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.

AI-use policy. The one-page statement, approved at the top of the organization, of which tasks a model may assist, which uses are prohibited, which controls apply, and who owns each instrument.

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.

BM25. A keyword ranking function used by most search engines. It matches exact words and weights rare ones more.

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

Canonical name. The one name, with its acronym and identifier, under which a dataset's mentions are counted.

Citation validity. The share of citations in generated answers that resolve to a real record and support the statement they are attached to.

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.

Content-Oriented Guidelines. The SDMX guidelines that define cross-domain concepts (REF_AREA, TIME_PERIOD, OBS_VALUE, OBS_STATUS, UNIT_MEASURE, and others) and cross-domain code lists for reuse across statistical domains.

COUNTER Code of Practice for Research Data. Rules for logging and reporting dataset views and downloads, including the separation of machine access from regular access.

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

Croissant. The MLCommons format, built on schema.org, for describing a machine-learning dataset so that tools can load it: its files with their checksums, the fields of each record, and the splits.

Crosswalk. A mapping from one classification to another, for example from a national occupation classification to ISCO.

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.

DCAT. The Data Catalog Vocabulary, a W3C standard for describing data catalogs and their datasets in machine-readable form so that catalogs can be harvested.

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.

DDI Codebook. The Data Documentation Initiative standard for documenting a study and its variables; the World Bank microdata schema is its JSON form.

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

Dense retrieval. Search that represents queries and records as numeric vectors (embeddings) and ranks by similarity of meaning.

Disclosure control. The measurement and reduction of the risk that a released file identifies a person or business or reveals something about one: removal of identifiers, top-coding, coarsening of geography, suppression of rare combinations; applied before any release.

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.

Embedding. A list of numbers that a model assigns to a text so that texts with similar meaning have similar numbers; the basis of search by meaning.

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

Exit plan. The steps by which an AI component would be switched off or moved to a second model or provider, tested once on the component's evaluation suite.

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.

Gap. The distance between a dimension's current level and its target, measured in levels and in the number of questions below the target's value.

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

Grader. A language model, with a rubric, that scores answers the automatic checks cannot score; validated against human scores before use.

Grader (judge). A language model that scores answers with a rubric where no script can; validated against human scores before use.

Grounding. Restricting a language model to what was retrieved or given for the task: an answer that uses only the retrieved records, a draft that uses only what the record and its named sources support.

GSBPM. The Generic Statistical Business Process Model, the UNECE reference model of the phases and sub-processes of statistical production, from specifying needs to disseminating and evaluating.

Hallucination. A statement in a generated answer that has no support in the retrieved material.

Harmonization. The matching of mention variants to canonical identifiers.

ISCED. The International Standard Classification of Education, whose levels classify educational attainment.

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.

JSON-LD. JSON with a vocabulary attached, so that each key has a defined meaning that different tools read the same way; the format in which schema.org and Croissant records are embedded in web pages.

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.

LLM. Large language model. A model that generates text, used here for drafting metadata, answering questions, and grading.

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.

MCP. The Model Context Protocol, the open standard through which AI applications discover and call tools, read resources, and use prompts offered by a server, such as a statistics API.

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.

Model Context Protocol (MCP). An open standard through which AI assistants discover and call an organization's tools and read its resources.

MRR. Mean reciprocal rank: 1 when the right item comes first, one half when it comes second, and so on, averaged over the questions.

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.

nDCG@k. Normalized discounted cumulative gain at k. A retrieval measure that credits partially relevant results and rewards placing the best ones first.

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.

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.

OpenAPI. The standard way to describe an API in a file: which addresses exist, what parameters they take, and what they return.

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.

Prompt. The instructions and context given to a language model for one task; kept as a versioned file when it is part of a workflow.

Prompt injection. Text placed in content a system reads (a document, a web page, a query) that is written as an instruction to the model in the hope that the model follows it; tested for before release.

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.

Read-only. A tool that reads and returns data and has no path to change anything; the property the server's safety rests on.

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

Recall@k. The share of questions for which the right item appears in the first k results.

Report card. A run's scores per slice with intervals, the set version, and the component versions, published with a release.

Required score. The suite score a task's model has to reach, set from the cost of error before any candidate is tested.

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.

Semantic search. Search by meaning; see dense retrieval.

SKOS and XKOS. SKOS is the web standard for publishing controlled vocabularies (concepts with labels and identifiers); XKOS extends it for statistical classifications and their correspondences.

Small model. A model of roughly one to fifteen billion parameters that runs on one GPU or on CPU, enough for narrow tasks with the right context.

Stable identifier. An identifier for a series or dataset that does not change across releases or site redesigns.

Statement of model use. The section of a release's quality report that says where models were used, which, how they performed, who decided, and what the effect was.

Statistical disclosure control. Methods that prevent the identification of individuals from published data.

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.

Suite. A question set, the scripts that score it, the required scores, and the record of runs.

Switch-off test. The test that production proceeds with the model layer stopped, with the fallback per task exercised.

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.

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.

Tool use. The ability of a language model to call functions or APIs during an answer, so that values come from the source.

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

Universe. The population a variable applies to, as the question was asked.

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

Variable group. A DDI structure that organizes variables by theme for navigation.

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.

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.

World Bank metadata schemas. JSON Schema definitions published by the Development Data Group for indicators, microdata, documents, geospatial data, tables, images, scripts, and videos, used by its catalogs and the Metadata Editor.

XKOS. The DDI Alliance extension of SKOS for statistical classifications and the correspondences between them.

Zero-shot model. A model that performs a task from a description of the labels alone, without examples of that task in its training.