Finding data in ARAD

Start from a scope

ARAD metadata endpoints are scoped. Supply exactly one of a set, base, selection, or indicator selector when the endpoint requires it.

library(aradR)

catalog <- arad_catalog(set_id = 1058, lang = "en")

arad_catalog() returns one row per indicator and can enrich the basic metadata with hierarchy paths and availability information.

Search human-readable metadata

Use arad_find() when you know what you are looking for conceptually but do not know the indicator code:

hits <- arad_find(
  "inflation",
  set_id = 1058,
  lang = "en"
)

The search covers indicator IDs and names, hierarchy paths, and—by default—dimension metadata. Results are ranked deterministically.

hits[, c(
  "indicator_id",
  "indicator_name",
  "relevance_score",
  "matched_in"
)]

matched_in explains whether the term matched the indicator ID, indicator name, hierarchy path or dimensions. The numeric relevance score is only an ordering device for the current query; it is not a measure of statistical importance.

Narrow by frequency

When a scope contains several frequencies, filter during discovery:

monthly <- arad_find(
  "households",
  base_id = "MBOP",
  frequency = "M",
  lang = "en"
)

Inspect before downloading

Once you have plausible candidates, inspect them before retrieving observations:

info <- arad_info(hits$indicator_id[1], lang = "en")

info$summary
info$dimensions
info$updates

The summary includes hierarchy and ARAD-reported availability. data_to can include a future forecast or reporting horizon, so do not automatically interpret it as the latest observed historical date.

Use the lightweight search when appropriate

arad_search() is faster and simpler when searching only basic indicator names and IDs is sufficient:

quick_hits <- arad_search(
  "inflation",
  set_id = 1058,
  lang = "en"
)

A practical rule is:

• use arad_catalog() to browse a scope;
• use arad_find() for human-readable discovery;
• use arad_info() to inspect candidates;
• use arad_search() when you only need a lightweight name/ID filter.

Retrieve the selected series

After discovery, pass the selected ID directly to arad_get():

x <- arad_get(
  indicator_ids = hits$indicator_id[1],
  from = "2020-01-01"
)

This keeps discovery and retrieval separate: first decide what the series represents, then download the observations needed for the analysis.