“There are no facts, only interpretations.” – Friedrich Nietzsche

Behind every creation–a work of art, musical composition, outstanding sporting performance–there is a creator. Behind a creator’s creation are copyright laws and license agreements detailing how that creation can be bought, sold, represented, and reused. In retail, the works and likenesses of artists and creators appear on merchandise which may be globally distributed. Whether it is the recognizable Jordan Jumpman icon or Bob Marley’s face on a t-shirt, there are contractual obligations and regulations which must be followed to avoid risk and exposure for both the creator and the contracting company. The use of names, images, and likenesses is captured in contractual language, defining the way an image or other work can be used and providing the legal foundations to make sure royalties are paid to the artist and their representative company.

In many organizations that have arrangements with artists or athletes, there are dedicated systems to manage contract documents specially designed to handle the content and also apply the appropriate type of metadata to describe these assets. The digital assets protected by these contracts, such as works of art, images, video, audio, and the like, can be stored in a digital asset management (DAM) system, which specializes in maintaining technical, administrative, structural, descriptive, preservation, usage, and rights metadata. In digital visual works, these rights and permissions may be captured as rights metadata accompanying the image file. Similarly, audio works can carry this information on physical media, and, more commonly, embedded in the individual audio files and the bound collection of an album. Rights and permissions are thus often associated to the artistic creation in both physical and electronic formats.

The metadata to populate values in these platforms can be created and maintained in a taxonomy management system to ensure the application of consistent values in one or more consuming systems. Taxonomies can contain centralized, standardized values describing asset usage and rights and can also provide descriptive metadata values; that is, the metadata that describes what the content is about or what is represented in it. In the world of semantic technologies, taxonomies and ontologies model domains to provide meaning which can otherwise be lost when flattening or decontextualizing metadata attributes. Since taxonomy and ontology management systems were not designed to be content or digital asset management systems, the taxonomy values and the ontology structures which define their use can potentially become detached from the content they describe. The semantic model lives in one system for application across one or more consuming applications while the objects themselves live in those systems, likely containing a mix of system-specific metadata, like technical descriptions of asset size and format and descriptive metadata coming from a taxonomy.

Semantic modeling is an act of establishing veracity. Taxonomies and ontologies model the domains of the organization, including describing the concepts in taxonomies and the relationships between them. Agreeing on what preferred label form to use, which concepts are synonyms, and establishing hierarchical and associative relationships between concepts are all actions to model the truth; or, more accurately, your truth based on the knowledge domain and how it will be used. For instance, modeling fixed relationships between an authority file of athlete names and associated taxonomy concepts could have the following named entities:

Athlete name has team Team name

Athlete name has product Product name

Team name has geography Geographical location

Each of these statements asserts a truth between one or more concepts at any given time. When that truth changes, but the model doesn’t change to reflect it, there is a drift between the current legal standing stated in contracts and how this is represented in the organization’s schema. When creative works or artist likenesses are surfaced on a front end user experience, such as linking a search term to a product or presenting audio or video content in a streaming service, the assumption is that the party responsible for the platform is presenting content for which it is legally liable.

Ironically, the attempt to standardize taxonomy values and their relationships for application across different systems to mitigate the risk of inaccurate metadata values being applied to content and to drive functionality like search and personalized recommendations can in fact introduce new risks. When defining the organization’s domains, it is important to bear in mind how that schema is applied to the actual “things” in other systems and what modeling a full domain truth might mean for how those assets are discovered and used. Attempts to model accurately and truthfully, when applied to content, can inadvertently reveal or persist truths which should not be exposed or have changed meaning over time.

For example, selling athlete merchandise associated with a team is common practice, since fans support teams and the athletes who play for those teams. However, facts which seem immutable, like team names and rosters, can change over time. I live in Oakland, California, home of the Raiders. Well, former home of the Raiders, who are the Las Vegas Raiders who were the Oakland Raiders who were the Los Angeles Raiders who were the Oakland Raiders. How many Raiders players have come and gone over the years and have played for multiple teams throughout their careers? Keeping on top of this kind of high-velocity data changing at scale can be extremely difficult. The same can be said of company-sponsored athletes. Contracts change and products once associated to or endorsed by an athlete may no longer be associated to that athlete. Selling one of these products out of contract can have serious financial and reputational repercussions.

Taxonomy and ontology governance processes must be firmly established and followed in order to make it possible to represent the company domain accurately while mitigating risk. A tight working relationship between the taxonomy team and business representatives in legal and/or marketing is a first priority. Whenever a contract changes, a request must be submitted to reflect this change in the semantic models so tagging moving forward is accurate. Changes to semantic modeling to reflect the new truth doesn’t only happen in the taxonomy management system. The change must be propagated to consuming systems and content on a known schedule. If the change is immediate, the tagging must be changed immediately. If the change goes into effect on a given date or at the end of an established period, the change must be made and pushed to meet that date.

Changing available concepts and tagging practices from a fixed point moving forward is relatively easy compared to other requirements, which may include the untagging or retagging of content to ensure it is not retrieved by search or otherwise discovered by consumers in the user experience. If an association between a team and an athlete is no longer valid, the company may have the opportunity to sell product through an established period of time, allowing the liquidation of as much outdated product stock as possible. After that time, however, discovering a product and purchasing it with the contract no longer being in effect can open the organization to significant risk.

The same risk applies to content not yet ready for prime-time. Any new product release, if tagged and made available to the user experience before a release date, can damage a company’s product launch and severely impact the time and planning that went into organizing an effective campaign. Internally, the risk still exists. If artist or product information is pre-planned in the organization’s metadata, there must be processes in place to keep this information known only to those who need to know it. That means allowing permissioned access to planned artist and product concepts to only those who need to know to avoid information leaks ahead of a release date. While organization’s have contracts stipulating how internal employees handle private company information, it is possible for a product release statement or other content to be discovered internally and intentionally or unintentionally shared to social media sources.

The examples I’ve provided here are in the domains of copyrighted work, but modeling against risk and exposure is even more critical in industries like medicine, health and safety, and manufacturing, just to name a few. While modeling truth is the ultimate goal of creating and curating semantic models, all concepts and their relationships which may be used to power a user experience, such as seeking prescription medicine or medical advice, safety procedures and equipment, and best practices in manufacturing, need to be carefully evaluated before being put into production in an application. While financial and reputational risks and penalties can be damaging, they pale in comparison to inappropriately modeled information people rely on to make potentially life and death decisions.

True to their name, semantic models are meant to be meaningful and act as a source of truth. Actively maintaining taxonomies and ontologies to be in line with truth as it changes includes a vital set of governance processes which must be carefully planned and executed to ensure the company is not exposed to risk. Unfortunately, there may be domains which can’t be modeled in taxonomies because the supporting processes don’t exist or can’t be maintained and executed upon efficiently enough to demonstrate low risk. If these domain areas are important to the organization, a strong case must be made to establish and maintain the processes and resources necessary to exploit beneficial modeling before the company is put at risk in the first place. An organization might not view semantic models as a potential source of risk, so it is up to semantic architects, taxonomists and ontologists, to be conscious of modeling repercussions and actively pursue governance processes to ensure their work is an accurate and up to date source of truth.