Associations

Taxonomy 101

Professional associations have a mandate to present and offer well-organized content and information to their communities of members and practitioners, but the process of creating and maintaining informational schemes that are relevant to end users doesn’t always overlap with designing to meet basic administrative needs. When approaching association learning technology from the perspective of supporting sensible information taxonomy for end users and administrators, there are a multitude of factors to consider. It’s difficult to offer a comprehensive discussion of all relevant inputs and considerations in blog post form, but I want to start a discussion and present a few tips that may help educational directors and technology directors get (and stay) on the same page—especially when it comes to the Learning Management System (LMS).

ConnectionsExperts at the Association for Information and Image Management (AIIM) deal with these types of CMS information management issues for various groups, so that feels like a good place to start the LMS discussion. An AIIM white paper written by Carl Weise, titled How to Develop Taxonomies to Support Navigation, Information Discovery, and Findability, addresses the fundamental taxonomy issues that arise for information domains. As Weise points out, developing and supporting a taxonomy involves weighing the tradeoffs between navigation (creating predictable and sensible structural form), information discovery (developing connections between pieces of information within a domain), and findability (capturing and refining the vocabulary of user communities). For example, a simple hierarchy tree structure is easy to manage and predictable for navigation, but information discovery and findability will suffer. I particularly like Weise’s larger point regarding a fundamental mistake that can lead people to develop poor taxonomies (Weise, pg. 7):

“Too often in taxonomy work, you sort things logically into warehouse type arrangements, instead of understanding what ‘relatedness’ means to our typical users in the course of their everyday work. This means you actually force people to go to lots of different places to gather the information they need, instead of finding them all close to each other ready to hand for the work they serve. Understanding our users and their patterns of information use are the only ways you can overcome this.”

Most groups are aware of these issues. Associations push to create more complex, facet-based taxonomies to satisfy user demands for better search functionality and content sorting on their website and CMS all the time. Users like the tags, recommendations, search filters, and other tools they employ on sites like Amazon.com, so expectations have been raised for the online experience. However, I often wonder if these efforts and concerns are fully translated to LMS side of the operation. After all, the same issues still apply within an LMS environment. A seemingly sensible taxonomy can become an impractical labyrinth of content for end users and administrators if there’s no flexiblity to grouping and connecting information in other ways. Descriptive metadata (i.e., information about an object that people can use to search and locate that object) can add value, so it’s important to seek out an LMS solution with a proper minimum feature set to accommodate (and enhance) these types of tagging, filtering, and sorting operations.

Here are a few basic considerations for associations looking to build better taxonomies in an LMS:

  1. Explore the feature set of your LMS. Does you LMS allow you to add multiple facets (i.e., tags) to learning assets and objects? It should, because this is a great way to redefine relationships between pieces of information. If your taxonomic structure can accommodate and promote reasonable approaches to “relatedness” as defined by administrators and users, you enhance findability and information discovery. This type of flexibility gives you a wider array of options to consider when developing a structure for content and information.
  2. Determine how you can use descriptive metadata to your advantage. Consider a quick example of how facets can work. A single quiz on a specific question in an assessment for a 2014 certification program exists in a single place within a hierarchical structure. Let’s say it’s located in the “2014 Program” folder and the “Quiz” sub-folder. If you know what you’re looking for and where to look, it’s possible to locate that quiz question fairly quickly. But what if you want more information? What if you want to know how it relates to other questions in the same sub-folder, or how it compares to a similar question in the 2013 certification program? The capability to add facets is crucial to providing speedy and useful answers to these types of inquiries. An administrator could add multiple facets to the quiz question for things like difficulty level, subject matter, experimental content, related regulations, etc. These descriptors would then allow administrators to group pieces of information in different ways and create new relationships beyond the basic hierarchical structure. Quiz questions across different programs could be grouped and filtered according to “intermediate difficulty” or content related to “regulation 9.34,” or any other relevant connection you could dream up. In essence, facets allow you to define the important characteristics of data so you can slice the same data set in multiple different ways and target the relevant intersections you need to see. The same concept applies to any piece of information in the LMS.
  3. Decide how you will manage facets. Facet management is important. Metadata should not necessarily be shared openly. An association administrator may not want to share everything with learners. An administrator may find it useful to add an “experimental content” facet to a quiz question, but that’s not necessarily something a learner should ever see. If learners are allowed to add facets, who needs to see that personalized information? These are decisions you need to make. If you want the process to work properly, you need to decide who should have the power to create new connections between information. Are new facets injecting potentially harmful ambiguities into the domain, or are they enhancing the organizational principles of your chosen structure?
  4. If you adopt a robust hierarchical structure, develop a process for controlling the vocabulary of the community.
    If you allow for the creation of metadata in theSearch form of thesaurus or ontological entries, you need to make sure these vocabularies still connect in logical ways to promote findability. If the new facets and descriptors you create don’t help users or administrators sort and find content, they aren’t adding value. Make sure you develop a plan to capitalize on value of this feature set in an LMS setting. One easy way to help control and promote the chosen vocabulary is to use an auto-complete feature in search bars. This can help shape user expectations and provide useful feedback on relatedness of various terms.

Ultimately, taxonomy solutions made to support navigation, information discovery, and findability require careful analysis of the relationships between pieces of information, and an understanding of realistic use-case scenarios. If you understand what learners and administrators need on the LMS side of things, you can seek out a system with a feature set that allows you to build a better information scheme.

Search