In computer science, transclusion is the inclusion of part or all of an electronic document into one or more other documents by hypertext reference. Transclusion is usually performed when the referencing document is displayed, and is normally automatic and transparent to the end user. The result of transclusion is a single integrated document made of parts assembled on the fly from separate sources, possibly stored on different computers in disparate places.
Transclusion facilitates modular design: a resource is stored once and distributed for reuse in multiple documents. Updates or corrections to a resource are then reflected in any referencing documents. Ted Nelson coined the term for his 1980 nonlinear book Literary Machines.
Transclusion works better when transcluded sections of text are self-contained, so that the meaning and validity of the text is independent of context. For example, formulations like "as explained in the previous section" are problematic, because the transcluded section may appear in a different context, causing confusion. What constitutes "context neutral" text varies, but often includes things like company information or boilerplate.
Under some circumstances, and in some technical contexts, transcluded sections of text may not require strict adherence to the "context neutrality" principle, because the transcluded sections are capable of parameterization. Parameterization implies the ability to modify certain portions or subsections of a transcluded text depending on exogenous variables that can be changed independently. This is customarily done by supplying a transcluded text with one or more substitution placeholders. These placeholders are then replaced with the corresponding variable values prior to rendering the final transcluded output in context.
Ted Nelson, who also originated the words "hypertext" and "hypermedia", coined the term "transclusion" in his 1980 book Literary Machines. Part of his proposal was the idea that micropayments could be automatically exacted from the reader for all the text, no matter how many snippets of content are taken from various places.