NOTAM_DRAFT_SOO.pdf

DRAFT STATEMENT OF

OBJECTIVES (SOO)

NOTICE TO AIR MISSIONS (NOTAM)

AERONAUTICAL INFORMATION (AI)

In support of the

FEDERAL AVIATION

ADMINISTRATION

Air Traffic Organization

October 24, 2023

U.S. Department of Transportation - Federal Aviation Administration

NOTAM Statement of Objectives Page i

Table of Contents

1 INTRODUCTION

1.1 PURPOSE

1.2 BACKGROUND

2 CURRENT STATE CHALLENGES

3 FUTURE STATE OBJECTIVES

4 IMPLEMENTATION APPROACH

5 SUMMARY

AI & NOTAM Statement of Objective Page 1

1 Introduction

1.1 Purpose

The Federal Aviation Administration (FAA)’s mission is to provide the safest, most efficient aerospace system in the world. To ensure the safety and efficiency of our national airspace system (NAS), it is imperative that users have access to accurate information describing the current state of the NAS to inform their decision-making. A large component of this NAS information can be categorized as Aeronautical Information (AI), a subset of which are notices to air missions (NOTAM). Today, the FAA is facing significant challenges managing the current state lifecycle of AI and NOTAM systems. To resolve these challenges and better position us for the future of the NAS, the FAA is seeking modern, innovative solutions from industry to aid in the management of AI and NOTAM systems.

In this document, the FAA provides a brief background on AI and NOTAM, describes the high-level challenges of the current environment, and lays out the FAA’s current objectives for a desired future state.

1.2 Background

Aeronautical Information 101: AI includes static (permanent) and dynamic (temporary) information about airspace, airports, navigation aids, and air traffic procedures. AI is the information that pilots, air traffic controllers, and other aviation professionals rely on for flight planning, navigation, and safety.

The FAA publishes this information in aeronautical charts, publication databases, data feeds, and other products. AI enables aviation professionals to make informed decisions, respond to changing conditions, and navigate the complexities of the NAS environment.

AI is subject to constant change due to factors such as revisions in airspace structures, air traffic routes, alterations in navigation aids, changes to runway and taxiway information, modifications to instrument flight procedures, weather condition variations, and many others. Changes to AI may be either permanent or temporary in nature. These changes are published in different formats including Aeronautical Information Publications (AIPs), Aeronautical Information Services (AIS) online portals, and NOTAMs. AIPs and AIS portals primarily deal with static data and are published following an Aeronautical Information Regulation and Control (AIRAC) cycle (every 28 or 56 days). NOTAMs are dynamic in nature and are notices issued to alert NAS users of temporary changes to published AI concerning the establishment, condition, or change of any facility, service, procedure, or hazard in the NAS, indicating the real-time status impacting airspace users and operators.

Ensuring the availability of accurate and timely AI is a foundation of aviation safety, efficiency, and reliability.

AI Lifecycle: Though there are different workflows, rules, and policies governing permanent changes to static AI and temporary changes to dynamic AI (like NOTAMs), the AI lifecycle encompasses three core phases: origination, management, and distribution.

• Origination: The identification and reporting of permanent or temporary AI changes to the FAA

• Management: The application of business rules and review/approval workflow to ensure AI policy compliance

• Distribution: The provision of AI to a diverse set of stakeholders for operational decision-making and situational awareness

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Global modernization of AI: The limitations and challenges of managing AI using traditional AIS products are widely acknowledged within the global airspace community. For example, traditional AIS products were originally intended for human consumption, resulting in primarily textual data. This textual data limits automation opportunities, leaving end users to deal with the challenge of distilling an overwhelming amount of information to inform their operational decision-making. With NOTAMs, the volume of temporary changes to AI has nearly tripled in the last decade, increasing the burden on pilots, controllers, and other aviation professionals to quickly identify critical information and maintain situational awareness.

These challenges have prompted the global transformation of AIS into Aeronautical Information Management (AIM), where real-time standards-based digital AI replaces traditional charts and paper publications. The transition to AIM has included the development of the International Civil Aviation Organization (ICAO) recommended Aeronautical Information Exchange Model (AIXM1) to globally harmonize and standardize the exchange of AI. AIXM was developed to address global challenges and standardize the management of static and dynamic AI. It achieves this by introducing a structured format and a temporality framework for digitally representing permanent and temporary changes in AI.

This facilitates a standardized and efficient way of capturing, exchanging, displaying, and transforming AI. AIXM is an enabler in realizing the global modernization of AI and provides an underlying specification for the integrated management of permanent and temporary (NOTAM) changes to AI.

The paradigm shift from a focus on products to a focus on digital data allows for nearly endless improvements in the end uses of the underlying AI. It allows for efficiencies, increased situational awareness, and opportunities for innovation in meeting a wide range of needs for all airspace users.

2 Current State Challenges The current operational environment for managing AI is fragmented and involves more than a dozen systems, each operating independently within its own distinct environment(s). The current systems were designed in the product-based AIS era to operate independently with their own unique data collection, management, and distribution interfaces, along with their own set of business rules and workflow processes that are deeply ingrained within the system. As a result, the output from these systems is in different formats, and requires additional processing from both internal and external systems to collate and harmonize the data and achieve complete situational awareness. Figure 1 provides a conceptual view of the current FAA systems managing AI.

1 https://aixm.aero/ https://aixm.aero/

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Figure 1: Current FAA Aeronautical Information Systems

These systems support data processing covering the entire spectrum of AI. This spectrum includes but is not limited to:

• Civil and Military use airports and heliports information

• Communications, navigation, and surveillance equipment

• Air Traffic Facility data

• Instrument Flight Rules, Visual Flight Rules, and Controller Route information

• Obstacle data and airspace evaluations, and

• Airspace definitions, status, and temporary flight restrictions

While the systems depicted in Figure 1 manage the static part of the AI, temporary changes for these aeronautical features issued as NOTAMs are supported by two interconnected systems that provide support for the entire NOTAM life-cycle through human and machine interfaces, as shown in Figure 2.

This current system environment involves a mixture of software components, multiple standalone databases, and legacy infrastructure components. For example, there are nine distinct tools for originating NOTAMs, and seven different tools are used for distribution. Although most NOTAMs are initiated through one system, they rely on a different legacy system for numbering and validation.

Likewise, the NOTAM Office, which serves as the ultimate authority for publishing and reviewing NOTAMs, depends on a two-decade-old desktop tool with limited functionality for reviewing and managing all NOTAMs processed within the system. Each independently deployed legacy system requires its own dedicated operations and management framework and include client-server and web applications. This complex configuration has given rise to considerable operational and maintenance challenges.

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Figure 2: Current FAA NOTAM systems

The current NOTAM systems were originally developed to produce textual NOTAMs for human consumption and were intended to alert pilots and controllers about temporary changes to published data. Like most traditional AIS products, the current NOTAM systems have limited automation options, and do not allow for effective filtering and sorting of information relevant to a specific route of flight.

Over time, the volume of NOTAMs has grown substantially, which makes it increasingly difficult for pilots, controllers, and other air traffic customers to quickly identify critical information while maintaining situational awareness.

Despite these challenges, the current suite of systems that support the origination, management, and distribution of NOTAM and AI supports a diverse group of domestic and international stakeholders.

These independent and interconnected data systems consistently maintain high operational availability and efficiently process a substantial volume of NOTAM and AI transactions. The stakeholders of these platforms include but are not limited to: airports; FAA’s Technical Operations office (which operates and maintains the communications, navigation, and surveillance equipment); FAA Aeronautical

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Information Services offices; the US Department of Defense; other government entities, and obstacle tower operators. These stakeholders create nearly 2 million NOTAMs annually, a figure that increases to over 3.5 million when international NOTAMs are included. All NOTAMs are managed and processed within the current systems before being distributed to the aviation community via human and machine interfaces.

The current objective is to transition these programs, systems, and services from the AIS product-based era in which they operate on legacy hardware infrastructure, to an innovative, modern, and resilient computing platform that enables real-time digital AI gathering and sharing using globally harmonized standards in alignment with the FAA’s vision of an Info-centric NAS.

3 Future State Objectives The FAA seeks to consolidate the current array of legacy AI systems into a streamlined digital platform that enables the origination, management, and distribution of AI as a set of events of aeronautical features. This platform will replace the current standalone separate set of products and allow NOTAMs to be considered a temporary (short-term) event and other more significant AI changes to be a permanent (or long-term) event.

The FAA envisions an integrated AIM platform that augments its current ability to provide efficient, timely, and on-demand access to data-driven products and information and better positions the NAS for the future. This modern platform should seamlessly integrate both static and dynamic aeronautical data updates, providing a comprehensive view of the airspace system at both a specific moment and over a defined time frame. It should leverage advancements in technology to replace manual processes with automation and possess the capability to identify anomalies or deviations to assist users in the origination, management, and distribution of AI through configurable workflows and business rules.

The FAA’s desired future state involves a comprehensive digital AI solution that:

1) Supports the lifecycle management of static and dynamic AI, including origination, management, and distribution functionality

2) Provides flexibility and scalability for future requirements to support the growth of new and emerging users of the NAS

3) Enables the near real-time global standards-based exchange of AI, and

4) Uses modern scalable and resilient software architectures, practices, and technologies.

To realize this future state vision, the FAA is seeking innovative ideas and solutions through engagement with industry that achieves the following objectives:

Architecture

• Uses a modular architecture for the integration of static and dynamic AI that facilitates updates and changes.

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• Significantly reduces the complexity of the current AI systems and interface architecture for full lifecycle management of AI.

• Involves an expandable architecture that supports incremental inclusion of AI functionality, with NOTAM architecture as an initial phase and future phased updates of static functionality

• Uses a modern scalable and elastic architecture that operates reliably across diverse hosting environments. The solution should prioritize consistency, portability, and efficiency in resource utilization while also supporting swift, secure, and flexible deployment and scaling in an agile and dynamic IT landscape.

• Integrates with existing and future FAA systems, services, infrastructure, and programs.

• Prioritizes availability, reliability, and resiliency to minimize downtime and withstand failures caused by natural and human-made events.

• Looking for an innovative and creative solution architecture that leverages advancements in the industry including open-source and non-proprietary options. Open to modern offerings including (but not limited) to no-code/low-code and other offerings that provide a future-proof solution that is easy to operate and maintain.

Interfaces

• Provides both human and machine interfaces for AI origination, management, and distribution functionality.

• Maximizes automation using standard interfaces whenever possible.

• Provides a user experience (UX) based on industry best practices.

• Uses intuitive and interactive user interfaces to include textual and graphical elements.

• Supports all modern browser platforms (without additional plug-ins or downloads).

• Uses industry recognized open standards-based machine interfaces (e.g., APIs, etc.) for exchanging information interfaces between systems.

AI Data Management

• Encodes static and dynamic AI, including geospatial data elements, in appropriate AIXM elements without users possessing in-depth AIXM model knowledge.

• Uses AIXM digital event scenarios to encode specific temporary events (NOTAMs).

• Allows for the integration of temporary (NOTAM) changes to permanent AI using the AIXM temporality model.

• Uses AIXM digital event scenarios to encode specific temporary events (NOTAMs).

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• Supports current FAA domestic format and enables the transition to ICAO formatted and Plain Language description of NOTAMs via digital transformation.

• Ensures currency of baseline static AI, published in various timeframes based on specific data types, including the standard AIRAC cycle (28/56 days). This solution should include an initial NOTAM capability, the design of the baseline data management should consider the future full integration of static AI management in the same solution.

• Supports robust metadata management.

• Uses a storage approach that allows for up to 3 years of AI and NOTAM data immediately accessible by external systems and users for analysis or visualization.

• Employs a robust data management strategy to ensure data integrity and quality.

• Integrates with advanced data analytics capabilities such as machine learning, including internal data analytics capabilities and external integration with data lakes and third-party analytics tools.

AI Lifecycle Management

Origination

• Supports end-to-end lifecycle (origination, management, and distribution) processing of AI changes, whether permanent or temporary.

• Supports origination of AI changes, whether permanent or temporary, at the source through digital data capture.

• Supports automated NOTAM origination triggered by events (e.g., automated issuance of NOTAM for navigational aid maintenance).

• Allows authorized originators to directly manage and issue NOTAMs without review when they use business rule-driven digital event specifications.

• Supports AI lifecycle processing for non-digital (free text) NOTAM in cases where a digital NOTAM alternative may be required.

• Explore using machine learning algorithms to support and streamline the creation of free-form NOTAMs when digital events are unavailable.

Management

Workflow

• Supports flexible and dynamic workflows that seamlessly combine automated, business rule-driven processes with manual user intervention as necessary.

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• Supports configurable workflows by authorized users without a software release.

Business Rules

• Supports configurable business rules by authorized users, as needed and without a software release.

• Enables the management of changes, additions, or deletions to digital NOTAM scenarios without software code changes.

• Provides flexibility to accommodate anticipated regulatory, standards, and technology changes. Including updates to the current FAA’s NOTAM Order 7930.2 to fully adopt ICAO NOTAMs.

Validation

• Validates submitted AI changes against current and, when created, future business rules and policy.

• Publishes AI changes only following validation by applicable business rules and workflow for the type of AI change.

• Explore the use of advanced analytical and machine learning techniques to help improve accuracy of data and reduce manual review especially for free-text NOTAMs.

User Administration

• Allows integration with Single Sign-On authentication solutions with support for protocols like Security Assertion Markup Language (SAML), OAuth, OpenID Connect etc.

• Ensures role-based user authorization throughout the AI lifecycle workflow.

• Supports decentralized user management (e.g., administrators at local facilities can manage access for their facility).

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Distribution

• Distributes AI changes to NAS users based on the time-sensitivity of the type of change.

o Supports a defined publication cycle for static AI.

o Supports immediate distribution of dynamic temporary NOTAM information.

• Supports flexible features for searching, filtering, sorting, and analyzing active and historical AI and NOTAM data.

• Provides access and visibility to digital geospatial data, including temporary events and permanent data, to enable informed operational decision-making.

• Provides a graphical representation of AI and NOTAM data within the human interface.

• Provides legacy formats for aeronautical products aligned with a deprecation roadmap (e.g., Subscriber Files).

• Provides data query and reporting capability.

Security

• Ensures multi-factor authentication for all human and machine interfaces.

• Complies with Zero Trust Architecture (ZTA).

• Implements Identity, Credential, and Access Management (ICAM) standards.

• Implements required access controls (e.g., role-based).

• Supports user authorization and permissions using least privileged access principles.

• Solution(s) that ensure data security in transmission and in storage while restricting data using least privileged access ZTA principles and allow authorized originators to directly manage and issue the required temporary change notifications without review, especially when they use digital event specifications.

• Solution(s) should meet the Federal Information Security Management Act (FISMA) security controls for a high-impact system.

• Cloud-based solutions must follow FedRAMP requirements.

Monitoring

• Supports industry-standard capabilities for real-time monitoring, alerting, and reporting of health, performance, and security status.

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• Provides flexible reporting of key performance indicators (KPIs) for solution health and performance.

Performance:

• Maintains a high level of availability by keeping downtimes to a minimum and guaranteeing reliable and uninterrupted services. It should be designed to endure various forms of failures, including hardware, software, network issues, human errors, and external disruptions.

• Achieves a fault tolerance design to gracefully handle faults, errors, and unexpected failures to minimize operational disruptions.

• Accommodates growth in system usage while maintaining service performance levels that do not require a disproportionate increase in resource consumption.

o Supports human UI interaction at the rate of at least fifty (50) million hits per month for NOTAMs.

o Supports machine transactions with processing latencies under 30 seconds with variable user workloads without affecting performance.

o Scales to accommodate daily volumes ranging from 3,000 to 18,000 AI changes and up to 50,000 NOTAMs without degrading performance.

Industry Partnership

In addition to the technical objectives listed above, FAA seeks a partnership with industry that achieves the following:

• A strong, high performing, mutually beneficial partnership based on clear, mutual accountabilities.

• Delivery of services firmly aligned with FAA’s dynamic business requirements.

• Alignment of organizational roles and responsibilities to effectively leverage resources, maximize organizational efficiency, and deliver continuous improvement.

• Proactive communication.

• A continuous improvement approach that encourages transparency, the incorporation of lessons learned, and consistent reduction in solution delivery time, costs, and defects.

• Process and quality management methodologies that incorporate industry-leading practices, standards, and innovations.

• Proactive risk identification and mitigation.

• Development and maintenance of a guiding roadmap for all program activities that addresses

AI & NOTAM Statement of Objective Page 11 activities related to solution architecture, design, development, integration, testing, training, configuration management, deployments, impacts on legacy AI systems, and operating and maintaining infrastructure and applications to meet FAA future state objectives.

• Execution of a program performance management framework that ensures desired outcomes are achieved through objective service level metrics, key performance indicators, customer satisfaction measurements, and executive performance indicators.

• Substantial visibility into the status and health of system operations.

• Implementation of a cost-effective and affordable program cost structure that ensures rates remain competitive with market rates throughout the contract lifecycle and pricing structure mitigates transition cost spikes. Provide visibility into program cost drivers; deliver year-over-year unit cost reductions to the FAA and support an equitable allocation methodology to share cost increases and cost savings resulting from changes in technology and business needs.

• Sustained knowledge of industry-leading information technology (IT) state-of-the-art practices and innovations, including hosting, applications, processes, and tools. Propose the insertion of new capabilities to optimize solution environment performance.

• Commitment to customer satisfaction.

4 Implementation Approach The FAA is searching for an innovative and flexible solution that is modular, easy to maintain, and adaptable to changing requirements. The system should be designed to minimize custom code, reduce reliance on proprietary code, and provide user-configurable workflows and business processes to reduce lifecycle costs.

To achieve this objective, the FAA is exploring a contemporary service delivery model that allows for assessing the vendor's ability to deliver a solution within program parameters. This approach could include the delivery of a Minimum Viable Product (MVP) and subsequent deliveries with testable functionality to receive early user feedback on the solution. The desired solutions should have a system architecture and design to integrate with other systems, exchange data, and provide future enhancements.

The transition towards this future state could be in phases, with NOTAMs serving as the initial foundation for this transformation. The solution could be implemented in phases where NOTAMs are created in compliance with FAA's NOTAM policy 7930.22. This could be accomplished by representing the temporary events through a digital message and automatically generating NOTAM text via transformation. This would eliminate the need for an originator to create the NOTAM text manually. Additionally, the digital platform should allow for the management and distribution of NOTAMs in human-readable messages in plain language to facilitate the transition away from the current all-caps-based contractions. The key is that the designed platform can be expanded to manage the static state of aeronautical features.

2 https://www.faa.gov/regulations_policies/orders_notices/index.cfm/go/document.information/documentID/1035053 https://www.faa.gov/regulations_policies/orders_notices/index.cfm/go/document.information/documentID/1035053

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5 Summary The FAA continues to provide accurate and timely AI and NOTAMs to its NAS users but recognizes the challenges of the current AI and NOTAM environments. To address those challenges, the FAA envisions a future state that allows for the comprehensive management of AI across the NAS. The FAA is looking for a secure, innovative, and flexible platform that meets the core objectives outlined in this SOO to bring this vision for AI origination, management and distribution to fruition in a modern environment.

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Table A–1: Abbreviations, Acronyms, and Terms

Acronym Definition

AI Aeronautical Information

AIM Aeronautical Information Management

AIPS Aeronautical Information Publications

AIRAC Aeronautical Information Regulation and Control

AIS Aeronautical Information Services

AIXM Aeronautical Information eXchange Model

API Application Programming Interface

FAA Federal Aviation Administration

ICAM Identity, Credential, & Access Management

ICAO International Civil Aviation Organization

IT Information Technology

KPI Key Performance Indicators

NAS National Airspace System

NOTAM Notice to Air Missions

SAML Security Assertion Markup Language

SOO Statement of Objectives

UX User Experience

ZTA Zero Trust Architecture