Group items tagged

The linkage between a metadata record and the resource it describes may take one of two forms: elements may be contained in a record separate from the item, as in the case of the library's catalog record; or the metadata may be embedded in the resource itself.

The Dublin Core metadata standard is a simple yet effective element set for describing a wide range of networked resources. The Dublin Core standard includes two levels: Simple and Qualified. Simple Dublin Core comprises fifteen elements; Qualified Dublin Core includes three additional elements (Audience, Provenance and RightsHolder), as well as a group of element refinements (also called qualifiers) that refine the semantics of the elements in ways that may be useful in resource discovery.

Another way to look at Dublin Core is as a "small language for making a particular class of statements about resources". In this language, there are two classes of terms -- elements (nouns) and qualifiers (adjectives) -- which can be arranged into a simple pattern of statements.

Keys provide a way for authors to create addresses to resources through the use of a named identifier rather thanto a specific URI pointer. In other words, I can create an easy-to-remember key, like “ms-word-functions” that actually resolves to a URL “http://support.microsoft.com/kb/211982” and link to this URL using the key name in my DITA topic.

Any time a topic makes use of a key reference, that topic is explicitly binding itself to a map (or many maps), meaning that a topic is no longer a unit of information that is completely independent of any particular context in which it is assembled into. You could make the argument that any reference defined in a topic to an external resource (e.g., an image or a cross-reference to another topic) by definition creates a dependency on that topic. And arguably, the referenced (the endpoint) resource is unaware of the object that is referencing it, regardless of whether it's a topic reference or a cross-reference. But there is an additional dependency in the case of keys: Any map that references a topic with a key reference must define the key. So in a sense, not only does the map (or an ancestor map) need to know about the topic, it needs to discover what the topic is about, specifically related to any key references it points to. Consequently, somewhere along the line, at least one map must define the keys used by a topic.  Did you get all that?  Imagine what your XML authoring tools, CMS systems, and rendering platforms will need to do to manage this.

there are potential downsides too.  Keys and key references add another layer of complexity to planning the authoring, deployment and management of DITA content.  

people need to act, they need to be engaged

they need to struggle

The minimalist idea, the way I think of it, is to minimize the extent to which the system and the information get in the way of what the user’s really interested in.

Administrative metadata is information intended to facilitate the management of resources. It includes information such as when and how an object was created, who is responsible for controlling access to or archiving the content, what processing activities have been performed in relation to it, and what restrictions on access or use apply.

Technical metadata and preservation metadata are particular types of administrative metadata. Technical metadata describes digital files and includes capture information, format, file size, checksum, sampling frequencies, and similar characteristics.

Structural metadata relates the pieces of a compound object together and/or bundles related objects into a package. For example, if a book is digitized as individual page images, structural metadata can record information concerning the order of files (page numbering) and how they relate to the logical structure of the book (table of contents) is also required.

In a topic-oriented architecture such as DITA, content is authored in small, independent units that are assembled to provide help systems, books, courses, and other deliverables. Each unit of information answers a single question for a specific purpose. That is, each topic has specific, independent subject matter

Because each topic has a specific meaning, DITA topics are tailor-made for semantic processing. However, current semantic processors can't read the text of a topic to find out what it means. What's missing is a formal declaration of the topic's subject matter that a semantic processor can understand

Simple Knowledge Organization System (SKOS) provides a standard for indicating the subject matter of content. SKOS lets you define the subjects for a particular subject matter area (organizing these subjects as a taxonomy if desired) and then classify each piece of content to indicate its subject. For instance, using SKOS, you could define configuration and security as subjects, and classify the three example topics that relate to those subjects so that users could browse the subjects to find the content regardless of whether the words "configuration" or "security" actually appear in the text.