If you work with data, there’s a good chance you’ve come across the term Taxonomy. As a reminder, the formal definition of a taxonomy is a documented and orderly set of types, classifications, categorizations and/or principles that are often achieved through mechanisms including but not limited to naming, defining and/or the grouping of attributes, and which ultimately help to describe, differentiate, identify, arrange and provide contextual relationships between the entities for which the Taxonomy exists (see definition of Taxonomy).
Most people that think of taxonomies think of them as just classification mechanisms. While this is not wrong, there are actually multiple different Taxonomy Types, each with different intended uses.
The most common taxonomy types are listed, below…
Classification / Categorization Taxonomy
The most commonly referred to taxonomy is a Classification Taxonomy, which is also known as a Categorization Taxonomy.
This type of taxonomy is used to classify (categorize) things based on traits and characteristics, such as those which might be inherited or collected, over time, that help with identification and labeling.
Common examples of Classification Taxonomies include but are not limited to a Taxonomy of Mammals, a Taxonomy of Birds, a Taxonomy of Insects, a Taxonomy of Geological Materials, and a Taxonomy of Products (such as in a Product Catalog).
Controlled Language Taxonomy
A Controlled Language Taxonomy, also known as a Language Control Taxonomy, is used to facilitate language, meaning, and understanding through explicit terminology that is associated with explicit definitions, and through relationships to other language constructs.
Controlled Language Taxonomies often require significant lexicographical consistency and rigor. For example, naming standards for, consistent definitions for terms that contain similar words, synonyms, antonyms, preferred terms, antiquated or deprecated terms, etc. We see these implementations in dictionaries, glossaries and controlled vocabularies.
A simple example of a controlled vocabulary can be seen in this Taxonomy of Service Types, which contains 1,000+ terms that need to be consistently named and defined (i.e. lexicographically consistent). A more complex example can be seen in the IF4IT Glossary of Information Technology Terms and Phrases, which is the largest and yet the most consistent lexicographically consistent IT Glossary in the world.
Decision / Rules Taxonomy
A Decision Taxonomy, also known as a Rules Taxonomy, is used to control logic processing order, procedural flows, and repeatable outcomes.
Examples include Control Systems (e.g. Manual Workflow Systems, Mechanical Systems, Analog Systems, and Digital Processing Systems) that leverage logic and data comparison tools, such as decision trees, to control manual and/or automated workflows.
In workflows or flowcharts, there are inevitable points where decisions must be made in order to select a path for moving forward. These decisions are usually tied to many different input data points that, based on value combinations and evaluation algorithms, dictate what decision will be made. We see these types of designs and implementation in Rules Engines.
A Navigation Taxonomy, sometimes referred to as a Traversal Taxonomy, is a means of controlling User Experience (UX) that is related to finding and exploring data, information, and knowledge through traversal or browsing (as opposed to searching). We see this type of taxonomy in the User Interfaces (UIs) of applications and systems. However, they don’t have to be used in just electronic systems.
For example, one of the most well known examples of such a taxonomy is how Card Catalogs and the Dewey Decimal System are used in brick and mortar libraries, specifically to control how people find things like books and other media.
Another example is how web site and application user interfaces are structured to control end users moving around from page to page or screen to screen. You can see an example of such a controlled navigation experience in this Digital Enterprise Library and in this Knowledge Management Body of Knowledge.
Organizational / Structural Taxonomy
An Organizational Taxonomy, also known as a Structural Taxonomy or a Containment Taxonomy, is means of structuring and ordering groups things, people, and places. Taxonomies of this type usually address containment or composition. For example, X is contained in Y, and Y is contained in X. Or, A is composed of B, and B is composed of C.
One very common non-technical example of an Organizational Taxonomy is an Organization (Org) Chart, where people are contained in organizations and organizations are often contained within other organizations.
A technical example includes the visual representation of computer file systems, where files are contained within folders/directories and folders/directories are contained within other folders/directories.
Another technical example is a system design schematic that represents parts of parts.
Association / Relationship Taxonomy (a.k.a. Tagging Taxonomy)
An Association Taxonomy, also known as a Relationship Taxonomy or Tagging Taxonomy, is used to assign meaningful context to things by relating or tagging those things with other things like terms or objects that may help add context. These types of taxonomies are often used to facilitate functions such as search and filtering.
We see the use of this type of taxonomy in the tagging of electronic documents and content with keywords that help search tools match such documents and topics to end user search criteria. In more complicated semantic data domains, we see the same patterns where objects are related to other objects and, through the nature of their relationships, help match objects to complex query criteria which can join or exclude data across multiple and different related objects.
More Examples of Taxonomies
While it is not intended to represent an exhaustive list of all possible taxonomies and taxonomy types, a list of examples can be found in the IF4IT Inventory of Taxonomies.
Examples of Taxonomy Users
Taxonomies have value to many different professionals in many different industries and organizations. Some examples include but are not limited to:
- Pharmaceutical scientists and researchers that classify drugs and chemicals.
- Librarians that classify books, periodicals and other media.
- Computer scientists, programmers and information technologists who develop and seed software-related systems and applications.
- Medical professionals like physicians and nurses who leverage classifications of symptoms, diagnosis and treatments.
- Technical writers, technical communicators, content managers and knowledge managers who capture, curate and share content.
A Word About Taxonomy Structures
There are different taxonomy structures that are used for multiple different applications. Some examples include but are not limited to:
- a List, such as in the case of a Controlled Vocabulary or a collection of related things like named hash sets.
- a Chain, such as in the case of Linked Lists.
- a Hierarchy or Tree, such as in the case of a Classification Taxonomy or an Organizational Taxonomy.
- a multi-faceted Graph or Network, such as in the case of an ordered and classified Semantic Data Graph/Network.
Taxonomy Types are not mutually exclusive
It is important to understand that the above taxonomy types are not always mutually exclusive. In other words, a defined taxonomy does not have to exist for one and only one purpose. For example, a taxonomy may be defined that meets the needs of, both, containment (i.e. Containment Taxonomy) and navigation (i.e. Navigation Taxonomy), such as in the case of a file system storage directory tree (a.k.a. folder structure).
Taxonomies are very common and used by many professionals in many different industries. There are multiple taxonomy types. Each type has purpose with different intended uses. No one defined taxonomy has to exist for just one type, although one certainly can, if it makes sense to do so.
As a professional who works with data, information and knowledge, it is always a good thing to know and understand the different taxonomy types.
NOTE: If you believe this article has missed a taxonomy type, please let us know and we’ll do what we can to update the article to include any new information that is submitted.
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