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When it comes to analyzing safety data, FAA might be in database hell

When it comes to analyzing safety data, FAA might be in database hell

One of the most important functions of the Federal Aviation Administration is to gather, review and analyze all manner of aviation safety data to reactively and more to the future, proactively prevent accidents and manage safety risks.

But that overarching and most valuable task is difficult to do because of a variety of reasons that include the sheer volume and multiple locations of data.

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Such difficulties were brought up in a report out today from the Government Accountability Office that stated: "Implementing systems and processes that capture accurate and complete data are critical for FAA to determine the magnitude of safety issues, assess their potential impacts, identify their root causes, and effectively address and mitigate them. Though FAA has put in place data quality controls, weaknesses remain in some areas. In particular, several FAA databases GAO reviewed in 2010 did not have a managerial review process prior to data entry — an important control that helps ensure data accuracy and completeness. In response to GAO's recommendations, FAA is taking steps to address its data weaknesses, but vulnerabilities that remain potentially limit the data's usefulness for safety analysis," the GAO stated.

How it overcomes such difficulties are key to the agency's goal of being more proactive in its data research and aviation safety recommendations. That program, known as the Safety Management Systems (SMS) is the FAA's plan to analyze data to identify and mitigate risks before they result in accidents. The GAO says the SMS system is a data-driven, risk-based safety program that heightens the importance of obtaining and using high-quality aviation safety data.

The GAO says the FAA faces some data-related challenges in including for example limitations with the analysis it conducts and the data it collects and the absence of data in some areas. For example, the GAO said the FAA does not have a process to track or assess runway excursions, which occur when an aircraft veers off or overruns a runway. Runway excursions can be as dangerous as runway incursions, which occur when an unauthorized aircraft, vehicle, or person is on a runway, and the FAA has tracked runway incursions for years.

The FAA said it is currently developing a program to collect and analyze runway excursion data and is drafting an order to set out the definitions and risk assessment processes for categorizing and analyzing the data. However, according to GAO's review of the FAA's plans, it will be several years before FAA has obtained enough detailed information about these incidents to assess risks.

Another challenge is gathering the right data from just a plethora of databases.

The FAA's effort to integrate aviation safety data — what's known as the Aviation Safety Information Analysis and Sharing (ASIAS) system, which connects 46 safety databases across the industry and has 45 participating airlines — is integrated into the Commercial Aviation Safety Team (CAST) process. ASIAS enables better safety information management and data sharing as it proactively extracts from public and non-public data sources, including accidents, incidents, and voluntary reporting. FAA has demonstrated the potential of using integrated safety data to better understand the causes of certain safety events and identify mitigating strategies, the GAO stated.

The GAO report outlines some of the databases the FAA collects data from, which include but are not limited to:

• Database: Aviation Safety Information Analysis and Sharing (ASIAS)

Responsible entity: FAA

Description: Integrates aviation safety data from 46 safety databases and 45 participating airlines

Safety-related data collected: Accidents, incidents, advisory information, aircraft information, statistical data

• Database: Air Traffic Quality Assurance (ATQA) database

Responsible entity: FAA

Description: Contains information recorded by air traffic controller supervisors, support specialists, and managers

Safety-related data collected: Surface and airborne incidents

• Database: Air Traffic Safety Action Program (ATSAP)

Responsible entity: FAA

Description: Non-punitive, voluntary safety reporting program for air traffic controllers

Safety-related data collected: Air-traffic controller safety issues, including loss of separation

• Traffic Analysis and Review Program (TARP)

Responsible entity: FAA

Description: Error detection system that automatically captures data on airborne losses of separation

Safety-related data collected: Airborne losses of separation that occur while the aircraft is under the control of air traffic control towers and terminal radar approach controls

• Aviation Safety Reporting System

Responsible entity: NASA

Description: Industry personnel in the air and on the ground (e.g., air traffic controllers, mechanics, flight attendants, and ground crews)

Safety-related data collected: All types of safety events

• National Wildlife Strike Database

Responsible entity: FAA, USDA Pilots, air traffic control personnel, and others involved in civil aviation

Description/safety data collected: Bird and other wildlife strikes

• Near Midair Collision System (NMACS)

Responsible entity: FAA Pilots and other flight crew members

Safety-related data collected: Near midair collisions

• National Transportation Safety Board Aviation Accident and Incident Database

Description/safety data collected: NTSB investigators Aviation accidents and major incidents.

Considering what it has to deal with the GAO says the FAA has put in place data quality controls that it considers good practices for handling data. The FAA's Office of Aviation Safety established a data management framework that includes a four-step process for importing data from other FAA offices and external sources, the GAO stated. This process includes:

1. data acquisition — obtaining information from various data owners,

2. data standardization — validating data by comparing a new data set with previous data sets to identify inconsistencies,

3. data integration — translating data values into plain English and correcting data errors, and

4. data loading — importing data into the agency's own systems.

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