AidOps
When multiple agencies assess the same population, their data should be comparable. AidOps provides structured definitions for the observations, measurements, and scores that humanitarian programs collect. Start here; adapt for your operation's context.
What the schema contains
AidOps is a shared set of definitions for humanitarian field data. It is not a data collection tool, a survey platform, or a reporting framework. When one agency records a food consumption score and another records a coping strategy index, the schema specifies exactly what fields to expect, what values are valid, and how scores are derived. Each definition has a permanent web address. Everything is optional: adopt the parts that fit your operation and leave the rest.
Concepts & Properties
3 concepts, 99 properties Structured profiles for field observations: nutrition screening, food security assessment, and shelter damage surveys. Each concept carries named, typed properties (muac, fcs_score, damage_level) defined once and reused. Core building blocks like Person, Household, and Location come from PublicSchema, so you don't redefine what's already standard.
Based on WFP (FCS, rCSI, CARI) · FAO (HDDS, FIES, MDD-W) · WHO (Growth Standards) · SMART · Washington Group
Vocabularies
22 vocabulariesControlled value sets for fields like food group categories, coping strategies, MUAC bands, damage levels, and shelter types. Where standard instrument definitions exist, we encode them. Where coding varies across agencies, we define a common set informed by field practice and standard instruments.
Why shared definitions matter
Three agencies run nutrition screenings in the same district after a flood. All three measure MUAC in millimeters, but Agency A classifies using standard WHO cutoffs (green ≥ 125 mm, yellow 115–124 mm, red < 115 mm). Agency B records weight-for-height z-scores using WHO 2006 growth standards instead of MUAC. Agency C measures MUAC but applies a modified national protocol where "severe" starts at < 120 mm instead of < 115 mm.
| Agency | Measurement | Classification |
|---|---|---|
| Agency A | muac (mm) | WHO standard cutoffs (< 115 severe, 115–124 moderate) |
| Agency B | weight_for_height_z | Continuous z-score (WHO 2006) |
| Agency C | muac (mm) | Modified national cutoffs (< 120 severe, 120–134 moderate) |
Same district. Three agencies. The raw measurements may overlap, but the classifications diverge.
The nutrition cluster coordinator needs a consolidated picture for the district. Today that means weeks of manual harmonization: mapping codes, reconciling cutoffs, guessing at equivalences. It is expensive, error-prone, and starts over when the next assessment round begins.
Spreadsheet crosswalks can reconcile naming differences, but they cannot recover information that was never captured in a comparable way. You cannot reconstruct z-score distributions from color bands, and modified cutoffs mean "severe" in one dataset does not match "severe" in another. Shared definitions do not just save time; they make accurate consolidation possible in the first place.
AidOps does not prescribe which measurement or cutoff is correct. It gives you a common reference so you can see exactly where agencies diverge, decide what fits your context, and extend it where your operation needs more.
Choose your path
Where to start
“I coordinate assessments across agencies”
You need consolidated nutrition, food security, or damage data from multiple partners to feed into your HNO or cluster reporting. AidOps gives you shared definitions so data from different agencies can be compared and merged without ad hoc mapping.
“I design data collection forms”
You need field names, value codes, and scoring rules that align with standard instruments (FCS, MUAC, rCSI). Use AidOps definitions in your KoboToolbox or ODK form design so your data is interoperable from the start.
“I build or maintain a humanitarian data platform”
You need a canonical data model for assessment and profile data. Map your KoboToolbox, DHIS2, or custom platform fields to AidOps properties once; partner data flows in without custom transforms.
“I need to produce cluster or donor reports”
You need to aggregate field data collected by multiple implementing partners into sitrep inputs, HNO sector annexes, or donor reports. When all partners use the same field definitions and value codes, aggregation is straightforward.
“I run assessments for a national authority”
Your ministry runs its own nutrition surveys, disaster assessments, or social registry updates. You need your national data to be understood by the humanitarian coordination system without losing national classifications. AidOps gives you a bridge: map your national protocol once, and cluster partners can read your data directly.