In a computing environment, data is of the utmost importance. Data is input into a system, manipulated, and commensurately output. Data, or content, is particularly important to a web site, as various forms of content are presented to a visitor to the site. However, as the size of web sites expands, and their functionality increases, managing the content utilized at these websites becomes increasingly more complicated. The amount of content deployed increases rapidly with the expansion of the site, and the organization of, and relationships between, this content is constantly in flux.
To deal with the volume of content, many managers of computer environments, or publishers of websites, may wish to utilize a content management system. Particular foibles of certain content management systems, however, make their use less than ideal. For example, many extant systems do not understand the complex relationships between the content. Other systems may not allow an accurate representation of the varied nature of the content present and the contents' associated attributes and requirements. Some systems provide such an inhospitable environment that their use itself is a barrier to their effectiveness, requiring extensive training in programming and the locale of information to effectively manage content.
A few select content management systems have managed to obviate these problems by using content types to model the content of a site according to the site's own vocabulary. These content types may use the vocabulary and business rules used by a particular enterprise within which the users work. Business data objects may be instantiated from the content types and may include attributes, and workflow, access controls. Content management systems of this ilk allow a layer of abstraction to be fitted to the content which represents the complex relationships between the data in the terms defined by the users.
Consequently, many sites may wish to migrate their data to content management systems of this type. Previous methods for migrating this data to a content management system involved manually entering this data into a proprietary content management repository, defining content types and associating this legacy data with the defined content types. This method was time consuming and expensive, in part because it did not allow the persistence of content management metadata across content management systems and required the migration of data from one repository to the next.
Thus, there is a need for systems and methods of content management that can migrate existing, large data repositories without changing either the structure or the location of the data, while simultaneously allowing any existing content management metadata to be persisted.