 Thank you so much for that introduction. And thanks very much for having me here today. I'm going to talk to you about a major open source initiative in the apparel sector, the open apparel registry. And I'm going to tell you about how it's fundamentally changing lives and conditions for some of the most vulnerable people in the global garment industry. So what is the trouble with fashion? Before I talk to you through what the open apparel registry is and the technology that it's built on, I'm going to give you full disclosure what is quite a depressing overview of the state of the global garment industry and why it's so desperately in need of fixing. And I do just want to stress that this is not about high fashion. If you wear clothing, even if that's a shirt on top and pajamas on the bottom during COVID, these issues affect you. So let's start with some context on the scale of the industry. Fashion is one of the biggest industries in the world and generates about 2.5 trillion US dollars in global annual revenues. Figures vary, but the Ellen MacArthur Foundation estimates that around 300 million people are employed along the global clothing value chain. And of those people, many of them are women who have children and families to provide for, and they'll often be the main income earners in their family. The rights of those women in the workplace are often limited, and verbal, physical, and sexual abuse are rife. But fashion is also an industry that exhibits enormous income disparity, and two of the top wealthiest people in the world are fashion industry leaders. So on the screen, you'll see Bernard Alnault, who's the chairman and chief exec of the LVMH Empire, which owns multiple luxury brands, including Dior, Fendi, Givenchy, and Louis Vuitton. And the other man on this screen is Agman Sior Feira, who arguably invented fast fashion through the creation of his brand Stara, which is part of what has become the Inditex Group. But at the other end of the scale, thousands of workers are toiling in garment factories around the world, adding to the wealth of bees and other members of the fashion elite. But the workers don't even earn a minimum wage, let alone a living wage. So I'll touch very briefly on wealth disparity and a lack of living wages for garment workers, but unfortunately, these aren't the only issues affecting the industry. Many people tuned in today may well remember this tragic moment in history, which was the collapse of the Rana Plaza building in Dhaka, Bangladesh on the 23rd of April, 2013. And in this accident, over 1,100 people were killed and more than 2,500 were injured. But during the morning of the 23rd of April, many workers in this factory had spotted cracks in the walls of the building and expressed concerned about going into work. But their managers responded to say that if they didn't go into work, they wouldn't just lose their pay for that day, but they'd lose their job. So with little alternative, fearful, but desperate, the majority of workers entered the building under duress, but with horrific consequences. And all this in order to meet the impossibly tight turnarounds imposed on factories by global brands to feed our appetite for fast fashion. But challenges in the fashion industry also are not solely social challenges. As an industry, many stages of production are heavily dependent on highly chemically intensive processes, including dying and finishing treatments. And in a bid to cut corners and save costs, management standards are frequently lax, and this impacts both the health of the workers handling chemicals, but also local ecosystems and waterways. And those waterways are often the very same places where the people who live locally to garment facilities will both wash themselves and source water for cooking and drinking. So how has this been allowed to happen? Supply chains in the fashion industry are incredibly complex and often really quite murky for a number of different reasons. Firstly, because creating an item of clothing isn't as simple as it's often low cost implies. So that made in Vietnam label in your top is only telling one tiny part of the story, which is where the product was finally cut and sewn. So think of all of the stages before that. Where was the cotton grown and by whom? And how did it get from the farm to the dinner and the spinner, which is the stage where the raw material is spun into yarn and then becomes fabric? Who dyed it? Has it been given a special finishing treatment? Who cut the pattern and stitched all the different bits together? Where did the button comes from? And those sparkly embellishments on the chest, how did all of those get fixed to the top? And what about the brand label in the neck and that care label in the side? How did those get there? Did you notice that your top looked really nicely pressed before you bought it? Even that process of ironing probably happened in a different factory as well. So I think you get the idea that producing fashion is and of itself a fairly complex endeavor. And then you throw in buyers at brands who are being set challenging targets to continually secure cheaper prices. And you're left with the global industrialized fashion system where the process of creating one ordinary t-shirt can involve multiple shipments between multiple different countries. Count the steps in producing that one simple t-shirt that I just talked you through and then remind yourself, there's just one product and a simple product in the inventory of brands that are churning out thousands of different products around the world on a weekly basis. So how can better data and open data help? When you're dealing with this many layers, keeping track of the data in your supply chain as seemingly as simple as the names and addresses of your facilities becomes really challenging. And if you don't have a clear sense of exactly where the facilities in your supply chain are, how can you possibly have any sense of the social and environmental conditions at those facilities? And what we found in building the open apparel registry is that at its basic level as name and address data, information and the quality of data in the apparel sector is really poor. So we hear stories of auditors turning up two days in a row at the same facility thinking that they're going to different places. Or in reverse, you have the same social improvement programs being run twice at some facilities and not at all at others. And you can see from the examples on this slide that the data of many global brands is often, quite frankly, a mess. So what is the open apparel registry and how can it help? I'm gonna play a quick 90-second animation in just a couple of minutes but at a basic level, what the open apparel registry is is a neutral open source tool in which we're mapping garment facilities worldwide and we're allocating a unique ID to each facility in the database. So here's that 90-second overview. Okay, so moving smoothly on in the presentation as the animation showed, the OAR is creating one common registry of facility names and addresses in the global apparel system. And it's eliminating issues with matching across multiple inconsistent databases. And what that does in turn is enables in-facility collaboration between organizations that all share connections to the same facilities. These unique ID numbers that are allocated to each facility in the registry do not replace any existing ID schemes, but instead they serve as a central source of truth alongside name and address data. And you can see here the logic with which the IDs are generated. So there's a country ID, the origin date for when the facility first appeared in the open apparel registry, a general ID, and then a check ID at the end. So what were the technical challenges that we faced when it came to building the open apparel registry? Well, it starts with the data because it's always the data. And particularly in the apparel sector due to its global nature, we knew that we were gonna have varying levels of technical exposure and expertise from both the users of the database, but also contributors of the database. So we knew we'd be dependent on low-tech contributors. There were also no industry-wide standards for name and address categorization in the apparel sector. And added to that, data was often extracted from PDF by OCR. And then there were the more standard issues of transliteration inconsistencies, non-structured address sets and international character sets that would need processing. And here's a little bit of maths behind the tool. We had a goal that within the first two years of launching the open apparel registry, we wanted to reach 50,000 facilities in the database. But what does that mean for processing times? Well, if you have an organization that wants to contribute and check 5,000 facilities against the existing database, you're looking at 250 million comparisons, which when you then multiply that up into the time it will take to process that data, it could take up to seven hours, which simply wasn't acceptable. So we needed a shortcut. So what was our solution? Djupe, an open-source Python library for accurate and scalable fuzzy matching record de-duplication and entity resolution. In the interest of time, I'm giving a really brief overview. So I'd really encourage you all to check us out on GitHub if you're interested. But in summary, you can see here that duplicate records almost always share something in common. So if you define those groups of data that share something and compare only the records in that group or a block, then you can dramatically reduce the number of comparisons that need to be made. And if you do the work to define those blocks well, then you can make very few comparisons and still have confidence. And what that means in terms of processing time is that you can dramatically reduce the amount of time that it takes to run data through the system by training that new model, processing thousands of matches then takes less and often significantly less in four minutes. And so in terms of the benefits that the Open Apparel Registry provides, our OARIDs plus that simple reference of facility affiliations enables much more efficient collaboration for any kind of organization in the sector because those organizations which share facility relationships can quickly identify one another to work together on improvements. Data currently set in silos is also able to synchronize using the OARID and connecting through our API enables further more automated data exchange. The other thing I want to mention very briefly is the work that we're doing in partnership with others in the sector to raise awareness of the need for more open data and especially given the challenges that the apparel sector is facing. So we work together with others on something called the Open Data Standard for the apparel sector. And this is a really entry-level introduction for any organization in the apparel sector to help them understand not just what data they need to share but how they need to share it. And we've even gone so far as to create templates for organizations to download to help them share their data in a more practical, usable and reusable format. Just very quickly, I want to share a few examples of how OAR data is being used. So we launched in March of 2019 and we've received really wonderful examples of how data in the Open Apparel Registry is leading to improvements in the lives of some of the most vulnerable people in supply chains who I spoke about at the start of this presentation. So I'm just going to share two quick stories and there's a range of other examples available on our website. But the first I'll share comes from an organization called Clean Clothes Campaign which is a global alliance dedicated to improving working conditions in the garment and sportswear industries. So they use Open Apparel Registry data both in their urgent appeal work where they're responding to concrete violations but also in their research initiatives. OAR data enables trade unions to identify which brands are sourcing from which factories. And in one example, following the dismissal of a union leader, this information was used in combination with data from an initiative in the apparel sector called the Transparency Pledge and it revealed that the brand was also a member of four multi-stakeholder initiatives. So in consultation with the Clean Clothes Campaign, the trade union picked the MSI known for the fastest response times on grievance mechanisms and was able to swiftly resolve the issue. What that looked like in practice, within five days, the union leader was reinstated to have full job including back pay. And without the centralized source of data that is the Open Apparel Registry, we know from Clean Clothes Campaign that resolving these sorts of issues can take months, not days. Katie, you've got about three minutes left. Yeah, great. Okay, so in another example from Business and Human Rights Resource Centre, our data has enabled them to respond to the dismissal of over 1,000 garment workers for striking over the non-payment of benefits in Cambodia. And again, similar to the example we saw from Clean Clothes Campaign, BHRSE was able to swiftly use the OAR to identify brands sourcing from the factories to ask for their response and plan of action. And through pressure from many quarters, including brand interventions, the majority of workers were reinstated. So those were just a couple of examples of how OAR data is being used. And here's what you can do to influence the system. So check us out on GitHub, search the Open Apparel Registry to see which organizations are openly sharing supply chain data. Contact brands, use your voice as a consumer and a purchaser of their products to encourage them to share their supply chain data and educate yourself on the issues. There are so many different resources and in the appendix of this presentation, I've shared some of my top tips. And then I'd also encourage you all to consider how you purchase and reuse clothing. And then more immediately with the Open Apparel Registry, get involved, explore the tool, consider uploading a facility list and you can sign up for OAR news. And I just really encourage you all to keep in touch and follow our growth. We've got lots of exciting things coming up. So we've maybe got a couple of minutes if anyone's got any questions. Katie, thank you so much. That was a really great presentation and we do have a little bit of time. So I'm gonna start with the most popular question which is from Peter. And the question is, have you had much pushback from the industry? I'm really happy to say that because we ran quite an extensive stakeholder consultation exercise prior to launching the Open Apparel Registry, we'd actually secured buy-in for what we were trying to achieve with the registry prior to launch. And so what that means in practice is that we've got a lot of trust within the industry and organizations very early on recognize the benefit that it can bring to all. And our neutral positioning and the fact that all of our data is open sourced is a really important part of securing that trust. Thank you very much. And very quickly, because we're literally a short answer if that's okay with you. But there was an initial question about whether you use blockchain technologies and then a follow-up question which is, have you identified any challenges there that you would like to talk about or about? With blockchain specifically? Yes. It can be a very quick answer. No, we don't use blockchain so we haven't identified any challenges but there are lots of blockchain platforms who want to make use of our IDs.