 Right, everyone. So if there are any further questions, please feel free to enter them into the chat. Otherwise, we can actually, I think move on to our next presentation. And that will be featuring 3 presenters. And so we're going to move over into the open footprint demo of the reference in the implementation. And that's going to be covering how to install and configure how to access how to use. And the plan for 2021, we will have the moderator, which will be Sammy. And then our 2 presenters, which will be taking you through the demo. Are Booby, I like to say Booby, it's Boopender thing. Shala is a program manager at emphasis and is also leading the open footprint UI development project. He's based out of my sore India and Booby leads digital transformation programs for the oil and gas majors. Gert Williams is a account CTO at IBM with his technical leadership and expertise in oil and gas and new engines energies. He has created open hybrid cloud architecture to build sustainability platforms that have enduring impact to the clients reimagine. Now, new normal and Garrett has an open group distinguished it architect certificate in defining architecture and holds a MS degree in electrical engineer from the University of 20 in the Netherlands. So, without further ado, I will turn it to all of you. Sammy, if you want to. Start then I'll close down. Thanks. Alrighty. Perfect. Thanks. Heidi. Appreciate it. And. And Booby, thanks for joining today and we'll key you guys up here. So, and Booby, I think you should have. The ability to share your screen at the time at the appropriate time, but we'll we'll we'll test out the fun of WebEx. Okay. Good. All right. So thanks everybody for joining again. We've got a good discussion. I think today around the reference implementation. We'll walk you through a little bit of an introduction around what is this taught and then actually get quickly over to a demonstration. And then we'll talk about next steps and QA. I'll tee up the conversation today. I mean, I think as we talked about. You know, yesterday, you know, if you go back to sort of, what are we trying to accomplish? And what is it that we're trying to do a really, you know, trying to calculate or, you know, the carbon footprint, we're trying to make that easier. We're trying to share information. We're trying to visualize data. We're trying to report information to stakeholders. Appreciate there might be multiple systems out there. There might be multiple technologies, a whole bunch of spreadsheets. I would imagine that have all this. But as we talked about yesterday, there's, there's a bit of a reference architecture that we've got and an ability to share data. Sorry. Sorry. It's John. I hate to cut in here, but unless you retain presenter, if you move the slides, nobody will see them moving unless you're the presenter. Okay. Oh, okay. I'm sorry. You have to retain present. I will make you present again. But if you move the slides, you'll see them moving on your screen, but nobody else will see them moving unless you're the presenter. Okay. Ah, okay. Perfect. Thanks. Thanks for the clarification, John. Yeah, when you're ready to hand over to Boopy, you hand over then. Okay. But not until that point. Okay. Alrighty. Thanks, John. Appreciate it. Good. Good. Good. Can everybody see the agenda slide now? Yes. Thank you. You guys are like, what the heck is he talking about? Okay. Good. All right. So these are my four graphics from earlier around calculating the carbon footprint and so on and so forth. I'm glad you guys told me that John for interjecting because I think the rest of the story you've been very confusing if you couldn't see my screen. So, excellent. All right. So these are the objectives that we're trying to accomplish. What I want to do is maybe hand this over to now to Gert Willem who walk us through how is this architecture influencing and then let's talk, let's maybe go through a real live example, I think. So Gert Willem, if I can turn it over to yourself. Well, thank you, Sammy. Yeah, absolutely. So, I'm here from harsh is working in the middle viable product team. And what we have done here and that's also the picture that you see on the slide right now is building an architecture for a simple architecture basically to start the MVP. So we started with this within with a simple version of, you know, the architecture that will be on the roadmap later on but we thought, let's start simple and let's start fast in that way. What is important to mention here and before we go into demonstration that the architect is completely on open architecture. So, so it is an open architecture that helps us as the whole community under the open group in the open footprint to co develop for this important sustainability use cases and carbon footprint. And I will go in a minute in the different layers that we have laid down. But it's important to notice that that the architecture is really should be really inviting almost for all the innovation that's that we would like to do within this important community. And to illustrate that on the left hand side you see a couple of concentric circles right and this illustrates just an illustration of what type of users you could have for the open data platform for the for the open footprint data platform. So you could think of, you know, large companies that have to capture their data in a consistent way for for carbon footprint. But also use cases for governing bodies for certifying agencies or maybe other stakeholders there that are going to use the platform to report things see insights from dashboards, etc. So the very important group of stakeholders there as well. And then the outer circle, you see all sorts of other things, like even electrical vehicles, really like you know smaller agents that will make use of this data platform as well even natural persons or households. Why is that important because that gives and provides the context for the architecture. And therefore it's fully scalable to the different scales that the platform needs to work for. On the right hand side to a couple of layers and so really a simplified version of a more complex versions that we have seen before and also probably doing this. The two days and also maybe some other open footprints and meetings that you have attended. I'm looking now at the right hand side where you see green box right open footprint data platform. That's basically the platform that we are working on different layers simplified version again. But what is super important is the layer of standardized API's the standardized API's will expose the functions of the platform to the whole ecosystem of developers users of the open platform. And these API's are, you know, besides their standards, they will also be exposed fire the platform and they provide and realize the functions of the system data services but also other services that will provide you data lineage and all the things that we have been talking about during these two days. And of course there are some ingression services as well to get the data in right. This whole green box is running on what we call a data control pane. So this data control pane is really almost like an, like an think of an, of one control plane to manage and your data, cover your data, segment your data, etc. And security is of course super important as well if you are ending up with a multi tenant platform as well later on, not now and don't get me wrong, not now but later on that's all all the architecture should really envision that. And then of course this this this step needs to run on infrastructure services well think of clouds, think of the cloud hyperscale is that we have where the infrastructure will be completely embedded. So just as an as an as a starting point for the conversation what we are going to show you in a minute the demonstration of, you know, the first middle viable products. So if you can go to the next slide or should I do it myself as Sammy. I don't know if you can switch to the next slide or I don't have a button here. You have control. Thank you. Thank you so much. The objective of today is to show you really the carbon lifecycle of a product. So we took a product and I'll come back into that in a minute, we took a very specific product that we all know. I'm going to show you how that life cycle and to end could be supported by the data platform and how we have been doing that with our demonstration with our MVP with about five of products. And that's the second objective of courses to try to reach right to understand how the capabilities of the current MVP can support let's say this very simple use cases now. But also, you know, what could be an inspiration for the future and the roadmap in the future. So let's go to our story. Thank you. So our story is a very concrete story. We are going to talk about a very simple product that everyone probably knows the destroy that everyone knows it's a bad. So this story is a day in the life of a bet. Of course with a wink here. And think of the bats that you buy at this, you know, large company, where, where you have companies in the world that have, you know, redo it yourself that's right. They are pre produced, but you still have to do work, do some work on it yourself to use screwdrivers planks and put all the bets together at home. So this type of bet we have imagined here. And as you know, there is quite a quite an effort and quite a string of actions that has happened before you have that bet finally in your bedroom and when you can use it. And we have simplified our story here because you know, this is a super complex end to end process but we have simplified it here. And our story starts really at the beginning where the battle really has been produced. And we know that there is a whole story before that for producing let's say the planks, the sheets, the mattresses, everything. But here we simplify the story. There is a company Acme imaginary company Acme producing has produced a bet and the end result is that they have boxes a couple of boxes that will be used. That will, you know, ultimately are the ingredients for this fantastic bet. And what the thing is that so once it has been produced near the global manufacturing side of this Acme company. Those global manufacturing sites normally would have warehouses or real hardware warehouses from where the shipment starts of these components of the bet to the different markets either in Europe, US, Australia, Indonesia. Imagine the whole is a global company. And for that you really need, you know, transportation quite a string of transportation as a matter of fact, to bring the product from the manufacturing site warehouses by using vehicles, going to for example a harbor where the harbor material handles the pieces of the bet into, you know, vessels, the vessels go to a certain area of the world where the goods are unloaded into cars or trains or whatever. You can imagine there is a whole string of transportation to be done there. But we also would like to address you that in the meantime, our main character Mary is going to be very inspired by, you know, a new bet and she is starting to look into catalogs go to websites of Acme. Maybe she is going to do some visits to the store already. This whole thing of inspiring and the cell selling process is of course an important step here as well. We have to consider that if we want to have an end to an picture of the carbon footprint of this, you know, very simple product like a bet, like a bet. And imagine then at a certain good day, when Mary is going to pick up her bet she is decided what bet she wants she would like to have goes to the store, clicks on a couple of things and then she needs to pick up all the ingredients from the distribution area of the store. You probably know how that feels right, but a bit confusing loading your stuff on a small cart and then finally drive the bet to home and fix it. The last aspect that we would like to show here is that, you know, from a totally different angle, for example, you know, customer success managers of of this company, for example, then needs to be able to really look at what is the carbon intensity of this product. So then needs reports dashboards, complete understanding of what the footprint is of this very specific product debate. So in other words, we have created here a really a day in a life probably a bit more than a day but you know, figuratively speaking a day in the life of a bet that shows basically all the aspects of of what it would take to capture all the data the carbon data in a consistent way by making use of the open footprint platform. So let's go to the next slide. Real quick, because we'll see everything in action in a minute. So what you will see is, first of all, as we've mentioned when the story starts when you have this bad acne company has produced a bet. We first have to set up the system, right, we first have to define the organization of acne the different facilities that they have the processes that they use to produce the bands. Also, you know, the scope and the scope of what you are going to account for this will be super important as well everything you will see from the data model that Gommar has shown on the on the first day yesterday will be here as well when it all starts. Can you go to the next slide please. And then it all starts with, you know, if we just dive into, for example, transportation and the different steps in the transportation, how our platform will be able to support the capturing of the of the of the of the greenhouse gas emissions of all the steps that are part of this end to end process as well as something we're going to show. Please go to the next slide. Thank you. And then also what is important here is that as we have been talking about, let's say also other steps like inspiring sell and a digital footprint that this product can have as well. We need to have a dashboard in the future that will really show and capture all the aspects of of of producing things like a bet. So that will be be discussed as well. So first of goods. This is only the theory. Let's go into practice and let's see how this all is done in a live demonstration. So I headed over to you will be. All right, so hi everyone, my name is Boopy program manager in process, and I'll quickly walk you through the screens for the reference UI that we have developed. So as we discussed in yesterday's architecture session as well, this is just a reference UI. So it comes as part of the whole platform bundle that you'll install on your organization infrastructure. So this is the reference point and you're obviously free to develop your own applications as you move forward, as long as the basic data platform and the API is exposed are being utilized. So this is completely open source following the open group practices, the right from the login page that you see right now. It's developed through key clock, which is our open ID based identity provider. So that's the identity provider that we have used. So like a normal UI, you provide your user ID password and you had the sign in button. If you are an authorized user, it will take you to the homepage of the application. So if I move to the next page. Right. So that's the homepage of the application in the interest of time. I'm just showing you quick snapshots and to avoid the typographical errors in the use case that we talked about. So this is the homepage of the application. Very simple UI that we have built to just ensuring that we keep it simple. The bottom tiles that you see here are just informational tiles and the real navigation happens through the top navigation bar. And the way we have categorized these modules is a typical workflow that anybody will follow when they are trying to enter their data and generate the reports out of it. So I'll just quickly tell you about those modules. So the first one is inventory boundary that's where you set up your organization, your organization structure, the boundary data, what are the GHG sources and so on and so forth. Once you do all that configuration, you come to start entering this data, which is through the emission data module. And once you have entered all your emission data, you start reporting out of it. So we have kept very simple reports in this application. And I believe there are already projects that is running around to develop more sophisticated visualizations on top of the same platform. So just to keep simple, we have simple tabular reports built in this application itself, which you can again enhance using whichever visualization tool you use in your organization. The last module that you see is admin module where we can enter the reference data. So all the dropdown list or lookups that we have used in this application, you can manage all that data through admin. All right, I'll move forward. So the use case that we have picked up, which Gert just explained right now, a day in a life of a bed. So let's say I am the Acme company organization admin who's actually set up this tool for the first time. So normally I'll download the platform. I'll put it into my organization infrastructure. The platform gives me this reference UI. I launched the UI. The first thing I have to do is set up my organization structure. Why? Because that's how you will actually eventually report your data as well. Let's say you want to report at an organization level or sub organization level or a particular facility. So and it could be it could be simpler organization. It could be much more complex organization with a lot of hierarchy levels in your organization. So the tool is flexible enough to cater to those levels and even the simplest one. So in this example that you see Acme organization, it's a corporate level, which is the top most level. And the industry sector, it belongs to his pulp and paper. It's Acme woodenworks. And then we can add a registration number, a dance number or a registration number for your organization, which ultimately you will actually use in your emission report. When you are publicly publishing your reports, you include some basic details including your registration number and so on and so forth. Your organization address, your contact details, all key people that you want to include. So this is your basic corporate or top most level setup of the organization. Then we move on to the next levels of your organization starting with sub organization. So let's say in our example, the Acme company has one unit for manufacturing and another unit for distribution or transporting the actual bid to its end user or the customer. So I've added Acme manufacturer as a sub organization. It's a subsidiary again, same industry. So you have a flexibility of adding the industry at the at the sub organization level as well. And then similar fields, your address and contact details for the sub organization. Similarly, a distributor as another sub organization here you can see the sector is actually service or an office based organization, which is just a distribution center for Acme company. So that's how you will set up your subsidiaries and your corporate level. Then comes the business area. So in which regional area you are actually doing your business. If you want to report your emissions based on that, you can form that structure here. So you can see we have Asia Pacific as one of the region and Europe has another business area. So after that we have the facility. So if you want to report your data and you want to track at the facility level your actual offices, you can do that as well. You can set up your facilities. So in our use case we have Acme China and Acme Holland. China is the actual manufacturing unit and Holland is where the distribution happens. So that's how you'll completely form your organization structure before you start entering the data. The next level of configuration that you do is the boundary setup, which is kind of the heart of the application where you define the GHG sources. At the organization level, sub-organization level or at the facility level. So these are the steps involved in the boundary setup, which is organization boundary, GHG sources, facility level, GHG sources and the sector attributes. So as you saw during the organization setup, we can choose a sector for your organization and sub-organization. So similarly catering to different sectors. We have this sector attribute because every industry will have some very specific way in which they report the data or because of the manufacturing processes and so on and so forth. There will always be some sector specific attributes, which can be included here. And that's where the flexibility of the platform comes into picture. So step number one, organization boundary. I've selected Acme China financial control. Yes, operational control as yes. Similarly for Holland, we provide the equity share between your different sub-organizations. And then you move on to add the GHG sources. So in this particular example, as I said, Acme China is where the manufacturing is happening. So we have Scope 1 emission, the GHG category as the emissions imported energy. So what electricity you are consuming from that unit, that's as one of the GHG sources. Similarly on the distribution center for Acme, we have the electricity consumption in there as well. So similarly you can add the other facility level GHG sources. Then comes the sector attributes, the flexibility that I was talking about that you can define your own parameters. So for the group transportation, I've added these two parameters that customer commute are fictional. Customer Mary actually travels or takes her car and travels to the distribution center. And from there, she normally tries to interact with the salesperson or tries to choose her bed. And then finally that bed gets transported using the company transport. So those are sector specific attributes which can be added. Similarly, these can be added for shipping industry, for cement industry and so on and so forth. So then comes the entry of the emissions data, that's our emission data module. So till now we have seen how I set up my organization boundary. Then how do I define my GHG sources at facility and sub-organization level. So after doing all that, I come and start entering the data at organization level, sub-organization level and so on and so forth. So in our example, electricity consumption is one of the GHG source. So we are generating or we are entering data for January to March, what was the amount of energy consumed and what was the type of the material. So whether it's CO2, NO2 and so on and so forth. What was the method type, whether you were actually able to measure this or it's a calculated value like we just heard about the calculation engine part. That's what will drive that kind of calculation. And you put the emission data and the unit of measure. So the number of GHG sources you have these panels will repeat for that you will enter the data. And this is again a reference UI if you want to import from your existing databases or something that obviously is extensible architecture that we have in place. If you don't want to do the data entry from this UI or you want to build your own UI, the architecture is flexible enough to support all that. Okay, so that's on the emissions data entry. So once you've added all your data, we saw for one unit and this is for the seconds of organization that we have. So similar calculation again for the electricity consumption group, Jan, March quarter, what is my overall calculated or the emissions quantity. So that's for the ECME distributors. Moving on to the simple report that we were talking about including the sector attributes. So first part in the emissions data was the GHG sources and the flexibility which I was talking about that you can enter parameters specific to your industry. So for ECME distributors in our example, we have the customer compute and the company transport as the specific parameters for which you can enter the unit of measure and value. So that's how you report or enter the data or the sector specific attributes. Moving on to the simple reports which I talked about. So you can create reports for a particular period. Let's say the one particular quarter or start date or end date based on how frequently you report this data. So ideally whatever data you have entered through the platform, you should be able to generate a report out of it. That's the idea. And as I said, we want to keep it simple. You can enter as create as many simple reports here and for this particular quarter, this is a sample report. So for the ECME example that we have for ECME China facility, I have this much emissions and for ECME Holland, these are the calculations or the emissions. So this is obviously simple tabular report, but you can create your dashboards. As I said, we are already working on the visualization project. All this data can be visualized in future. So you can have as many charts or as many dashboards like what you see right now. All right, I think that's about it from my side. So over to you Gert and Sammy. And Boopy, thank you for that. I think it's sort of a useful representation. And I think a couple of things that I want to kind of leave with as we get closer towards the end and also potentially open it up for some questions as well. And I see some questions already in the chat window here. I mean, I think so two things. You know, if you think about the story that Gert Willem, you know, described, right, everything from sort of that manufacturing of that bed to the distribution to the transport, you know, to the customer buying, et cetera. I mean, if you think about what we're trying to do once again to sort of represent that emissions across the supply chain, right? Look at it across different organizations, different umbrellas, different lenses and so on and so forth. In some cases, we may need to be able to share that information across organizations in our simplistic example, everything was sort of owned by ACME. In reality, that's probably not likely the case or might be a shipping company, there might be a supply chain company that's that's actually making the beds and so on and so forth. You can imagine that this is extended supply chain that are then doing their own calculations or their own emissions and being able to share that information across so that you have a complete information or complete representation of your impacts. And then finally to be able to visualize that whether it's by the company or by the customer or wherever it might be. Okay, a couple of key things I want to kind of point out and I want to emphasize once again. One is this concept of open architecture, right? It's a reference architecture that's available for use now. And as Boopy mentioned, there are folks that might type that in or calculate the emissions as we saw from William and Javier earlier. You might already have existing systems like your SAP or your SPHERA systems or whatever it might be that are calculating emissions, importing that data in. I see a question from Raymond on the Q&A around potential uses of blockchain, absolutely, right? All those different channels of getting data into the system are all feasible. But at the end of the day, we have a common reference architecture and a common data model that we're all working so that as different organizations, as different ecosystems, partners and so on and so forth and as different technology providers bring their technology. We've got a common way of sharing and communicating and storing and processing that information and equally so visualizing it. So something to consider as we go through this, keep in mind, this is MVP, so deliberately so we wanted to start somewhere. I'm sure there's lots of things that we can and should be doing equally. There's probably some areas that vendors and software partners and technology providers have already are in the space and we just need to align into the open architecture. Okay. Carol, Bill, anything I'm missing on this diagram that we wanted to cover? No, you made a very good summary, I believe, Sammy. It is still, you know, I hope this will be a bit of an inspiration of what can be done with the platform and it is really early stage. But you have to start somewhere, right? Yes. Yeah, exactly. And I think, you know, the point being is, you know, once again, I kind of go back to these green boxes. I see being able to represent those emissions, you know, whether that's being inputted, whether that's being imported, whether that's being integrated from systems and blockchains and so on so forth. And then being able to share the other important thing about the reference architecture and part of what we're showing is ideally this reference architecture exists in multiple, you know, instances, multiple organizations and the ability to share information via through APIs and some of that reference architecture stuff that we've looked at yesterday and today makes it easier so that if you're the transport company, you might be quantifying your scope on emissions because of the ships and the boats. You're then able to communicate that to, you know, your customers and so on and so forth and down the road and down the road. I know Gommar yesterday talked about upstream versus downstream emissions, same kind of concept that we've got the ability to share that information. Okay. Good. All right. A couple of more slides and then I'll open it up for some questions. What's next for us? I mean, I think we're going to continue to validate the reference implementation against test data sets. We want to make sure that it's fit for purpose, that it accurately represents the footprint. Once again, there's organizations that have been tracking this, but now how do we make sure that it's a consistent way to do that. We definitely want to continue to look at the calculation engine. So embed that as William and Javier talked about earlier today. How do we then fit that into the, into this architecture that we've seen in terms of the platform. Or alternatively, if organizations are really going to be leveraging their own solutions, whether they built it or bought it, you know, to be able to facilitate that in. And then finally last but not least, but really to look at that sort of that sharing of information through APIs and so on and so forth. So, so ideally that's, that's, that's sort of what's ahead of ahead of us in the journey. We're still in that MVP state. So we still need to actually finish out this MVP and get that published so that people can download it, install it, play with it and touch it and so on and so forth. But anyways, just maybe a good starting point. Okay. Good. I think that I do want to just kind of give a couple of credits because it's what you see, although we will be covered that in a very short period of time. In 15 minutes it represents a lot of hard work by by emphasis and Wipro and IBM and Shell who've contributed significantly to the development of that. Once again, it's it's it's a starting point you've got to start somewhere. I'm sure there's probably a thousand things that we can add to it. And I know every time I look at it I'm like, oh wait, what about this what about this and we'll continue to evolve and grow that. But the key thing is that we've got a common, you know, taxonomy common rough data model and so on and so forth. Okay. Good. Alright, I think that's pretty much all I had for for today I know we've got a fair amount of time still left in the agenda we've got about 15 minutes that we wanted to leave for any questions or comments. Any questions outstanding semi yes. Yes, yeah, perfect. Yeah, I was just kind of scrolling through here. Perfect. Yes. Excellent. Jared Willem, do you want to maybe take the question around the the architecture one that I see from mono and then I'll maybe cover some of the other ones. Let me read it out maybe that might be easier because I was looking through the. Yeah, let me. Yeah, let me read it out so so the question from mono is how would this architecture prevent duplicate reporting. Example who should report example is shipper or receiver should report. Yeah. No. So that that is also you know the architecture itself can support it but I think it will be important to define the processes here as well the boundaries of where you can, where you will report or will be very important. The data model includes those boundaries. The duplicates that can happen if you're receiving the product or if you're producing the product is is supported by the data model but you have to make sure that the desperate that you're creating on top of the data model are really taking care of those boundaries as well. I think the, the concept and the concept of the different scopes and the concept of the upstream and downstream model that that I'm referring to also what Homer was talking about yesterday facilitates that the implementation that we have right now is a first implementation of the data model, but there is work to be done to, to support that further that's that's for sure. So I think it's a very good question. Yeah. Yeah. I think that spot on your will admit, I mean if you think about sort of the reporting in some ways, you may consider duplicate reporting but it's really more accurately representing your, your, your, your impacts your footprint from an organizational perspective so you might have a logistics company a shipper over in our in our example here. And they're generating emissions right there ships have diesel and they're, you know, burning, and that's generating emissions and that's part of their scope one emissions. Equally that might be attributed to scope three scope two or scope three emissions for for other organizations so, you know, things to consider that that that in some ways it's it may be duplicative but in many ways it's representative of the entire scope and that can also represent for example things like when you get into the, the emissions that are associated to your, you know, to the products that you could, you know, or goods and services that you that you're, you know, that you're providing or selling so to speak. So hopefully my answer to your question. Maybe a separate question I think that I see here. Hopefully, are we going to have a master data validation and automation for scope one two three based on a mission type from operation source and the scope will be auto, auto determined. I'll maybe I'll take a first pass to that one good Willam and happy to get your thoughts and Johan feel free to chime in as well. I will say, eventually yes. I don't necessarily know if everybody has their firm handle on especially the scope threes I think ones and twos are probably a little bit probably more easier to find. But I think once you get into scope three that might be a little bit tricky to start to auto determine that isn't that doesn't say that we can't start to be able to track what our scope one two and three within the system and to be able to validate that. Yeah, I think that's definitely an achievable thing. You know, whether that's the highest priority for an organization versus just the sharing of information. That's that's probably something for us as a community to decide. Yeah, you're correct. I'm not to add to that. Sammy you spoke on. Good. Good. And then last but just make sure I don't miss any questions here. I think Raymond, I got, I got yours already. And Alice just to come back to your question, which is I think sort of a build up from from from the earlier presentation from from William around the calculation engine. So just to talk through that and I think it's a couple of flavors. So first of all, the methodologies that we put into these calculations engines are generally certified they're either ISO standards or the regulatory driven. So those are the engines that those are the calculations that you would embed and then ingrained embed into the calculation engines or into whatever tool that you have. The calculation engine itself often is assured by a third party, you know, auditor verifier than those are those are certified people that do that. We'll have to go back and investigate to see if there's the calculation engines actually get officially certified by a standard or that's through the verification process. I myself I'm not as familiar, but it's I think it's a good, it's a good takeaway for us to consider. Because at the end of the day, we want to make sure that people have comfort that the calculations that are being done or correct and a right and the methodologies are being used. I think we can definitely ensure that the calculations and the factors that are being used in the open source are representative of of the, you know, the standard calculations, the endorse calculations, the regulatory ones, whether that be EPA or, you know, you coa or, you know, I peak or any of those different areas. I think we'll also find that there's a lot of different interpretations of those regulations. And so, and oftentimes, even with carbon, for example, you might have multiple multiple methodologies that are both equally applicable as well. So there's there's some complexity to it, but it's a good point that's that's taken. But also important over here that we, of course, using metadata keep track of what calculates we're using how we use this calculation people can always go back to later say okay. This calculates was used this release and this was used for the whole metadata stories also important to support for future reference. And just to build on that to you as you think about it is sparked an idea in my head as well or comment to my head is also some of these methodologies that are coming we've we've now seen advances in satellite imagery for methane data. The regulators themselves and the verifiers themselves are still catching up to those as well. So how sure they how certain are they, how do they align with the regulations. I think there was also a question on blockchain by Raymond. Yeah, we already responded to that. Maybe I get a general statement about blocks and people often asked that. Over time, we will add blockchain and also say we mentioned that we will add blockchain to the mix. As I said yesterday, at the moment, we're still crawling. And I see blocks in being running. So it will be important when you want to do a proof or did you really say that the values you put in are the real values. So over time, we'll be at blockchain to the to the platform. Yes, we clearly will. It will not happen to me today. No, we will not happen to me today for the reason just gave other questions from the group. And once they can try to miss anything, I think, you know, AI. I think just to just to build on that Raymond, I think, you know, equally so I think that's that's sort of in the run phase of versus the crawl. Equally, I think, you know, I think there there are. Once again, I think technologies exist out there for, for. You know, applying artificial intelligence into some of this some of these may be not as proprietary or some of them may be proprietary to specific vendors that, you know, feed off the data from our platform. Alternatively, as more open source methodologies come into place, that could be something that we consider into the AI as well. I mean, equally, I think it's important to understand what are we using the AI for? I mean, once again, I go back to the key purpose of what we're trying to do is make sure we can effectively report and share information, especially across boundaries. Some organizations may may like to implement some of that AI at a much more operational level as well. So we'll have to assess that, but I think it's a good point as well. To see that and also in the AI space is also, you know, is it really for prevention or is it to understand where we're seeing gaps deficiencies and potential. You know, challenges to meeting very various carbon targets and so on so forth. So it's good. It's a good point to bring in. Maybe to add to that, build on that. We see, yeah, when we look at our artists we showed yesterday, the application space is not really part of the open footprint. It's really where people can shine, can differentiate, and again, the proprietary solutions. AI, of course, is very much part of that space. So AI will exploit the data in our open footprint environment for the AI, for the API layer. And you also look at AI where companies want to differentiate, want to do something special, and they have a lot of the AI, not everything. They can also be AI in the data platform layer, but a lot of AI, when we see learning, we see these other things. They really fall under that great piece where we say there's outer scope of footprint work. That's what people want to differentiate, want to shine, want to have their own proprietary solutions. Yeah, good. All right. Anything else, I think. Any other last questions? If not. So, Gerb Willem, Boopie, thank you so much. And Heidi, if I can turn it back over to you. Absolutely. And thank you all. Thank you, Sammy. Thank you, Boopie. Thank you. Got well, excellent, excellent session and overview of the demo.