Advancing Land Management with Parcel Fabric Technology with Amir Bar-Maor | ESRI

So my name is Amir Bamore. Uh I work for Ezri for the last 17 years and I know you're getting a lot of information in those presentations. So I'll try to be brief. Uh the parcel fra is a framework for managing cadustle data parcels managing it and distributing it in using web services in a multi-user or a single user environment using the RGIs software. In the past, we've seen a lot of Cadillac systems that use the old paradigm where you have a desktop and you work against files or maybe you're connecting to some DBMS to a database directly. Now, we're shifting in the past decade into a web service environment where the data is being shared through web services can be shared with multiple types of clients. Your phone, your desktop, web browser, and we also talk sometimes in the context of system of systems. your data, your cadustle data is also shared with other government agencies. They also want to make sure that they use the most current data when they make decisions and include your data and that's a paradigm of system of systems. I joined Ezra in the right time uh during the Arkmap times but this is our fourth generation of software to solve cadastel problems. Unlike Arc Map which was specific to the desktop product, now we took it into the enterprise where we use web services from all type of clients and every generation of course technology changed, requirements change, caters to those new requirements, new expectations. When Arc Map was designed and implemented, we didn't have the internet yet. That just shows how much things have changed. So I'll try to make just a few points across. There's a lot of data. uh so we don't overload you with too much data. So with a parcel fabric data is defendable. We know every feature a point a line a boundary a parcel what created it. We keep track in lm it's called special source sometimes um or the source but we also know each information what caused it to become historic to become uh retired. So here's a small example. I can select any parcel, a road in this case, and I can easily navigate to the source that created it. And that will link me to additional information. So I can defend what created it. In this case, another parcel that was a result of a merge operation of two parcels. And you can see that the record also tracks how many parcels it created and how many it retired. And when we merge and split parcels, we create historic parcels automatically. So you can see that this parcel was retired and we know what retired it. The next point is called parcel lineage. Like a family tree, we can trace that lineage in parcels as well. And this is important for many of our customers. And it tells them what created it. So if you want to see that in action, I'll first perform a record-driven workflow. I'll create a new record. That's the new transaction that is going to happen and that's a unique name for that transaction. So usually it involves some dates. Here you can see German data. I'm using some German translated coded domains. And while I'm editing today, it might have been recorded legally a few days ago. So there's the legal date. Now it's the active record. It tracks everything I do. So it knows that when I'm going to do a split of this parcel in this case into five proportional areas, it knows that all the new parcels that are going to be created were created by this active record. And of course once I created the parcels, I might assign them a new unique identifier which is also common in all cadustle systems. And we have tools to also make that more efficient. Now that's one way to look at it. But where's the historic parcel and the historic boundaries? In some cases, they are still there. And we also have the functionality to just switch off everything and just see the active record. So that's also very useful when you bring more data uh that overlays the existing data for example. Now I can also create and view that in a parcel lineage view what we just did. So we can see here that I chose a parcel and now I can see that the active record we created created this new parcels. So this help people do chain of title and other processes and to see where the parcel uh was created from. And of course this is a link chart. You can interact with it and the map as well. The second thing that is important to our customers is topological integrity. We think of points as one point on the ground. We want to have only one point in the system that represents it. And when that point moves, if you update the coordinates, we want all the features that connect to that point to move and maintain the topological integrity. So, uh you can think about points as the glue and sometimes you might have different parcel types, buildings and parcels connected to the same point or easements and ownership. Here we see how a simple move will also keep the linear linearity of the road edge the road road frontage. So when you move a point um this is a spe special parcel behavior that it maintains the colinearity of the road. It doesn't become bent. It remains straight and that's also a common process uh for some of the customers. When we designed the system, it was important for us to support all types of cadas systems. There's different ways to legally describe length. It could be based on coordinates. It could be based on measurements online, meets and bounds. Um, it could be using fitforpurpose methodology of data that is rapidly collected from other sensors, from drones or phones. And it could be evid submissions from CA data. So, it doesn't matter where the data comes from, we want to maintain it. in the system. And here's another example. Um I'm using here all the data in Denmark, so a few million parcels, but there's a CSV file that came from a GNSS receiver, and we need to process it. So the first thing is to specify the text file, specify the special reference that it is coming in, the accuracy, and I'm going to import those as fixed points. And here's a small Python script. It will create a point layer and it will also zoom to the right area. The data could have come from a lend XML file from an alis file. Doesn't matter the format. We can always uh write some script that processes it. And now that we have the point and this is of course exaggerated, we can symbolize it to see it a bit better for the boundaries that need to get updated. And how do we now apply those new boundaries? Well, again using a partial geoprocessing tool. So here we have the import parel fabric points tool and many organization that use coordin. So I can specify the points that will be imported. Uh I can specify in this case proximity because there's no unique identifier to tie between to match the incoming points and the existing points and everything moves to the new location. And this can also help if you have multiple organizations that need to collaborate and make sure that different data sets coincide with each other. So we have also those use cases in some jurisdictions. And why adopt a new technology? That's a big headache and a big investment. So it's efficiency to do more and to do better with less people. And there's a lot of tools in our system that allow you to easily migrate and easily adopt the system. Um, there's of course APIs, but we want users to use the APIs as a last resort. We actually our attempt is to have people just use the software as it is and if something's missing, let us know. We'll put it in the core software so they can keep update uh their system and not work on a system that's 20 years old. Here's one efficiency thing we did in the last release that we are happy about. And this one lets people import a legal document. In this case, it's a USD that contains measurements and we automatically OCR it in RGS Pro, identify where we have the measurements and create features out of those. And we keep the human in the loop. So I can compare the source document to the extracted text to the measurements that was were extracted. And if I'm happy and the misclo is small enough, I can just import it to the map and my working done. And this is a process that is of course very labor intensive and use manual data entry. So this is a big hit now in the US. Another thing we wanted to do is lower the learning curve. If you see some of the cadustle systems, they are a disaster to learn. Sorry, we wanted to make it easier. Why are you laughing? So um how do we let a new user uh that came to the system be efficient on the first day of the job? So one framework is called tasks and tasks are fully configurable so much that I use German. I cannot read it but I it's Google translate so I'm sorry if the translation is bad but here we create the new record in this framework. It tells me what I need to do. It gives me links to help documentations. It will also verify that I don't miss anything I need to do in this step before I proceed to the next step. So that's another capability. And now it tells me search for your work area. I happen to be in the correct location. So I can just follow the instruction. Select your parent parcels. I select them. I'm now in the merge tool. I can follow the instruction to do what I need to do. Provide a new name. Press finish. Done. So I don't need to know where the tools are in the toolbars. I don't It gives me the right tool, the right time. And uh I can become more efficient. So this is one example of how we can become efficient without any writing any code. This is zero code in there. So another thing that that's more on the IT side that we are happy about we can deploy it on a single user that's just RGS pro that's it or you can do it in the enterprise now you have a portal you have user management you know who's entering the system you have multi-user editing with versioning many more capabilities but we found that there's a middle sector that was not satisfied and they require a SAS solution SAS stands for software as a service how can And I put this software on the cloud and we do have a cloud. It's called RJS online. So the new deployment type that will be released in the first quarter of 26 is the RJS online deployment. Basically have the parcel fabric on RGS online. This can work very well for developing countries that struggle on the IT side to stand up a DBMS and a DBA and so on, but also for those smaller jurisdictions, maybe a small city u and so on that do want to move forward and use web services, do want to access the data from the web, do want to have a web map that shows the data at any given moment in time. And just to give you a sense how this looks like from a user perspective, it's exactly the same. I'm using RGS Pro here using data from Ghana Acra but uh it's coming from the cloud. I don't know where it's hosted. I am a named user. I'm still authenticated to do edits with this data and I can perform exactly the same workflows or others that you've seen before against this data. So it simplifies the deployment because all I need to do is take my data and upload it to the RJS online and then it spins up the services and you can continue to work in pro or if you want to work in a web browser work in the web browser so you choose the right tool uh for the right purpose we call it fit for purpose right so that's part of that this is a misconception because some people think because we are American company that it's designed for the US market and that's uh not correct actually the core technology that was implemented in arc mapap started in Australia so nothing to do with the US we of course took it improved learned from the mistakes with the new generation and you can see we you have an implementation in every continent except one place that I hope we never have to implement which is Antarctica has no caduster it's shared between all nations right so uh I never want to implement anything in Antarctica but all other continents there's implementations in production today and another thing that is important for CAD systems are is the quality it's a system of record we want to make sure that the data as a minimum can be evaluated so we know the special accuracy we know whether we have problems topological attributes and so on and these quality rules are very different from one organization to the other so everything needs to be configurable We use a few engine topology rules, attribute rules. It's a new framework, not new anymore, but pretty upcoming. We and we have dedicated tools to find kadasal issues and also list square engine. We use dinojust from geoscience Australia. It's a robust list engine. Some might argue better than the move three, maybe not. Who knows? But again, LSA is like a religion, so we're not going to get into that. Here's a tool that lets users quickly find gaps and overlaps. a common issues with parcels um of different types. So this is uses the GPU to quickly find gaps and overlaps in every scale. You can immediately see it and you can zoom to your problem area. In this case green is gap and yellow in this case is an overlap. So I think so where you can configure it and people use that we can also automate this process. And we're almost getting to the last point. So it's based on international standard when we implemented the parcel fabric the lead administration domain model LAM was already out there. So we made sure that our physical implementation of the of the conceptual lm uh was in compliance and there's other standards out there that this information model also complies with. One is the kadensdi from the federal government in the US. Another one is the Canadian information model and many others. And the reason is it's in core based on LM. So it makes sense that it can comply with other standards and people just extend the information model to meet their demands. So here's data uh from a place called the Netherlands uh not far from where I live. So here we can see some attributes in Dutch and we want to use them in our extended information model. Well, how difficult can it be? And this can be any day. So, this could be also fields in German. So, I can just right click, go to the field design view, copy and simply paste the fields that I want to take. So, um this is how you can extend the information model and it's true not only for fields, you can also do it for domains, what we code, it's called code lists in some places. And that guarantees that you can easily extend information model to your business needs. So here we're using LM terminology for this data. But this is how simple it is. So if you bring me some German data, it will take me 10 minutes to extend it partials maybe the points another few minutes. But it's really data migration becomes really easy. So I do maybe I have a bit more time. I'm not sure but uh just kind of the main points I wanted to bring across with a parcel fabric that we made it very easy to adopt and fast to deploy. So don't trust what you've seen. If you want to take your data, contact us. We'll show you how easy it is to put in the technology and then we want to know if you can do everything you need to do with this technology out of the box. So that's makes it simple. You don't need to hire expensive developers to do that. um efficient, scalable, configurable. We have it deployed with agencies that have a few tens of thousands of parcels, but also those that have more than 20 million. So, it's scalable uh and that's important for us. We want to build built-in quality is part of the story. So, built-in quality rules. It's modern using serviceoriented architecture which has a lot of um advantages when you start integrating with other business systems and all cadustle systems always integrate with other system document management land registration etc etc etc. So you always want to have good integration with other systems. Parcel lineage we've seen it works anywhere client-wise or cadustle systemwise and you can deploy it in different areas. And just kind of to uh there's a community of many thousands but few other demos. Here's a DWG. We also can bring lend XML. Uh maybe if you use FME you can also bring alis data or your own data set. But here's CAD data. uh and a few layers and by copying it to the active record we create a seeds. It's also good for QA and then we can run some more tools. In this case, we planerize and we want to have some measurements. So, we update the KOGO values uh by inversing the geometries which are still in ground before we then build the parcels and align them to the surroundings. So very efficient tools to streamline workflows to do the QA in that uh process and here we create the links and we simply align and we took care of business. So you see in a minute or two we can do really big workflows and all of those workflows some of can be automated right if you know the layers you can automate them completely. Here's an example of a web map that shows Dutch caduster data. Thank you, Dutch Cadustaster. And uh I'm looking at the web viewer. But if I now go to my enterprise system, I can perform that same merge we saw before in a named version. And then I can if it passes QA, maybe I don't have permissions to push it out. My boss can push it out and then everybody can see the current data immediately reflected. And this is part of the power of services. You don't need to move data around ETL anymore. You just decide who has access to the data and what level of access do they have. Maybe they can only edit, maybe they can do the edits. It's and you can be in the field and have access to the current data. So that's also an advantage. Uh 3D also important for our clients. Uh so we also working on the third dimension. In this case, it's a condominium units and tools to support it. And this is also used a lot for massive valuation of properties which determines the tax value that you pay. And this is what drives a lot of the American caduster uh fiscal caduster. This is more for the countries that need to have a title map, a single parcel that has a dynamic table that shows the coordinates and simple tool and a dynamic layout that spits out the parcel with a sequence of the lines and points that you can put in the layout and easily automate. So this is again uh a layout that pulls data of the owners and the region and so on automatically. And uh this was just a few points to make.