Unit 3: Data Queries

In SDMX API v2, data queries are designed to be more intuitive, flexible, and aligned with RESTful principles. The API supports queries for both aggregated statistical data and microdata, making it suitable for a wide range of analytical use cases. Developers can use structured paths or query parameters to request specific datasets, time series, or observations based on dimensions like time, geography, indicators, or other classification codes.

The API supports multiple response formats—JSON, XML (SDMX-ML), and CSV—giving developers flexibility, depending on their needs and tools. Pagination options help manage large data volumes, allowing responses to be split across multiple pages with customisable page sizes.

Key query options include filters for specific time periods (startPeriod, endPeriod), frequency, dimensions, and attributes. Developers can also choose to include or exclude metadata, annotations, and series-level information. Flags like detail=full or detail=serieskeysonly control the depth of returned data.

For microdata, the API allows queries with variable-level filtering, enabling granular access to individual records while respecting privacy constraints.

Overall, SDMX API v2 offers a comprehensive and developer-friendly approach to querying complex statistical datasets, making it easier to build data-driven applications, dashboards, and automation scripts.

In this unit, we'll cover the ways in which SDMX API data queries assist users and present a few realistic examples of data queries.

The SDMX API data queries

In the SDMX API, users can give various dimensions as a parameter in the URL like series code, country code, or frequency and time range etc., and the resulting data can be downloaded as XML or JSON.

Data queries in action

Let's look at a few examples of data queries. The images below Illustrate options for formulating a data query and how the query string may be used to filter or provide further information about the results.

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Familiarisation

An easy way to become familiar with retrieving data and the various options available is to try various parameters using a public SDMX API, such as the BIS API.

A closer look at data queries

Now let's explore data queries using a realistic example. In this short video, we'll cover a few examples of data queries.

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To access the code presented in this video, click here.

Coming next

In the next unit, we'll focus on structure queries.