Glossary

Agent. An AI system that calls tools to complete a task; here an assistant that calls the organization's data API or MCP server to answer a question about statistics.

AI visibility check. A fixed set of questions asked of AI assistants on a schedule, recording whether the organization is cited and whether the figures are right.

AI-ready. Data and metadata that software, including AI systems, can find, retrieve, interpret, and cite without manual steps. See the AI-ready data framework.

Annotation. Optional properties on a tool that describe its behaviour (for example that it is read-only); hints that clients treat as untrusted unless the server is trusted.

API. Application programming interface: the address at which a program asks a system for data and receives it in a structured form.

Benchmark (population). The share of each group in the population, from the census or population estimates, against which a dataset's composition is compared.

Bounding box. The rectangle that encloses a detected table or figure on a page, written as the left, top, right, and bottom edges as fractions of the page width and height, with the origin at the top left.

Candidate. A model shortlisted for a task, with its licence classified and its card checked, to be run on the suite.

Code list. A published table of the codes used in a dataset (for geography, periods, categories) with their labels. In SDMX, a code list is part of the data structure definition.

Component register. The table with one row per AI component the organization runs: owner, model, provider, data, human review, risk tier, approval and review dates, and exit plan.

Confidence. A number between 0 and 1 that a model returns with its output to say how sure it is; the basis of a threshold rule.

Coverage. The share of a reference list of known uses that the collected documents contain.

Data snapshot. The image of one table or figure cropped from a page, with its coordinates, class, and source document; the unit of extraction and of citation.

DataCite. The registration agency and metadata schema for dataset DOIs. The World Bank Microdata Library assigns DataCite DOIs.

DDI. The Data Documentation Initiative, the standard for documenting surveys and their variables, value labels, and files; the World Bank microdata schema is based on it.

Decision. A curator's recorded verdict on a suggestion: accept, edit (with the final text), or reject (with a reason).

Derived column. A table column computed from others, such as a rate from a numerator and a denominator; a check for extracted values.

Document record. The catalog record of a document in the World Bank document schema, with the series and surveys it draws on.

DOI. Digital object identifier, a persistent identifier registered with DataCite that resolves to a dataset or to one version of it, carries citation metadata, and makes citations countable.

Estimated. The status of an extracted value for which the document offers no check: no printed label, total, or derivation.

Fine-tuning. Changing a model's weights by training it further on the organization's own labelled examples, so that it does one task better or follows the organization's conventions.

Flagged. The status of an extracted value that failed a check and awaits correction with the page open.

Gate. The rule that decides whether a change ships, applied to a paired comparison of the evaluation suite before and after the change.

GPU. A graphics processing unit, the processor on which language models run fast; its memory decides which model fits.

Inventory. The list of documents with their type, year, page count, text-layer status, and counts of tables and figures.

Issue. The review pipeline's output: a detected problem with a category, a severity from 1 to 5, the current value, and a proposed value.

Known-item question. A test question with one expected identifier, known in advance, used to measure whether a search returns the right record.

Label. The column a model is trained to predict: the occupation code, the transcribed value, the series a question refers to.

Language model. A model that reads and writes text; used in these guides to draft, flag, code, explain, and translate, with a person deciding.

Layout detection. A model that finds regions of a page image and returns their class and bounding box.

Manifest. A file that lists the parts of something so that it can be checked or resumed: for a job, the records and their status; for a release, every file with its checksum; for an agent interface, the design document of its tools, inputs, outputs, examples, and resources.

Map. The table of model-assisted tasks with phase, role, review, data sensitivity, model location, and owner.

Maturity level. One of three states used in this guide: foundational, AI-ready, AI-native.

Mention. A reference to a dataset in a document, named or unnamed.

Metadata Editor. The World Bank's open-source application for documenting data of all the types in the World Bank schemas, with templates and validation, publishing to NADA, and export to SDMX and, for some data types, schema.org, Croissant, and DCAT.

NADA. The open-source data catalog from the International Household Survey Network, used for the World Bank Microdata Library. It supports DDI Codebook, Dublin Core, ISO 19115/19139, and IPTC. NADA AI, a service being integrated into NADA, adds semantic search and an MCP server over the catalog.

Number check. The comparison of every figure in an assistant's answer with the values of the source table, which marks each as verified or unverified before the answer is used.

OBS_STATUS. The SDMX observation status attribute, with codes such as A normal, P provisional, B break in series, E estimated.

OCR. Optical character recognition: reading text from the image of a page, which is what a scanned document needs before anything can be extracted from it.

Open-weight model. A model whose weights can be downloaded and run on the organization's own infrastructure, under a published licence that may be permissive or restricted.

Precision. The share of extracted mentions that are correct.

Precision and recall. Precision is the share of what a system found that is right; recall is the share of what is there that the system found. F1 is the average that combines the two.

Provenance. The record of where a value came from: the series, the release, the source, the document and page, the method, and the version, carried with the value.

Provenance fields. The fields every data response carries: series identifier, reference area, unit, release date, source URL, licence, citation, and observation status per value.

RAG. Retrieval-augmented generation. A pattern where the system retrieves records first and the model writes the answer from them.

Recall. The share of labelled mentions that the extractor found.

Resource. Context a server offers to the model or the user, such as code lists or a release calendar, identified by a URI.

Review board. The interface in which a curator sees the current and proposed values as a diff and decides.

Roles. What a model may do in production: flag, propose, code, explain, draft. It does not decide.

Rubric. A written scale that says what each score means, so that two people, or a person and a model, score the same thing the same way.

schema.org. A vocabulary that search engines agree on for describing things on web pages; a Dataset record in it, embedded in a page, is how dataset search engines learn what the page is about.

schema.org Dataset. A vocabulary for describing datasets on web pages, read by general crawlers and dataset search engines.

SDMX. Statistical Data and Metadata eXchange, the standard for exchanging aggregate statistical data, their structure, and code lists; its concept names (SERIES, REF_AREA, TIME_PERIOD, OBS_VALUE) are the column names of this series' data files.

Split. The division of a dataset into a training part (the model learns from it), a validation part (the model builder chooses settings on it), and a test part (touched once, to report a score).

Structured output. A model's answer returned as data in a declared shape (a JSON object with named fields that conforms to a schema) so that a script can validate, read, and aggregate it.

Table record. The catalog record of a statistical table in the World Bank table schema, with columns, rows, sources, definitions, citation, and relations.

Target level. The maturity level a dimension is to reach by the end of a planning cycle, set with a written reason and approved by the board.

Text layer. The machine-readable text inside a PDF; absent in scanned documents until OCR produces it.

Threshold. The value of a score (a confidence, a similarity, a garble rate) at which the rule changes what happens to an item; set from measurements.

Tidy data. A table layout with one observation per row and one variable per column.

Tidy file. A data file with one record per row, one variable per column, and the same columns in every row; for extracted data, one row per value with provenance columns (document, page, bounding box, class, title, row, column, value, unit, status).

Token. The unit in which language models read and write text, roughly three quarters of a word; prices, context limits, and throughput are counted in tokens.

Total row. The row of a table that sums the others; a check for extracted values.

Trace. The logged record of one question: tools called, series used, answer, whether the agent declined, latency.

Use. A document whose analysis, decision, or statement depends on the data, as opposed to a mention that cites them as context.

Variant. A way of naming a dataset other than its canonical name: an acronym, an informal name, a translation, a misspelling.

Verified. The status of an extracted value that matched a printed label, a total, a derivation, or a catalog value.

Vision-language model. A model that reads an image and returns text or structured output; used to extract chart data from snapshots.

Vocabulary. A concept scheme with preferred labels, alternates, and URIs, to which free-text keywords and topics are mapped.

Weight. A variable that scales each record to the population, with the calibration and the estimates it applies to documented.

Weight (survey). The number of population members a record stands for in a survey, kept as a column for population estimates; not a training weight by default.