An infobox is a template used to collect and present a subset of information about its subject, such as a document. It is a structured document containing a set of attribute–value pairs, and in represents a summary of information about the subject of an article. In this way, they are comparable to data tables in some aspects. When presented within the larger document it summarizes, an infobox is often presented in a sidebar format.
An infobox may be implemented in another document by transcluding it into that document and specifying some or all of the attribute–value pairs associated with that infobox, known as parameterization.
Placement of an infobox within the of an article is important for accessibility. A best practice is to place them following disambiguation templates (those that direct readers to articles about topics with similar names) and maintenance templates (such as that marking an article as unreferenced), but before all other content.
Baeza-Yates and King say that some editors find templates such as infoboxes complicated, as the template may hide text about a property or resource that the editor wishes to change; this is exacerbated by chained templates, that is templates transcluded within other templates.
The name of an Infobox is typically "Infobox [genre]", however the more widely used infoboxes often have shorter names given to them, like taxobox for taxonomy, warbox for military conflicts, and geobox for geography.
Knowledge obtained by machine learning can be used to improve an article, such as by using automated software suggestions to editors for adding infobox data. The iPopulator project created a system to add a value to an article's infobox parameter via an automated parsing of the text of that article.
DBpedia uses structured content extracted from infoboxes by machine learning algorithms to create a resource of linked data in a Semantic Web; it has been described by Tim Berners-Lee as "one of the more famous" components of the linked data project.