This website occupies itself primarily with the organization of content for websites and other online channels, such as apps.
In order to be able to classify documents (content), we need models that define classification rules. We classify by assigning meta data or attributes to documents.
In this section, we will look at different structures for meta data.
For simplicity's sake, we will assume the smallest piece of information, that we will work with, will be a document. This could be a Word document, a PDF, a web page.
Meta data is - oversimplified again - data about data or information about information.
A simple example of meta data: the publication date, the language and the author of a document. One of the first meta data standards dealt with this type of meta data: the Dublin Core Metadata Initiative.
Meta data is not art for art's sake. It has a purpose. This purpose is to unambiguously identify documents and to create relationships between documents (a relationship might be expressed as a navigational structure in a website). Meta data plays an important part in smart searches, for instance facetted search. Meta data takes on even more value when it comes to omni-channel publications.
A number of models require our attention. We will focus on: