The concept of an ‘information model’ goes back at least to the 1970s with the growth of digital information and database software to manage structured data. In the 1980s information models became a key tool for organizing and managing documents and unstructured data, and in the 1990s emerged as a critical requirement for complex content management applications. A ‘content model’ is an information model for unstructured data, or a combination of unstructured data types and structured data.
“An Information Model provides the framework for organizing your content so that it can be delivered and reused in a variety of innovative ways. Once you have created an Information Model for your content repository, you will be able to label information in ways that will enhance search and retrieval, making it possible for authors and users to find the information resources they need quickly and easily… The Information Model is the ultimate content-management tool.” (The Gilbane Report, Vol 10, Num 1, 2002 , What is an Information Model & Why do You Need One?).
“An information model provides formalism to the description of a problem domain without constraining how that description is mapped to an actual implementation in software. There may be many mappings of the information model. Such mappings are called data models, irrespective of whether they are object models (e.g. using UML), entity relationship models or XML schemas.” (Wikipedia).
Also see Integration DEFinition for information modeling (IDEF1X)
Content strategy refers to the planning, development, and management of content—written or in other media. The term has been particularly common in web development since the late 1990s. It is a recognized field in user experience design, and it also draws from adjacent disciplines such as information architecture, content management, business analysis, digital marketing, and technical communication.
https://en.wikipedia.org/wiki/Content_strategy
Also see: https://gilbane.com/category/content-management-strategy/
The term has also been adopted by the content marketing movement.
This term came into widespread use with the emergence of electronic documents, especially after the Web was created. Since then “multi-channel” has grown to mean any number of channels and even an unknown, n + 1, number of channels given the proliferation of devices and applications.
“Omnichannel” or omni-channel publishing became a popular concept among marketers to refer to “all the channels”, including physical and digital, to a customer, and the desire to synchronize all channels and touch points for a good customer experience. Marketers are of course hopeful by nature.
Also see single source publishing, multipurpose publishing, SGML, and XML.
Now more commonly known as machine translation (MT), refers to the the use of software to translate text or speech from one language to another. In the 80s and 90s MT software was rule-based, but in the 2000s statistical analysis and the re-emergence of neural networking and more advanced machine learning techniques have proved to be far more successful.
Single source publishing, also known as single sourcing publishing, is a content management method, often referred to as multichannel content management, which allows the same source content to be used across different forms of media and more than one time. The labour-intensive and expensive work of editing need only be carried out once, on only one document; that source document can then be stored in one place and reused. This reduces the potential for error, as corrections are only made one time in the source document. Single-source publishing is sometimes used synonymously with multi-channel publishing though whether or not the two terms are synonymous is a matter of discussion.
A component content management system (CCMS) is a content management system (CMS) that manages content at a granular level (component) rather than at the document level. Each component represents a single topic, concept or asset (for example an image, table, product description, a procedure). The CCMS must be able to track “not only versions of topics and graphics but relationships among topics, graphics, maps, publications, and deliverables.
See this Gilbane Group white paper for a more detailed description Component Content Management – How True CCM Technology Drives the Most Compelling Content Initiatives.
The Semantic Web is a collaborative movement led by the international standards body, the World Wide Web Consortium (W3C). The standard promotes common data formats on the World Wide Web. By encouraging the inclusion of semantic content in web pages, the Semantic Web aims at converting the current web dominated by unstructured and semi-structured documents into a “web of data”. The Semantic Web stack builds on the W3C’s Resource Description Framework (RDF).
Also see linked data and knowledge graphs.
This Scientific American feature article from May 2001 sets out the vision (and yes, this is also a fun example of what a staid web page looked like in 2001):
The Semantic Web
A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities
by Tim Berners-Lee, James Handler and Ora Lasilla
Also see:
Introduction to Semantic Technology
and for a slightly more skeptical point of view:
Web 2.0, 3.0 and so on
and this:
Why Adding Semantics to Web Data is Difficult
In computer science and information science, an ontology is a formal naming and definition of the types, properties, and interrelationships of the entities that really or fundamentally exist for a particular domain of discourse. It is thus a practical application of philosophical ontology, with a taxonomy. An ontology compartmentalizes the variables needed for some set of computations and establishes the relationships between them. The fields of artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture all create ontologies to limit complexity and to organize information. The ontology can then be applied to problem solving.
