Data Integrity in NG9-1-1: Essential QA/QC Practices for GIS Success

Is your GIS data ready for the demands of NG9-1-1? With increased responsibility on local authorities, data integrity has never been more critical. Discover essential QA/QC practices and see how tools like Esri Canada’s Address Manager can streamline data accuracy and readiness for NG9-1-1 compliance.

Quality Control Dial

As GIS professionals we work hard every day creating and maintaining high-quality data—but how do we ensure that the data is good?

Quality assurance (QA) and quality control (QC) are important for ensuring data integrity. Quality assurance is a process to prevent data errors, while quality control identifies errors that slip through the cracks. Our public safety project delivery team at Esri Canada works with different jurisdictions across Canada on Next Generation 9-1-1 (NG9-1-1) GIS Readiness Assessments, and often we are met with confused looks when we ask about what QA/QC data measures are in place. In many cases we find gaps or inconsistencies in the QA/QC process and in some cases these processes are nonexistent.

Why does data integrity matter now more than ever?

NG9-1-1 is bringing a new level of responsibility to local authorities in Canada. GIS technology will be used to overlay the geography (civic location, like a street address, or geographic location, like latitude and longitude coordinates) of the caller along with the geographic extents of the emergency response boundaries to determine where to forward the emergency call to as well as which local emergency response agencies need to be dispatched to respond to that location. For all this to work well, a robust GIS data standard is required. In an emergency, where seconds matter, data integrity is critical. 

How can we ensure data integrity for NG9-1-1?

There are a variety of techniques that can be implemented to assist with data integrity. Below we will highlight several options for consideration. It’s likely that a combination of these options will need to be used to find what best fits the needs of a local jurisdiction.

Quality assurance options

• Access controls are a great place to start. By limiting the editor access to 9-1-1 specific datasets you can avoid unintentional mistakes that could have significant impacts to response. Those with the ability to edit these layers should have a clear understanding of how this data is used in the 9-1-1 system and the impact that each small change has.

• Editor tracking is an optional geodatabase setting that can be enabled to help with accountability. Knowing when edits were made, and who made them, can expedite issue resolution. 

• Domains are another simple and effective method to restrict attribute values. This can eliminate typos and inconsistent values. NG9-1-1 industry standards, created by the National Emergency Number Association (NENA) define domain values and are a good place to start. Also, consider attribute rules, which are user-defined parameters that can automatically populate attributes, restrict invalid entries during edit operations, and perform quality assurance checks on existing features.  

Quality control options

• Geoprocessing tools like Select by Attribute or Select by Location are a simple method to review data. When the attributes and relationships to other features are clearly understood, these tools can be used to assess the positional accuracy or completeness of a dataset. 

• Automation can create more efficient processes by incorporating these previously mentioned checks into scripts and tools. Using geoprocessing tools, model builder, or python scripts can work in the back end to identify issues, generate reports, and enable scheduling.

• Topology tools can also be used to ensure positional accuracy using ArcGIS geoprocessing tools for building, analyzing, managing, and validating topology. Applying topology rules such as “polygons must not have overlaps and gaps” can identify where boundary datasets are not consistent. Applying “lines must not have dangles” can help to identify road segments that are not connected at intersections. 

• Formalizing these manual reviews or automated processes in a systematic way is an important part of making it a step in your process. Document it, schedule it, and test its effectiveness. 

Tools with built-in QA/QC already exist and can help to ensure data quality for NG9‑1‑1. Esri Canada created Address Manager which uses preset defaults and lookup tables to ensure data consistency. Address Manager streamlines NG9-1-1 data management by automating data entry; for example, when you create a new address point, records associated with the new point automatically generate fields such as road name, municipality, etc. based on the location of the new address point. It also validates the topology of service boundaries preventing any gaps or overlaps. This is a great option if you are looking for a framework that streamlines the management of data for NG9-1-1 with built-in QA/QC. 

Joining the conversation can greatly benefit any jurisdiction. Getting involved in the national conversations around the development of standards and best practices with different working groups like ESWG or NENA can help to stay informed of what is coming with NG9-1-1 and how these coming changes will impact your data management policies and procedures.

For more information on NG9-1-1 readiness, visit our site.