What Data Belongs in a GIS for Pipe Utilities
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.
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