Aeronautical data quality
DO-200B aeronautical-data quality support for equipment suppliers
DO-200B aeronautical-data support helps a supplier whose equipment processes navigation or aeronautical data assemble the data-quality evidence its certification depends on. It is used by avionics and database teams whose article consumes, transforms, or supplies aeronautical data. The work reviews the data chain, the assigned data quality requirements, and the integrity, resolution, and traceability evidence for each processing step. You receive a gap assessment against DO-200B and a structured data-process record ready for review.
When this review is needed
- A navigation or aeronautical-data function is being certified and the data-quality evidence has to be built against DO-200B.
- A data chain spans multiple originators and processors and the quality requirements at each handoff were never written down.
- A reviewer questions the integrity or resolution of supplied data and the substantiation cannot be located.
- A data process is being changed and the assurance argument has to be brought current before the next release.
The problem
Aeronautical data passes through originators, integrators, and processors before it reaches a display or a flight management computer, and the quality argument has to survive every handoff. Data quality requirements get set informally, integrity and resolution are assumed rather than substantiated, and the traceability from source to output breaks at a step nobody documented. A data process that cannot show its quality requirements draws questions that stall the program.
What gets reviewed
- The data chain from each originator through every processing step to the output
- Required accuracy, resolution, integrity, and timeliness assigned at each step
- The data process specification and how each step preserves the assigned quality
- Traceability from source data through transformation to delivered output
- Error detection, correction, and integrity-preservation mechanisms across the chain
- Tool assessment for software that processes the data without independent verification
- Records of agreements that fix responsibilities between data suppliers and users
What gets validated
- Quality requirements are assigned and recorded for every step in the chain
- Accuracy and resolution at the output meet what the consuming function requires
- Integrity is preserved end to end, with detection or correction where a step can corrupt data
- Each output value traces back to a source and the transformations applied to it
- Tools that process data without verification are assessed for the assurance they need
- Responsibilities at each handoff are fixed by agreement rather than assumed
- The data process specification matches the process that is actually run
Evidence normally required
- The data process specification and any quality requirements already assigned
- The list of data originators, integrators, and the handoffs between them
- Sample data sets and the transformation steps applied to them
- Tool descriptions for software that processes data without independent checks
- Existing agreements that allocate data responsibilities between parties
Common discrepancies
- Data quality requirements that were never assigned for an intermediate processing step
- Output resolution that is finer than the source data can actually support
- Integrity assumed across a handoff that has no detection or correction mechanism
- Traceability that breaks at a transformation nobody documented
- Processing tools used without an assessment of the assurance they need
- Supplier and user responsibilities that are undefined at a handoff
What is at stake
When the data-quality evidence does not hold, a reviewer cannot accept that the output meets the integrity and resolution the function needs, and the finding sits on the critical path. Each round of clarification costs schedule and pulls data engineers away from the release they were building.
Move from findings to resolution
Identify gaps against the means of compliance.
How the work runs
Map the data chain
Identify every originator, integrator, and processing step and the handoffs between them.
Assign quality requirements
Confirm accuracy, resolution, integrity, and timeliness requirements at each step against what the output function needs.
Trace and assess
Trace each output back to source through its transformations and assess the tools and integrity mechanisms involved.
Package the evidence
Produce a reconciled data process record and a prioritized list of the gaps to close.
What the buyer receives
- A gap assessment against DO-200B data quality requirements
- A data-chain trace from source through transformation to output
- A reconciled data process specification with assigned quality at each step
- A prioritized list of the integrity and traceability gaps to close
Who uses the output
- Certification leads preparing the data-quality argument for submittal
- Data engineering teams closing integrity and traceability gaps
- Program management sequencing the remaining data-process work
How the work fits into the transaction or program
The work supports the supplier's own certification of an aeronautical-data function. It strengthens the data-quality argument before submittal so questions about integrity and resolution are answered in the evidence rather than in review correspondence.
Start with a single asset
Confirm requirements trace through verification.
Regulatory limits
Endeavor Elements supports the applicant's data-quality evidence. It does not certify the data, originate aeronautical data on an authority's behalf, or guarantee that a data process will be accepted. The applicant and the authority retain their roles.
What this review does not cover
- Originating or publishing aeronautical data
- Issuing any approval or making official acceptance decisions
- Operating the data processing chain in production
Specific to this review
- DO-200B frames data quality across accuracy, resolution, integrity, and timeliness, and a gap in any one of these can invalidate the output even when the others are sound.
- Aeronautical data crosses originator, integrator, and processor boundaries, and the quality argument is most often lost at an undocumented handoff rather than inside a single step.
- Software that transforms data without independent verification of its output needs a tool assessment, which is a step suppliers frequently skip.
- Output resolution finer than the source data supports is a recurring finding, because resolution is treated as a display choice rather than a data-quality property.
Sources
U.S. Government (eCFR). Type certificates, STCs (Subpart E), TSO authorizations (Subpart O), PMA (Subpart K), and export airworthiness approvals (Subpart L).
RTCA. Objectives and lifecycle data for airborne software assurance, by design assurance level (DAL A-E).
Federal Aviation Administration. STC application process, certification basis, and continued airworthiness obligations of an STC holder.
Frequently asked questions
Does this cover the software that processes the data as well?
The data-quality work focuses on DO-200B. Where the processing software needs its own assurance, the engagement coordinates with the software lifecycle data rather than replacing it.
Can you help when the data comes from several outside originators?
Yes. A common engagement maps the responsibilities at each handoff, checks the agreements that fix them, and traces the quality argument across the originators into the supplier's process.
Relevant glossary terms
Related pages
Where this fits
Talk to an engineer who has done this work
We will walk through your current state, the records or evidence involved, and a scoped first engagement.
Walk through your situation with an engineer who has done this work.