates came and went, the Melon Race community eventually fizzled out. The game mode got one final nod from the Gary's Mod team in 2013, over six years after its removal. GMOD's Steam trading cards released with newly commissioned art and among depictions of the fizz gun and the face poser was one final tribute to the Melon Racer game mode that had been cut all those years ago. It was now long discontinued, yet still immortalized alongside some of the game's most iconic imagery. Nowadays, TTT and Sandbox are the only game modes that come prepackaged with GMOD, and while those two on their own are capable of producing thousands of hours of fun even without mods, it's still weird to think about how much more content used to come with the game. And to this day, I believe Melon Race is a story of missed potential. I mean, it's just a simple silly prop racing game mode, but I've probably spent tens of hours of my life playing it at this point, both with friends and on my own. I've streamed it for hours at a time, me and my friends have made our own custom levels for it. Hell, one of them even holds the speedrun world record for the game as of recording this. Although this time I've sunk into a watermelon game from 15 years ago that, honestly, at this point I've probably thought about more than the guy who made it. I wonder if he even remembers it. Gary Newman is a private and rather elusive guy. There's only a few pictures of him online, and his life has changed a lot since he prototyped this silly watermelon game at his parents' house in 2006. He's now the millionaire founder of one of the most successful game dev companies in Europe, he's a father, and he doesn't do many interviews anymore. Needless to say, he's a busy man, and getting in contact with him is not the easiest thing in the world. However, in my time doing YouTube I've come to make a few dark and shady connections, and with a little bit of elbow grease, I managed to cut myself a small portion of Gary's time to ask him about melon race. Now, GMOT has been a very big part of my life since I was young, so of course I was very nervous going into this, but here's what I learned from it. Surprisingly, Gary does indeed remember melon race, pretty well in fact. He also claims to remember working on melon sumo wrestling at one point, which I guess never saw the light of day. I asked him if he used to time himself and whether he remembered his fastest lap, but he replied saying back then he was just happy to make it around the course in one piece. I told him about the resurging community around the game, including the speedruns and the custom maps that my friends have been working on. He seemed a bit surprised, which kind of confirmed my suspicion that I and the rest of the melon race community had given more thought to it than the person who created it ever did. And finally, he told me that now that I'd reminded him of it, he does kind of miss melon racer, and that he even now plans to make a new version of it for his upcoming GMOD successor Sandbox. With that, I thanked him for the thousands of hours of fun GMOD has given me in the community over the years, and I bid him farewell. So there you have it folks, a story of something so simple but with so much depth and potential. Laying dormant in the hearts of many for nearly two decades, only to eventually rise again when we all least expect it. It's kind of beautiful, isn't it? Also, since the build of GMOD that melon race comes with is really insecure and unstable, I reached out on Twitter to find a programmer, and am happy to announce that a faithful port of the original melon race to the latest version of the game is now for the first time in history, available to download as an add-on on the GMOD workshop thanks to the talented archivist Fagardo. The link will be in the description, so go check that out if you want to celebrate this obscure piece of Gary's mod history. Thank you for watching, I hope you enjoyed this video as much as I enjoyed making it, and have a good day. I'm melon racing all day and night, I'm melon racing to my heart's delight. You can see me melon racing every single day. That's Monday, Tuesday, Wednesday, Friday, Saturday, and Sunday. Got this green fruit, make it scoot and make it crawl.