Latest Contributions by TomDeWitte

  By Tom DeWitte & Tom Coolidge Transporting natural gas to homes and businesses can result in deadly consequences when the pipe network fails. Historical instances of when the pipe network has failed has resulted in governmental entities around the world to create and enforce regulations on the natural gas industry. These regulations are intended to improve the safety and reliability of natural gas pipe networks. Complying with these governmental regulations has resulted in an industrywide culture of safety, procedures, and standards. Industry standards are foundational to helping natural gas organizations to establish consistent procedures and maintain a culture of safety. These standards are often initiated by natural gas industry organizations such as the American Gas Association (AGA), or industry research organizations such as GTI (historically known as the Gas Technology Institute). The efforts of these collaborative industry organizations can result in new standards managed by engineering organizations such as the American Society of Testing and Materials (ASTM). Natural Gas industry engineers are regularly attending meetings, webinars, and training sessions to stay current on engineering and industry standards. How do IT and GIS professionals know that their projects and efforts are incorporating these same standards, and procedures? A Gas Industry Specific Data Model Adopting a gas industry specific data model is an easy solution to this challenge. Starting a GIS or IT project with a gas industry specific data model, lays a foundation for a project to have adherence to the numerous regulations and standards of this industry. Not any gas industry specific data model will do the job. In a world of ever-changing regulations and ever evolving industry standards, a gas industry specific data model needs to be regularly updated. A data model published before 2010 would be a poor choice to build a project upon in 2025. Such a data model would be missing the ASTM F2897 barcode standard. It would be missing changes to the US Federal annual reporting forms. It would also be missing the moderate consequence area requirement for pipelines. A desired gas industry data model is one that is maintained. One that has the financial backing and community input to stay current with these never-ending changes. Such a data model is the Utility and Pipeline Data Model provided by Esri. Utility and Pipeline Data Model The Utility and Pipeline Data Model, UPDM is a gas industry specific data model that was first published in 2013. Its legacy goes back even further to 2009 with its predecessor, the ArcGIS Gas Data Model. Since 2013, UPDM has had updated releases in 2014, 2015, 2016, 2017, 2018, 2019, 2021, 2023, and 2024. Each release contains updates based on changes to regulations, standards, and ArcGIS technology. Esri provides the financial backing to support these updates. Gas customers across the globe who have already implemented UPDM, provide the feedback to ensure this data model is meeting the industry’s needs. Implementing a gas industry data model, such as UPDM, also helps your organization to reduce project implementation time and reduce project costs. ASTM F2897 The ASTM F2897 barcode standard was originally approved in 2011 by the American Society for Testing and Materials (ASTM) organization. Since then, it has been updated several times. The latest update was published in November of 2023. This barcode standard is required in the United States to be printed on every plastic pipe segment and component. US Federal regulation 192.1007 is often referred to as the Distribution Integrity regulation. Section 5 of this regulation requires all gas distribution organizations too: Provide for the capture and retention of data on any new pipeline installed. The data must include, at a minimum, the location where the new pipeline is installed and the material of which it is constructed. UPDM has this standard built into its picklists for plastic pipe and plastic components. Selecting a plastic pipe manufacturer, material, diameter, and wall thickness in UPDM is automatic adherence to this industry standard. US DOT Annual Report for Gas Distribution Every natural gas distribution organization in the United States is required to submit US DOT form F 7100.1-1 by March 15th each calendar year.   The effort of filling out this form, only requires of few hours of time. Officially the U.S. DOT Pipeline and Hazardous Materials Safety Administration (PHMSA) estimates the time to be 16 hours. The effort to gather and summarize the miles of pipe by material, size, decade of installation and the number of services by material, size, and decade of installation, as well other information can take several months. UPDM has been shown to significantly decrease the time to gather and summarize pipe asset data. UPDM accomplishes this time savings by first leveraging the geospatial representation of the pipes. ArcGIS automatically calculates the length of pipe for each unique pipe segment. Second, UPDM embeds the US DOT generalized material type into the AssetType data field on those same pipe records. This eliminates the need to translate a company’s pipe material listings into the US DOT pipe material categories. Tabulation of total miles of main categorized by US DOT material classification is a simple summarization of all installed distribution pipe (AssetGroup = Distribution Pipe) by generalized material (AssetType ). US DOT Annual Report for Gas Transmission Gas pipeline and gas gathering organizations are required by US federal regulation CFR 42 Part 191 to submit the US DOT Annual Report for Gas Transmission and Gathering Pipeline Systems on March 15th. Form, PHMSA F 7100.2-1 is a larger task to complete than is gas distribution peer. PHMSA estimates 54 hours to complete this form. To reduce the time required to gather and summarize this information, UPDM integrates many of the names and categories used in this report. Part A, section 5 of the US DOT for Gas Transmission and Gathering asks for a separate report filing for each unique type of commodity flowing through the pipeline. To simplify this division and summarization of pipe, UPDM embeds the same categories of type of gas into its commodity type listing. Part D of the report asks for pipelines summarized by material, and to differentiate between onshore and offshore. The RegulatoryType data field on all pipe records encodes this differentiation between onshore transmission, offshore transmission, onshore gathering and offshore gathering. The AssetType valid value picklist for transmission pipe and gathering pipe align with the federal reporting material classifications. A quick run of the Summary Statistics tool can provide information needed to complete this portion of the US DOT report. These two examples are just a few of many aspects of UPDM designed to align with these US DOT reporting requirements for pipelines. Leak Survey Compliance The alignment of UPDM to federal regulations extends beyond reporting. It also includes compliance activities, such as leak survey. The leak survey areas have types, that are based on the many regulatory types of leakage surveys. Similarly, leakage reports are aligned with federal regulations and reporting. Classifications such as leak cause type are based on regulatory classifications. UPDM Summary The natural gas industry is highly regulated with many industry standards, reporting requirements and compliance requirements. Building your data management systems for asset system of record and compliance from a data model with these regulations and standards embedded, reduces the cost for IT to deploy and maintain these critical data repositories. Each year in the spring it saves your organization time and money by reducing the time required to gather, summarize and report. If you are interested in better understanding how UPDM can ease your reporting and compliance requirements, please review the data model yourself. UPDM is provided as a free download from the Esri solutions website. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions.   ... View more

By Emery Poulsen and Tom DeWitte Simplifying and optimizing the field user experience of completing an asset inspection seems to be a high priority on every utility’s to-do list. Many utilities will refer to this effort as a paper to digital transformation. With any transformation comes an opportunity to improve on the legacy method. So, what can be done to improve asset inspections? Eliminating Redundancy On every asset inspection is a set of questions about what asset is being inspected. These questions ask the utility mobile worker to enter information such as AssetID, size, and material. These are nuggets of data that the organization already knows. With legacy paper forms this information had to be manually entered by the utility mobile worker. With digital forms this information can be automatically passed from the asset record to the inspection record. The passing of this known information can be achieved with app linking, eliminating this type of redundant data entry. What is App Linking? App linking, sometimes called deep linking, is not an Esri-specific term, and you likely take advantage of app linking every day. This capability can be used in many different ways, but the general idea behind app linking is that it allows separate applications to communicate with each other. A common example – you have the Contacts app on your cell phone open, and you’re looking at a friend’s contact. When you click on the “call” button, app linking is the mechanism that then opens the Phone app and dials that phone number. A more Esri-specific example – you're in Field Maps, and you’ve selected the asset that needs to be inspected. Within the pop-up for that asset, you click “Directions.” App linking is the mechanism that not only opens the navigational app of your choice, but also inserts the coordinates of that asset as the destination, without any copying or pasting from you. How Can App -Linking Improve Asset Inspections? App linking between ArcGIS Field Apps allows the field worker to view the asset in Field Maps that needs to be inspected, click on a special link that can be found in the pop-up associated with that asset, and open the Survey123 app directly from there. Not only this, but that specialized URL can open the correct survey (using the desired survey’s unique item ID) and pre-populate the survey with information about the asset from the asset record in Field Maps. All of these steps happen with the click of a button, creating a seamless experience for the field worker. Benefits of Passing Asset Data If your utility maintains unique IDs for all assets, and you have a lot of assets, those IDs can get long and complicated. Manually entering this ID is tedious and prone to error. It’s imperative, however, that the ID gets transferred into the survey correctly in order to associate that inspection record with the correct asset. App linking automatically enters this ID into the inspection form. By using app linking between Field Maps and Survey123, you can take the human error out of the equation, saving the field worker time and energy while also ensuring that that information is accurate, the first time around. The primary workflow I’d like to highlight is app linking between Field Maps and Survey123 to optimize a valve inspection workflow. This workflow is just one example of how app linking between ArcGIS Field Apps can help to maximize efficiency and minimize human error. The workflow is designed so that the field worker views the asset in Field Maps and clicks on a link embedded in the pop-up. That link then opens Survey123, creates a new survey record, and pre-populates the asset’s attribute information into the appropriate places within the new survey record. This saves the field user from having to copy over all of the information from the asset record into the asset inspection record, in turn saving the utility mobile worker time, energy, and potential frustration. This app linked integration eliminates mistakes and typos that can be made with paper forms. How Does App Linking Work? App linking works by using a specialized URL (called URL schema or URL parameters) to open an external app and communicate information. When utilizing app linking in Field Maps, this specialized link is constructed as an attribute expression in a web map... ... and then that attribute expression is put into the pop-up via a text element in order for the end user to access it. Within that text element, the attribute expression is inserted as a hyperlink. The attribute expression represents the specialized link to the desired survey, as well as the instructions directing the pre-population of information from the asset’s fields into the appropriate questions in the asset inspection survey. From the end user’s perspective, they are simply clicking on a link; this creates a seamless experience for the field worker and increases the likelihood that correct information is entered the first time around. How Else Can App Linking be Used? The field apps that can launch or be launched using app linking include ArcGIS Survey123, ArcGIS QuickCapture, ArcGIS Field Maps, ArcGIS Workforce, and ArcGIS Navigator. The workflows that are possible are only limited by your imagination and creativity. For example, in addition to creating new survey records in Survey123 from Field Maps, the field worker could start in Field Maps and open up an existing survey, make any necessary edits, and submit like normal, rather than digging through hundreds of survey records to try and find the correct one to make edits to. Another use case for app linking would be creating specialized links for field crew to directly open their routes for the day in ArcGIS Navigator, as shown below.   A Workforce Launchpad is another potential use case; the field crew could open ArcGIS Workforce first, and from there launch Survey123, Navigator, and Field Maps. The possibilities are truly endless. It’s About the End User By utilizing app linking, we allow the utility mobile worker to complete asset inspections in a way that saves them time and effort. This also eliminates data redundancy and improves data quality. This connectivity between apps, creates a way to pass those already-known nuggets of data from the asset record to the inspection record. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

By Tom DeWitte & Tom Coolidge Field data collection on paper forms has always struggled with defining a location. Too often, the top portion of a paper field data collection form asks the mobile worker a series of questions to describe where they are located. These questions ask for imprecise location descriptions such as state name, county name, city name, service area, construction project area, street name, and property number. None of these vague location descriptors will provide the follow-on mobile workers with the precise understanding of where the buried wire or pipe is located on the property to allow them to quickly locate these assets. To solve this location accuracy issue, most paper forms ask the mobile worker to draw a sketch in addition to answering those vague location descriptor questions previously mentioned. These “dumb” paper forms require more than conversion to digital; they need conversion to location-aware smart forms. Unfortunately, too many IT teams miss this opportunity to improve mobile worker efficiency by automatically populating these location questions.  They miss the opportunity to lower Operation and Maintenance (O&M) costs by eliminating the need for mobile workers to draw a sketch. Instead, they simply convert the questions on paper into digital form. When this “dumb” digital form is deployed to the mobile workforce, the mobile worker does not benefit. Often, they get frustrated and ask this simple question: If my mobile device knows where I am, why doesn’t the digital form? Location Aware Today’s mobile phones, tablets, and even laptops know their location. Many have built-in Global Navigation Satellite System (GNSS) chips. Others use cell phone triangulation or wi-fi network node location. These mobile devices can put a blue dot on the map to show the mobile worker where they are located. Where am I? The simple question of “Where am I?” is at the heart of location-aware smart forms. Leveraging the device’s understanding of location is a great first step in eliminating vague location questions. Remember that even the cheap GNSS receiver card in today’s mobile phones provides a more accurate location definition than a street address. According to Apple documentation, an iPhone 15 GNSS card has an average spatial accuracy of  +/- 10 meters. That translates to a search area of 314 sq meters. A quick Google search for the average square footage of suburban single-family lot returns an estimate of 1300 sq meters. Doing some quick math shows that using the mobile device GNSS card to identify location results in a 75% reduction in the search area to locate the buried utility. Knowing where you are, can be refined further by providing an interactive map with a basemap. Then allow the mobile worker to move the blue dot location to a new location based on the basemap. This will improve the spatial accuracy of your location, further reducing the potential search area for the buried utility. What Area am I in? With the location now defined, a location-aware smart form such are ArcGIS Field Maps can leverage this information to automatically answer other questions, such as, what service area am I in? What construction project area am I in? What city, county, or governmental region am I in?            These questions can be easily answered with the appropriate data to reference, and a geospatial function to overlay location against the reference data. Below is an arcade script for use as a calculated expression within ArcGIS Field Maps. This script uses the Intersects() arcade function to compare the feature’s location against a Construction Project polygon map layer. In this example, the construction project polygons were included in the map. This ensures the required reference information is always available, even when there is no network connection. What is Near Me? A location-aware smart form can also identify other features near you. For example, if you are inspecting buried hazardous pipelines and want to know if you are near a school. The question, “Is this near a school?" can be automatically answered with a combination of a buffer of your location and an intersection of the buffer area against a layer containing schools. Location Aware While Online When creating location-aware smart forms, it is important to know whether the field data collection activity must be available when the mobile device is not connected to a network. When offline support is not required, the referenced datasets do not have to be included in the map.  This is very useful when referencing Living Atlas of the World datasets, such as USA Current Wildfires, USA Structures, or USA Flood Hazard Areas, to name a few of the many available data layers.  A minor change in how the referenced dataset is called is all that is needed. The arcade function FeatureSetByPortalItem() allows the form's calculated expression to reach out to another portal and query its data. Location Aware While Offline When the field data collection form must function even when the mobile device is not connected to a network, then all referenced data must be in the map. These referenced data layers or tables must be correctly configured per Field Maps' offline map area requirements. When a data layer of the data table is correctly configured for offline map area usage, the syntax to call these reference information items is the same, regardless of whether the mobile device is online or offline. The FeatureSetByName() arcade function with the $Map parameter is the arcade function to call the reference items. This function is the same whether the referenced map item is a layer or a table. Completing Paperwork Faster Using a location-aware smart form simplifies the field data collection process. These smart forms improve a utility’s mobile worker productivity by auto-populating the form's location questions and removing the need for manually created sketches. For utility organizations, this location-based intelligence reduces O&M expenses by allowing mobile workers to spend less time doing paperwork and more time managing utility assets.  For IT professionals, location-aware smart forms avoid the embarrassment of mobile workers asking them: If my mobile device knows where I am, why doesn’t your digital form? PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

This zip file contains the arcade scripts to enhance Field Maps for ArcGIS with the following capabilities: A sample geodatabase compatible with UPDM 2021. This sample schema has been modified to address the specific needs of mobile as-builting. Arcade calculation expressions to automatically decode the ASTM F2897 barcodes when scanned by a mobile devices camera or Bluetooth scanner.  These scripts work in both a network connected and a network disconnected mode. Incorporates modifications made to the ASTM F2897-23a standard in late 2023. This includes new manufacture components, material types, and pipe dimensions. Automatically capture the original GPS data and write to feature attributes (GPSX, GPSY, GPSZ). Arcade pop-up expressions perform real-time validation of the collected pipe and pipe component information.  Validation checks include:                  -Verify medium density and high density polyethylene components have not exceeded industry recommended shelf life.                  -Verify the pipe or pipe component manufacturer is a gas organization approved manufacturer.                  -Verify the pipe type and size are compliant with gas organization codes and standards. And more…   Thank you Tom DeWitte Esri Technical Lead – Natural Gas Industry ... View more

What Data Belongs in a GIS for Pipe Utilities By Tom DeWitte and Tom Coolidge We, “The Toms of Esri,” “have supported pipe organizations for many years. Neither of us has enough fingers and toes to count our years of service to the natural gas and hazardous liquids industries. Over the years, industry professionals have asked us the following foundational question: What data belongs in the GIS? This question gets asked by all levels of staff within a natural gas or hazardous liquid organization. Everyone from entry-level GIS analysts to Chief Information Officers want to know the answer to this question. So, what data belongs within a GIS? The simple answer is that all data with a defined location should be stored and managed within a GIS system such as ArcGIS. This technically correct non-specific answer may not quench your desire for a fuller understanding of why a specific dataset should or should not be managed with a GIS. A fuller understanding requires answers to at least four questions: Question 1: What is the spatial accuracy of the data? Question 2: How should the location be described? Question 3: Who needs the data? Question 4: How will the organization consume the data? What is the spatial accuracy of the data? This is the question that non-geospatial-oriented persons struggle with the most. However, the answer is critical to help determine which enterprise system should store that data. Ask a non-geospatial-oriented person where a critical valve is located, and they will likely try to provide you with a street address. When attempting to find a buried asset less than 6 inches in diameter, the street address for a major manufacturing facility may describe a location covering over a square mile! The street address is technically correct, but its lack of spatial accuracy fails to meet the need of the field employee attempting to find the specific valve to close during an emergency event. This example highlights that whichever enterprise system stores this information must be able to store the location to a level of accuracy that meets the needs of the organization’s users. Within the natural gas and hazardous liquids industries, there is an evolving consensus to locate each buried pipe asset to within 18 inches of its absolute location. How should the location be described? It is helpful to know that the location of a pipe network buried asset should be defined to within 18 inches of its true location on the surface of our planet. Most enterprise information systems can easily store a latitude, longitude, and elevation value for a single record within their data storage solution. But what happens when more is required to describe the asset? What happens when the asset is linear, such as a 50-foot-long section of pipe? What happens when the asset is polygonal, such as a right-of-way easement. Accurately describing the location of a plastic pipe section that curves around a cul-de-sac can require dozens to hundreds of x, y, and z coordinates. Answering this second question is our first clear separation of capabilities between information systems. Most information systems cannot manage the complex geometries of pipes, pipeline routes, and right-of-way easements. These complex geometries require not only special spatial data types within the data repository, but also the ability to display, query, and analyze. A tabular display of a plastic pipe segment with dozens of vertices to accurately represent its location is not a useful nor easy to understand presentation of data. Who needs the data? Now, we need to look at who within a natural gas or hazardous liquid organization needs this geospatial representation of the asset.   An initial answer to this question is anyone in the organization who needs to see and understand the relationship between the assets, the relationship between the assets and nearby hazards, or the relationship between the assets and the environment in which they reside. Every engineer within the organization must understand how the individual assets are combined and connected to create a pipe network. Without this understanding, they cannot model and understand how the gas or liquid flows through the pipe network. Field staff use maps every day to help them understand where the pipes are buried. The geospatial location displayed on the maps informs the field staff how the pipe system runs across a property, neighborhood, and community. The location displayed easily and clearly provides the field staff with an understanding of where a service line connects to a main, where a valve is located along a pipeline, and which portion of a pipe is located within an easement. The finance department is another pipe organization department which depends on accurate and current representations of tax districts and pipe asset locations. The spatial intersection of these two separate datasets is required to be able to accurately tabulate an organization’s tax bill. Every time a pipe segment spans more than one tax district, the finance department needs to know what proportion of the pipe asset resides in each tax district. How will the organization consume the data? There are many subsets of data for which the answers to the first three questions do not clearly and logically define where a dataset should be stored and managed. In these grey-area datasets, the fourth question provides clarity. How will the organization consume the data? Many critical datasets, such as reported leaks, excavation damage, and exposed pipe inspections, often fall into this grey area. Each record within these datasets represents an event that occurred at a specific location. Each record requires a spatial accuracy to define where it occurred on the surface of the planet. Each record is typically defined as a singular coordinate pair (latitude, longitude). Each record is used repeatedly across the organization to support compliance department staff, damage prevention staff, pipe integrity staff, and field staff. Yet, for each of these examples, it is how these departments consume and utilize this information that provides clarity on how it should be stored and managed. The exposed pipe inspection dataset is a great example. In many countries, such as the United States, it is federal law that anytime a natural gas or hazardous liquid pipe is exposed to the atmosphere, it must be inspected. The information collected with this field activity is very valuable to the departments performing distribution integrity analysis, transmission integrity analysis, and main replacement prioritization for capital planning. Digging into how these departments consume this data is where you see that the commercial products typically purchased to perform these valuable analytics require a specific geospatial format for input. Why do they require a specific geospatial format? They require a geospatial format because the risk analysis being performed requires an understanding of where the asset resides with respect to risks nearby, as well as an understanding of the consequences of failure to the portions of the community near the asset. If you store this information in a spreadsheet or other non-geospatial structure, you will have to convert the data into a geospatial feature to support the geospatial-based analysis. The decision to store data that needs to be consumed with a geospatial representation in a non-spatial data structure means that your organization will incur additional O&M expenses every time you want to run these mission-critical analyses. By understanding how information is consumed, IT departments can organize, store, and manage their data in the enterprise system, which provides the organization with the lowest operational cost and greatest efficiency for end users. A logical approach Four simple questions about the data can provide organizations with a logical and defensible  approach to answer the question of which enterprise system should store a dataset. These four questions can help guide the organization to a decision that is truly in the best interest of the entire organization. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

Helping Mappers Get it Right  By Tom DeWitte and Tom Coolidge Correctly mapping a buried pipe network is difficult. Everyone in your organization depends on the information to be “right.” The geometry must be right, the location must be right, the attributes must be right, and the connectivity and flow must be right. If any of these information components are wrong, your organization incurs inefficiencies, extra expenses, and potential damage to your pipe network. The mapper is the person within the organization typically responsible for creating and maintaining this information. Every day, they come to work and face the challenge of consistently entering a large amount of information correctly—information that the entire organization depends upon to perform its own jobs. To succeed at this challenge, mappers need software tools to allow them to enter this information consistently, accurately, and efficiently. Within ArcGIS, many configurations are available to help the mapper enter and update this information correctly the first time. Some of these capabilities are real-time data quality control, and some are validations to be checked after feature editing but before posting. Let’s look at the tools and capabilities available to help mappers create the pipe network information correctly the first time. Getting the Geometry Right Getting the Geometry right is critical to ArcGIS tracing and for hydraulic engineers who import the geometry into their modeling software, such as DNV’s Synergi Gas product. Both ArcGIS tracing and hydraulic modeling software require polylines that are not self-closing and do not have multiple vertices occupying the same coordinate location. Additionally, a polyline representing a pipe segment should never have a cutback of less than 60 degrees. Implementing rules to prevent these types of misconfigured polylines is easy within ArcGIS Pro. A pulldown listing of ready-to-use geometry rules is provided for a geodatabase administrator to select and apply to the desired polyline featureclass. With these geodatabase configurations in place, the mapper will receive real-time feedback when they attempt to create an invalid geometry. Implementing the attribute rule constraint denying polylines with a cutback of less than 60 degrees, blocks this new feature from being completed. Getting the Connectivity Right Getting the connectivity right is also critical for any use case that requires tracing or an understanding of flow direction. Common use cases requiring connectivity are:                 -Hydraulic modeling                 -Emergency isolation tracing                 -Cathodic protection management Within pipe utilities such as gas, water, and district energy, there is another aspect of connectivity that the mapper also needs to consider. That is the correct assembly of the pipe network itself. There are many combinations of connectivity that are invalid.  For example, it is not valid for a gas service line to tap directly off a gas transmission line. Nor is it considered valid for a cathodic protection rectifier to be connected to a plastic pipe segment. Metallic-only fittings, such as screws, flanges, and weldolets, should not be directly connected to plastic pipe segments. The Esri-provided data models include a rulebase that defines valid connectivity between assets. Mappers using ArcGIS Pro get rule-based snapping tips to show them the valid connection options. This real-time guidance is a display mechanism to help mappers get it right the first time. When a mapper attempts to connect two assets together incorrectly, the snapping tips will not display. For example, in this example, a steel pipe is incorrectly attempting to be connected to a plastic pipe. When the mapper correctly attempts to connect a plastic distribution pipe segment to another plastic distribution pipe segment, the snapping tip displays to indicate the valid connection. Getting the Attributes Right – Calculations Mappers are continually asked to enter an ever-increasing amount of information about the asset. Implementing attribute rule calculations into the geodatabase is a great way to automate the input of the information and improve its accuracy. Decoding barcodes is a great example of the power of automation while also improving the quality of the data. In this example, an arcade script was written to automatically populate the data fields: nominal diameter, wall thickness, material, manufacturer, manufacture date, manufacturer lot number, and material component type. That is seven data fields automatically populated from one data field. For the mapper, life is simplified by having this very detailed information auto-populated. Getting the Attributes Right – Picklists Most data fields that a mapper is asked to populate have a finite number of valid values. Fields like diameter, material, component type, and even wall thickness have a limited number of valid values. The geodatabase provides two related mechanisms to allow administrators to have ArGIS provide a picklist from which the mapper can choose. Coded-value domains, and contingent values are these two mechanisms.  Coded-value domains enable an administrator to create a pre-defined list of values from which the mapper can choose.  This eliminates misspellings, inconsistent capitalization, and inconsistent abbreviation mistakes that are common with freeform data entry. When applied to a data field, the mapper will be restricted to selecting a value from the list. There is no override option. Contingent values enhance coded-value domains with a dynamic filtering capability that is based on another data field’s value within the record. For the mapper, selecting a coded-value domain value in one data field, such as asset type = Coated Steel, will automatically filter the coded-value domain list of values in another data field, such as pipe material grade. This real-time dynamic filtering can be defined as the unique combination of values across two, three, four, or more data fields.   Getting the Attributes Right – Required Field Constraints Geodatabase attribute rule constraints can also be configured to prevent the submission of an edit unless specified conditions are met. A common example is required fields. In this example, an arcade script was written and applied as an attribute rule constraint.  This attribute rule script requires that a tee cannot be submitted unless the data fields; diameter, diameter2, wallthickness, wallthickness2 are populated. More advanced logic can be applied to have conditional required fields based on values of other data fields in the same record. With this type of logic in place, mappers will be reminded at the point of submitting the record when a required data field has not been populated. Getting the Attributes Right – Validations Not all business rule logic can be consistently and correctly applied at the record submission stage. Some business logic needs to wait until the full set of edits for a construction project or repair has been applied. This delayed application of business rules is called validations. Validation checks are initiated by the user with the Validate tool or automatically as a nightly batch process. Common pipe network examples of validations are: -verifying against the utility network rule base, - verifying that the excess flow valve is coincident to a service pipe, -verifying that the valve diameter is the same as the coincident pipe diameter. These types of multi-feature data quality checks help mappers find mistakes that would be missed with simpler business rule logic applications. Getting it Right The geospatial data created and maintained by mappers is critical to the safe and reliable operation of the pipe network. Everyone in the pipe organization, from finance to engineering to field operations, depends on the geospatial data to be correct. The mappers maintaining this enterprise-level data source need robust and multi-tiered business rules to help them enter this information correctly the first time. ArcGIS is the system to provide these capabilities and to aid the mapper in getting it right the first time. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

By Tom DeWitte and Tom Coolidge Within every pressurized pipe network, whether natural gas, hazardous liquid, water, or district energy, there are one or more pressure zones. Pressure zones are foundational to the engineering and operation of pressurized pipe networks. A formal definition defines a pressure zone as a distinct subset of the pipe network where a minimum and maximum pressure range is maintained by pressure-controlling devices. Yet, knowing this definition of a pressure zone is not the same as understanding a pressure zone. Understanding a Pressure Zone Understanding a pressure zone has differing meaning across an organization responsible for managing a pressurized pipe network. System planners require an understanding of the capacity of the pressure zone and the load from customers consuming the commodity traversing the pipe network. Hydraulic engineers need to understand the capacity, load, assets, commodity flow, and the type of customers depending on the provided service. Integrity Engineers require an understanding of the pressure zone assets and their characteristics. System control center operators must understand the standard operating pressure and the current maximum allowable operating pressure (MAOP). For many others across the organization, it means visually seeing the extent of the pressure zone. With this wide range of what it means to understand a pressure zone, how does an organization achieve this understanding? Defining the Pressure Zone The need to create an inventory of the assets that comprise a specific pressure zone is foundational to all these various aspects of understanding a pressure zone. From a software perspective, this means utilizing software that can determine a pressure zone. This determination is based on how the pipe assets are connected, knowing the location of the pressure regulating devices, and an understanding of the high side and the low side of those pressure regulating devices. With this understanding of pressure zone components, add some software logic to define commodity flow, and you can now define a pressure zone. Within ArcGIS, the capability to determine a pressure zone is called the ArcGIS Utility Network. The result of the application of this capability for pressure zones is the creation of a pressure subnetwork. Defining a pressure subnetwork within ArcGIS generates multiple items of information to aid in understanding the pressure zone. These aids are: Creating a persistent graphical representation of the pressure zone. Inserting the name of the pressure zone to each asset contained within the pressure zone. Tabulating quantities of the identified assets, such as number of meters and number of valves. Performing engineering calculations to determine MAOP for the pressure zone. This inventorying, tabulating, calculating, and visualizing provide pipe organizations with the foundation to understand the pressure zone. Understanding A Pressure Zones Capacity A common derivative of the pressure subnetwork representation of the pressure zone is the tabulation of the volume within the pressure zone. Knowing a pressure zone’s pipe volume has historically been the primary challenge in accurately determining the standard operating pressure amount of commodity within this subset of networked pipes. For an individual pipe segment, tabulating volume is an exercise in remembering the middle school geometry equation for a cylinder. That equation leverages the diameter and length of the pipe. Repeating this geometry calculation thousands of times for each distribution main and service line within the pressure zone is hard for humans. It is a simple calculation for a computer. With the volume automatically tabulated for the pressure zone, the next step is to apply the Ideal Gas Law equation and some commodity specific values to determine the mass and energy stored within the pressure zone. An arcade script within a pop-up can easily perform this calculation for both the standard operating and the maximum allowable operating pressure. Having the result of this tabulation readily available whenever a user opens a pressure zone pop-up within a web application or mobile map is a significant time saver for engineers and system control operators. Understanding A Pressure Zone’s Assets Once the ArcGIS Utility Network capability defines a pressure zone, the capability updates the name of the pressure zone in all traced assets (pipe segments, valves, fittings, customer meters, etc. This assigning of the pressure zone name to each asset, simplifies follow-on pressure zone asset queries often used in capital planning, such as: Average age of pipe Length of pipe by material Length of pipe by size Understanding a Pressure Zone’s Pressure Range Core to managing a safe and reliable pressurized pipe network is knowing the maximum pressure at which the gas utility can safely operate the pressure zone. To most industries this value is known as MAOP (Maximum Allowable Operation Pressure).  This value is asset specific and will vary across the thousands of assets comprising a single pressure zone. The pressure zone MAOP is defined by the weakest link within all the assets of the pressure zone. In software terms, this is the application of a minimum function against all the pressure zone asset’s individual MAOP value to find the lowest value. The ArcGIS Utility Network capabilities can automatically tabulate this engineering value as part of defining the pressure zone. With MAOP now automatically defined and maintained by ArcGIS, whenever a new asset is installed within the pressure zone and the asset’s individual MAOP value is defined, the software will revise the pressure zone MAOP to reflect the installation of the new asset. Combining the calculation of MAOP with the tabulation of volume for a pressure zone allows for the calculation of maximum line pack. Line packing is a natural gas industry term for increasing the mass of gas within a given pressure zone. Line packing is achieved by increasing the operating pressure. An increase cannot exceed MAOP. Control room operators use this value to understand how much additional mass can be placed within the pressure zone pipe network in anticipation of a forecasted increase in customer demand. Understanding a Pressure Zone’s Extent The ability to see a visual representation of the pressure zone is another product of the ArcGIS Utility Network defining a pressure zone. The ability to see the extent of a pressure zone is key to helping a utility’s staff answer their questions. Typical questions include: Emergency Events. Which pressure zones will be impacted by wildfires and floods? Planning: Which pressure zone provides service to the address of a potential new customer? Engineering: When planning a system modification, what is the extent of the pressure zone? Understanding a Pressure Zone’s Customer Base With the pressure zone accurately defined, geospatial analysis methods can be applied to identify and inventory the customers within a given pressure zone. As an example, a buffering of customer meters with the pressure zone name can query the USA Structures Living Atlas feature layer to tabulate valuable information such as: Number of hospitals Number of schools Number of impaired / limited mobility customers Quantity of types of customers (residential, commercial, industrial, government This provides instant clarity of the customer base being served by the pressure zone. This clarity helps emergency event coordinators, engineers, and planners. Bring it All Together Historically, the information mentioned in this article has been scattered across an organization’s many data siloes, spreadsheets, and the brains of individual employees. Leveraging ArcGIS and its ArcGIS Utility Network capability to define the pressure zone brings this information together. This aggregation of information and presenting it in a manner that is easy to understand is what turns defining a pressure zone into understanding a pressure zone. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

AutoCAD and ArcGIS Working Together By Tom DeWitte and Tom Coolidge Esri released in January of 2024 an updated version of its ArcGIS for AutoCAD plug-in for Autodesk® AutoCAD®, AutoCAD Map 3D®, and Civil 3D®. The Esri plug-in allows AutoCAD users to become editors of ArcGIS-managed data. The January 2024 update (version 430) of ArcGIS for AutoCAD enhances the editing experience by supporting branch versioning within AutoCAD. This branch versioning support further strengthens the incorporation of the AutoCAD editor into the data management workflows within the world of ArcGIS. What do these new tools and capabilities mean for Utilities? Within the world of documenting new construction projects for utilities, there is a common practice that is needed but very inefficient. This is the practice of using AutoCAD to document the construction project and ArcGIS to document the current as-built state of the entire utility system. After construction, AutoCAD drawings are created as part of the project closeout activity to document what was installed, retired, and modified. The AutoCAD drawings are often converted into PDF files and stored in a document management system as a historical project snapshot. At the same time, the ArcGIS mapping team is updating the as-built representation of the entire utility system to reflect the newly constructed changes. This information is shared with the organization through web and mobile applications, giving the whole utility organization a current representation of the entire utility network. The problem with this dual documentation workflow is that the AutoCAD editor and the ArcGIS mapper perform the same data edits. The ArcGIS for AutoCAD plugin provides a solution to this redundant data entry. Eliminate the Duplication The ArcGIS for AutoCAD plugin solves this duplicate data entry issue by allowing the AutoCAD user to update their CAD drawing with the data edits made by the ArcGIS mapping team. Now, a simple “Synchronize” from the ArcGIS ribbon in AutoCAD allows the AutoCAD mapper to update their AutoCAD drawing with the features created by the ArcGIS mapper. Since the ArcGIS data maps an area much larger than the project area of interest to the AutoCAD mapper, a blue project area bounding box is used in AutoCAD to define the geographic extent of data of interest to the AutoCAD user. When the synchronization is complete, the GIS features within the project area are loaded into the AutoCAD drawing. No additional conversion, prep, or translation is required. This synchronization with ArcGIS is more than simply bringing over geometries. It also brings over features’ attributes, including coded value domain descriptions. CAD And GIS Working Together The increasing collaboration between Esri and Autodesk directly benefits Utilities. The ability of AutoCAD to consume ArcGIS layers of data and basemaps simplifies their tasks for creating CAD drawings and improves their productivity. Long gone are the days when the CAD community and GIS community were antagonists to each other. Now, we can all work off the same dataset. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

   Beware the Ides of March By Tom DeWitte and Tom Coolidge Beware the Ides of March. Stated in less Shakespearean form, beware of March 15th. This statement was true for Julius Caesar and is true today for many GIS and compliance professionals across the United States natural gas industry. In Roman times, March 15th was the deadline for settling debts. Today in the United States, March 15th is the deadline for submitting annual reports for gas distribution and transmission companies to the U.S. Department of Transportation (U.S. DOT) Pipeline and Hazardous Materials Safety Administration (PHMSA). The submittal of the U.S. DOT PHMSA Annual Report for Gas Distribution (Form F 7100.1-1) and its sibling, the U.S. DOT PHMSA Annual Report for Gas Transmission and Gathering Pipeline Systems (F 7100.2-1), is an exercise in data mining. If your data is well organized and attuned to the data summarization requirements of these reports, gathering the information required to complete these forms is manageable. Suppose your data is not attuned to the data query, filtering, and summarization needs of these reports' data query, filtering, and summarization needs. In that case, this annual effort is scarier than having a best friend named Brutus. Officially, PHMSA estimates that the time required to gather the data needed to complete these forms is 16 hours for Gas Distribution and 47 hours for the Gas Transmission and Gas Gathering form. This is achievable with a well-attuned geospatial dataset such as an ArcGIS data repository organized with the Utility and Pipeline Data Model (UPDM). If your data is poorly organized, this effort can take several months. What does a well-attuned geospatial dataset look like? Summarizing by Pipe Material The first indication of a data model well attuned to these reports' data summarization needs is how material is defined. Part B of the Gas Distribution report does not ask for the specific material grade of the pipe (PE2708, Grade X42, etc.). It asks for a generic categorization of material (Plastic, Coated Steel, Bare Steel, Cast Iron, etc.). Part D of the Gas Transmission and Gas Gathering report similarly asked for a generic categorization of the material instead of the specific grade. The UPDM data model explicitly defines these categorizations of material in a data field called; AssetType. This AssetType data field has a set list of values which align with the categorization material values requested in the DOT reports. A simple summarization of the assettype and cptraceability data fields will produce the data values needed for section B1 of the Gas Distribution Report. A summarization of unique combinations of assettype, cptraceability, and regulatorytype will produce the data values needed for Part D of the Gas Transmission and Gas Gathering report. These summarizations can be easily accomplished in ArcGIS with UPDM-organized data in minutes versus hours, days, and even weeks. Summarizing Transmission By SMYS Part K of the Gas Transmission and Gas Gathering Report asks for the miles of transmission pipe based on the operating pressure as a percent of specified minimum yield strength (SMYS) for a given DOT class designation. Storing engineering information about the pipe as descriptors about the pipe greatly simplifies summarizing this information for the Gas Transmission and Gas Gathering Report. When the UPDM data fields for this engineering data are populated, this tabulation can be performed. The specific data fields within the pipelineline layer of UPDM are operatingpressure, SMYS, percentSMYS, dotclass and shape_length. Similar to the mileage by material table, a summarization of the unique combinations of percentSMYS, and dotclass, then summing the total length of pipe produces the information needed to populate this table. Summarizing Leaks by Cause UPDM and its optimization of data organization to support the reporting needs of the annual DOT reports extend beyond pipes. It is also attuned to the reporting requirements of leaks. Part C of the Gas Distribution report asks for the number and severity of leaks on mains and services. Here again, the P_GasLeaks featureclass in UPDM is intentionally organized to accommodate this categorization of leak cause and severity. The data field, leakcause includes a set list of valid values, which correlates to the Cause of Leak categories of the reporting table. The data field, revisedleakclass provides the leak severity distinction, and the leakstatus data field provides the indication of the status of the leak. UPDM Alignment with DOT Reporting was no Accident The fact that UPDM is so well aligned with the reporting needs of these annual reports is not an accident of data modeling. When UPDM was originally created, these DOT reports were studied. The intent way back in 2009 was to organize this information to not only address the daily engineering and operational needs of natural gas organizations but also to simplify this required annual reporting task. In the 15 years since the original release of UPDM, the gas team at Esri has continued to monitor the evolution of these compliance reports and, when needed modify UPDM to accommodate changes in reporting. March 15th was a very bad day for Julius Caesar; it does not have to be a bad day for you.   PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

Utility and Pipeline Data Model 2023 is Released By Tom DeWitte and Tom Coolidge Esri’s Utility and Pipeline Data Model (UPDM) 2023 is available now. This release continues Esri’s practice of maintaining a template data model ready “out-of-the-box” to manage gas and hazardous liquid pipe system data within an Esri geodatabase. This release includes enhancements to keep up with changes in industry practice and implementation feedback received since the previous release. Updates to Industry Barcode Standard In mid-2023, the ASTM technical committee overseeing the F2897 barcode standard published an update. F2897 is the Tracking and Traceability encoding system defining the format of the barcode that manufacturers place on their pipe, fittings, valves, and other assets. This update added new materials, new manufacturer components and new manufacturers to the standard. New materials include PE80, PE100 and Reinforced Epoxy Resin, to name a few of the additions. New manufacturer components include new types of pipe, new types of fittings, and more combination components such as Reducer Socket Fusion with EFV. There were also four new manufacturers added to the standard. These additional manufacturers are:                 -Improved Piping Products                 -Shawcor Composite Production Systems                 -Krah USA LLC                 -Hawkeye Industries Inc All these modifications now have been baked into UPDM 2023 to continue its support of this important industry standard. Updates Based on Implementation Feedback There are now dozens of gas and hazardous liquid organizations in production with UPDM. As each organization goes through its journey of implementing this geospatial system of record, Esri’s industry data model gets tested and retested. These projects are located globally, and our implementation partners continue to provide feedback when a gap is identified. This list of recommendations from implementations is short, as the data model has reached a level of maturity and completeness that limits the need for change. For this release we have: added Storage Facility as a new type of PipelineAssembly. added Olet as a new group to PipelineJunction to cover a type of fitting known as olets.  Weldolet, Threadolet, and Sockolet are types of olets that are now a part of our industry data model. added Service Station as an additional type of PipelineDevice to support the emerging idea of compressed natural gas, and hydrogen as fuels for transportation. Gas and Pipeline Referencing Utility Network Foundation For many gas utility and hazardous liquid pipeline enterprises, deploying ArcGIS is more than simply loading the UPDM 2023 data model into an enterprise geodatabase. That’s because ArcGIS leverages the concepts of a service-oriented web GIS. It requires additional steps, such as creating an ArcGIS Pro map configured for publishing the data model, publishing of the Pro map to create the required map and feature services and, perhaps, configuring a location referencing system. To help simplify these additional steps performed with UPDM 2023, Esri has embedded UPDM 2023 into the Gas and Pipeline Referencing Utility Network Foundation. This solution provides UPDM 2023, sample data, and an ArcGIS Pro project configured with tasks and performance-optimized maps. You can access this solution from the Esri ArcGIS for Gas solution site. A full data dictionary of UPDM 2023 is available online. A change log documenting the full list of changes incorporated into UPDM 2023 is also available online. Esri’s Template Data Model for the Industry Esri first released UPDM in 2015 as a part of a new vision of how a geospatial system of record for pipe systems can be much more than a departmental solution. It can be a foundational enterprise system providing a unified office and mobile workforce with a near real time single source of the truth. This belief that there should be a single source of the truth from which the entire organization can view, query, create and maintain their entire pipe network has driven not only the development of this industry data model, but also the development of our network management and linear referencing capabilities. UPDM is the only industry data model built by Esri in collaboration with Esri’s ArcGIS software development team to support the enterprise needs of the gas and hazardous liquid pipe industries. UPDM is a moderately normalized data model that explicitly represents each physical component of a gas pipe network from the wellhead to the customer meter, or a hazardous liquids pipe network from the wellhead to the terminal or delivery point, in a single database table object. This freely available data model is designed to take full advantage of the capabilities of the geodatabase. The data model is created and tested with ArcGIS products to ensure that it works. This significantly reduces the complexity, time, and cost to implement a spatially enabled hazardous liquid or gas pipe system data repository. Looking ahead to the Future A wise man once said “change is the only constant.” This is a great quote when thinking about UPDM going forward. The Esri development team will continue to enhance the capabilities of ArcGIS. Industry will continue to evolve its practices. To continue adjusting to industry practices and incorporating new ArcGIS capabilities, UPDM will continue to evolve.  This evolution will help assure gas utilities and hazardous liquid pipeline operators that their GIS industry-specific data model is current with their needs. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more