Glossary

Access tier. A class of release conditions: public use file, licensed file, or secure access, each with its own disclosure control and agreement.

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.

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.

Client configuration. The settings a user pastes into an assistant to connect it to the server: endpoint, transport, credentials.

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.

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.

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).

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.

Feature. A column a model may use as input.

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.

Guidance resource. A resource that tells the model how to use the tools: search first, read metadata before interpreting, cite the source and release.

Harness. A program that sends questions to an agent connected to the server and logs the traces.

Incident. An AI component's output reaching a reviewer, a product, or a user with an error that the controls should have caught, or that a control caught at the last step; handled by a fixed procedure and recorded.

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.

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

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.

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.

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

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.

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

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.

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

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.

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.

Streamable HTTP. The transport for servers used over the network; stdio is the transport for servers run locally by a client.

Structured content. A tool result returned as JSON that conforms to the tool's output schema, alongside a text rendering.

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.

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.

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.