Content automation is about manipulating different pieces of information. Information about product components can be retrieved from a bill of materials, matching content can be found in the content repository based on metadata, and then put together into a deliverable, according to a pre-defined logic.
Similarly, if information about each product component and its interaction with other components is formalized in some standard way, it can be relatively easy transformed to a visual representation. And so on.
To make individual pieces of information retrievable and recognizable, they must be addressable. Addressability of data is the key to content automation.
An example of an addressable data is any Excel spreadsheet. Each cell has a unique address, like A1 or C4, so it can be used to retrieve the data from the specified cell.
An example of a non-addressable data is any plain text, for example, anything you would type in Notepad. This is a monolithic text whose individual paragraphs don’t have any ID or anything similar that would allow you to directly address to a specific paragraph or maybe even to a piece of text within a paragraph.
Finally, semi-structured data is the best of two worlds. On one hand, it does have some structure. However, it’s much more flexible and less restrictive than data in a tabular format. After all, a narrative cannot be represented in a tabular format. On the other hand, almost every single piece of information is addressable or can be made addressable.
If the structure is semantic, it’s even better because you can also know the actual meaning of each piece of information. Having such a structure lets you manipulate content as you want: you can automatically generate an entire documentation, disintegrate the original content, re-aggregate it in a way required for a specific context, or dynamically change the visual representation of the content depending on the content specifics and user needs.
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