Roster history
Published, revised and actual duties. Source and timing retained.
MAFRM / 04
Data & integrations
Connect the schedule
with the real world.
MAFRM’s data roadmap brings operational history and independent observations alongside model-based indications, with clear provenance, consent and access boundaries.
The data ecosystem
Different sources.
Different kinds of evidence.
Useful integration starts with a clear source, authorised access, understood limitations and an interpretation suited to the decision.
Rules & assumptions
Versioned requirements, model configuration and data-quality checks.
Scenario inputs
Isolated alternatives, each compared with the same baseline.
Continuous, explainable analysisSeparate roster checking and fatigue modelling · Reproducible run identity
Review & compare
Duty-level explanations, downstream effects and population patterns.
Independent observations
Sleep diaries, wearables, fatigue ratings and functional tests.
Evaluate & improve
Validation layer with frozen predictions kept separate.
Integration roadmap
Airline roster systems.
Authorised provider adapters are being designed to ingest published duties, amendments, reserve and standby activity, actual duty records and historical rosters.
Each connection depends on the provider’s capabilities, operator agreements, permissions and implementation arrangements.
Selected user-supplied workbook and JSON imports are supported today. Live connections will be introduced through authorised, provider-specific integrations.
Data lineage roadmap
Historical duty information.
Preserving the originally published roster, later revisions and actual duties supports analysis of what changed, when it became known and how the model response changed.
The data-lineage roadmap adds a canonical event history, repeatable imports and traceability from source records through recalculation.
Observation sources under evaluation
Wearables, with context.
The following sources are being evaluated for suitable observations. Each integration depends on access, consent, data quality and the question being examined.
WATCH / HEALTH
Apple Watch & Apple Health
Under evaluationSuitable sleep and physiological records may be available through an authorised mobile data flow.
WEARABLE
Garmin
Under evaluationActivity, sleep and physiological observations may contribute where provider access, participant permission and dataset suitability align.
RING
Oura Ring
Under evaluationSleep timing and other supported observations may contribute subject to API access, consent and evaluation of the available measurements.
ACTIGRAPHY
Research devices
Under evaluationDedicated actigraphy and physiological monitoring may suit specific study protocols, selected for the research question and measurement quality.
CUSTOM HARDWARE
Purpose-built collection
Under evaluationPurpose-built collection may support a defined requirement that cannot be met by existing tools, with its own design and evaluation pathway.
PARTICIPANT INPUT
Diaries & observations
Under evaluationSleep diaries, KSS and Samn–Perelli ratings can be combined with functional testing under an appropriate research protocol.
Data responsibility
Useful evidence starts
with clear boundaries.
Consent, purpose limitation, data minimisation, confidentiality and appropriate access are core design requirements for the platform.
Participant identities, identifiable rosters, health-related observations and organisation-level outputs will be separated where appropriate, with de-identification assessed against the context of each dataset.
Hosted identity, consent records, retention controls and multi-organisation security form part of the implementation and verification program. Collection will proceed under agreed protocols and verified controls.
Explore observation and validation designHelp shape what comes next
A better question starts
with a conversation.
Developing a roster proposal, investigating an operational pattern or planning fatigue research? Let’s explore where MAFRM could contribute.