“But it’s always been a smoke and mirrors game / Anyone would do the same.” – Gotye, Smoke and Mirrors

It’s pretty common for organizations to have many software systems and platforms. Some are home grown, some are commercial; some have small scopes while others are enterprise grade; some are legacy while others are newly rolled out; some are seamlessly integrated while some (um, many) are standalone and siloed. What many of these systems have in common is that they are dedicated to one or more functions. They may be for digital asset management (DAM), content management (CMS), product information management (PIM), customer relationship management (CRM), and so on. Something that few enterprise systems do well is taxonomy management. And, to be fair, why should a standalone system dedicated to a particular purpose also be excellent at taxonomy (and ontology) management? There are dedicated systems for this function as well.

Typically, taxonomy management systems (TMS) are positioned as centralized repositories for controlled values which can be integrated with multiple systems in a hub and spoke model. A centralized taxonomy architecture ensures single concept values with a unique identifier can be used across multiple systems for many use cases. A centralized architecture makes sense, but there are many challenges arising from consuming downstream systems’ inabilities to handle the rich semantic models published from a TMS. Consuming systems may not be able to ingest properties, relationships, or even hierarchies.

What are some ways we can address these integration issues while maintaining an architecture in which a TMS is a centralized source of truth for metadata values?

Smoke and Mirrors

When the first iPhone was released, it shifted paradigms. The original iPhone wasn’t the first device to include touch screens, but its form and user experience was unique in many ways. Apple is touted for their designs, and it was the combination of form and function that garnered such immediate success. We didn’t learn the iPhone, the iPhone taught us. We learned to scroll, swipe, and tap so these basic functions became ubiquitous across many devices and manufacturers. A good user experience will do that: teach us how to navigate through an application, how the functionality works, where we should expect to find a “yes/no” or “next” button, and the overall design principles. I see this as domain teaching and reinforcement.

The same is true in the world of semantics. As semantic practitioners, we must educate users and meet them at the level of their knowledge need. Some business users will only need to know the basics of taxonomy principles when a taxonomy redesign is in progress or they are onboarded as taxonomy consumers. Other business partners will want to become more involved in the process and go beyond concepts into modeling the semantics of their domain.

Modeling conceptual domains is what semantics is built for, reflecting the ways of thinking in the organization, including business processes and relationships between concepts and things. Semantic models are mirrors of organizational thinking. Consuming systems may be mirrors of these mirrors, even when they are not designed to be semantic modeling platforms themselves. 

The most basic smoke and mirrors game is aligning concept label values across systems. While the values may be mirrored, it is more smoke than anything else, concealing the incredible amount of overhead in agreeing on the label values, maintaining the governance process to ensure these labels stay aligned, and workaround maintenance required by the nuanced differences between consuming systems. In these scenarios, any necessary change in any of the systems (including the taxonomy as an aligned source of truth) can be precarious as downstream values may be driving workflow processes or are hard-coded, making them extremely difficult to change.

Consuming systems supporting hierarchy, definitions, and synonyms can mirror hierarchical structures and at least some of the properties adding semantic context to concepts. Consuming systems only supporting flat lists may have the ability to create dependent fields. Although not a true hierarchy, selecting a value from one field that constrains the values in another field mirrors hierarchical structures. Again, mostly smoke and mirrors concealing the amount of semantic design it takes to understand which parent values may drive dependent fields and how the child concepts are displayed. A more advanced step toward alignment is ensuring that all of the values share a common ID, even if this ID is manually entered for each mirrored concept so they are the same across systems. Not ideal, but having a unique identifier for each concept can bring these concepts closer together even if they are pulled directly from a source of truth taxonomy management system.

More Mirrors, Less Smoke

The best way to take advantage of semantic models is to pull taxonomy concepts and their associated properties—including fields like description, scope note, and the URI or GUID—into consuming systems so there are taxonomy terms for metadata tagging and their associated attributes for context and additional information. Tagging interfaces might be dropdown lists of 10-15 values, hierarchical browsing, or typeahead fields displaying taxonomy concepts as the user enters characters. All of these methods of applying taxonomy concepts reinforce the terminology used in the organization. Dependent fields and hierarchies reinforce hierarchical relationships between concepts and reveal how ideas are organized.

Users less frequently see full ontologies including concepts and the relationships between them. However, revealing these structures in browsable visualizations can be useful to help users understand concepts and the relationships between them.  Again, these semantic structures mirror the activities of the business. If users can see interrelated concepts, and preferably in the context of content tagged with those concepts, it reinforces the mission and activities of the business. Additionally, showing graph visualizations can help shift thinking from simple hierarchical structures to more semantically rich graph structures. When business users understand the current domain thinking, they can also begin to understand how these semantic structures can be applied to business use cases to solve common organizational problems. In addition to active education by taxonomists, user interfaces and mirrored domain modeling in systems can help users understand semantic modeling and what it can do for the business. Revealing semantic models can be reinforcing, but it’s probably less common and useful than more practical mirrorings in systems that don’t have particularly strong semantic foundations to begin with.

Conceptual domain mirroring takes creativity, using the functionality of the TMS, APIs, and consuming systems to create an ontological and graphical domain representation even in systems that are foundationally relational and hierarchical. Taxonomists, working hand in hand with information architects, can find opportunities to express the complexities of semantic models in existing UIs and through creatively creating new ideas meeting the use cases of the business. Mirroring domains creates organizational alignment and reinforces domain thinking without conscious effort by the users. Just as well-designed hardware and software teaches us new domains, so can we as semantic practitioners find ways to passively educate our users about domain thinking and semantics in the organization.