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How Analysts & Researchers Use Gravy’s Location Data Forensics

February 23, 2022

What is Location Data Forensics?

Location Data Forensics is a unique feature of our Observations data. This process involves separating high-quality location signals from low-quality, suspicious, and even fraudulent signals. These signals are then tagged with Gravy Forensic Flags that enable analysts to filter valid data by signal origin, location accuracy, and other key characteristics.

Forensic Flags - Signals Processing
An example of location data forensic processing for a sample of Gravy’s data.
What Challenges Do Forensic Flags Solve?

Over 50% of location data is flawed, but that doesn’t mean it can’t be used in analyses. If analysts are provided with visibility into what makes those individual location signals flawed, then they can determine which data points are right for their company’s needs. 

For example, Observations data that we have flagged as being reported from a potentially spoofed location would not be useful to include in foot traffic analysis where high precision is paramount. That same Observations data, however, would be highly valuable in fraud detection analysis where consumer-provided location information needs to be corroborated against another dataset.

A Real-World Example: How the University of Florida Transportation Institute (UFTI) Used Forensic Flags

UFTI researchers currently use Gravy Observations to study human mobility in evacuation zones around wildfire disasters, which can help to inform emergency and disaster management policies. These researchers work with our data because of its transparency and flexibility.  

In a recent study, UFTI researchers chose to exclude the Observations that were flagged as being reported from a “spoof location” because those location signals would have skewed their data analysis. Gravy Observations flagged as “likely driving” were included however, as those types of signals were equally effective in analyzing human mobility patterns in wildfire evacuation areas as those associated with pedestrian foot traffic. Read the full case study to learn more.

Figure 11: Distribution of Census-Tract-Level Evacuation Compliance Rates. Image from Zhao. et. al, “Estimating Wildfire Evacuation Decision and Departure Timing Using Large-Scale GPS Data,” 2021.
Image from Zhao. et. al, “Estimating Wildfire Evacuation Decision and Departure Timing Using Large-Scale GPS Data,” 2021.
Top 4 Benefits of Location Data Forensics

By including a Location Data Forensics feature in our Observations data, analysts can select the best location signals to work with for a variety of use cases. Additional benefits of this feature include:

  • Transparency in the data with resulting insights they can trust
  • Less time and fewer resources spent on preparing the data for analysis
  • Potentially lower storage costs for smaller datasets
  • Ability to use the same dataset easily for different types of analysis

For more information on which of Gravy’s Location Data Forensic Flags align with your analytics needs, speak with a location intelligence expert from Gravy Analytics today.

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