Knowledge Maps, or KMaps, can be crudely described as "labels in a hierarchal tree format." If you're familiar with the concept of ontologies, controlled vocabularies, or semantic fields, then KMaps won't be new to you. However, each Knowledge Map also has its own data (alternate names, descriptions, and more), visible through the Subjects, Terms, and Places viewers. A KMap's metadata, along with its position relative to other Knowledge Maps in the hierarchy, provides valuable context about a term.
Content created in different Mandala tools can use the same Knowledge Map: this joins content across tools.
Knowledge Maps are:
- subject and place controlled vocabularies…
- …represented in ontologies…
- ...with their own independent structured data (names, descriptions, illustrations, maps, and more)…
- ...that index content across Mandala, and
- …that connect:
- content from one Mandala tool with content from another tool; and
- a Mandala asset with information about a keyword; and
- a term with related Knowledge Map keywords.
Knowledge Map collaborators can either be general users or editors. These different types of collaborators work on different websites, though the information is shared between sites. Anyone with a UVa NetBadge account can be a general user, but the Knowledge Maps team needs to give you special privileges if you want to be an editor.
If you have questions about getting started with Mandala or would like to discuss a potential Mandala project, please contact Courtney Floyd, Associate Director of Learning Technologies and Digital Humanities, at email@example.com.
Types of Knowledge Maps
Places are for geographical features of all types, i.e. locations. They include descriptions, alternate names, maps, feature types, relationships between places, relationships between places and other Knowledge Maps, ids, altitudes, and more.
Subjects are for concepts or topics. They include descriptions, translated titles, relationships between subjects, relationships between subjects and other Knowledge Maps, citations, and more. Unlike Terms, they’re best at creating nuance when describing relationships between subjects.
Terms are for defining words, like in a dictionary. Unlike Subjects, they focus on words, definitions, and descriptions, while only lightly focusing on relationships. Terms include nested definitions, citations, details on the term type, and more.
Should I use Subjects or Terms?
Think about Terms as dictionaries of terms, and Subjects as ontologies of subjects. The table below can help you understand how to think of each tool.
Names and descriptions
Naming and describing play a primary role. You can add nuance to the descriptions: examples, pronunciations, dictionaries from different sources, and more.
Naming and describing play a minor role. You can add a simple description and alternate names, but no advanced features exist.
Hierarchies (also known as trees or ontologies) play a very minor role. While very simple hierarchical structures are possible, you can't create very sophisticated relationships between terms.
In subjects, ontologies play a primary role. You can create complex relationships between subjects.
If you want to learn about Knowledge Maps in-depth, we've put together a mini three-part course. You can watch it below or in this Mandala Audio-Video collection.
This video is still in progress. Watch this space! Meanwhile, check out the Knowledge Maps editor guide.