Taxonomies and Attribute Data

In the past (such as my 2021 blog post "Attributes in Taxonomies"), I have explained that “attributes” serve as filters to refine search results on content, results that have already been narrowed by a hierarchical taxonomy concept or category. As such, the attributes available for filtering can vary based on a taxonomy concept or category that had been selected. To the end user, high-level taxonomy facets and attributes both function similarly as filters, and the distinction between facets and attributes may not be apparent. If the distinction is not noticeable to end users, then then facets and attributes may be confused. It’s best to describe attributes for what they are, and not merely by what they can do. That’s that this blog post aims to do.

Attributes

Data is information in the form of specific values that are relevant to something such as an asset, object, product, person, event, or transaction. Since data is relevant to something else, we can refer to data as an “attribute “of something. When attributes are standardized and used in information/data management, then attributes are metadata. Metadata schema are structures to organize data.

Examples of attribute metadata are:

• for people: birth date, gender, occupation, nationality, phone number
• for products: brand, price, color, size, SKU number
• for documents: title, author, publication date, language, word count, publication status, file type

Almost all metadata, both descriptive and administrative, are attributes of something. (Only structural metadata, that which is used to mark up text, would not be an attribute.)  Attributes, as metadata, can serve various purposes, including identification, comparison, sorting, filtering, and finding something based on its attributes.

Attribute values may be of different types: text, numbers, dates, or yes/no (also called “Boolean”). As text strings, attribute values may be uncontrolled free text or terms from a controlled list.

Taxonomies

Taxonomies are structures of concepts, which are used primarily for tagging and retrieval of content, although there are secondary uses. The concepts include subjects and named entities. In all cases, the concepts are of controlled vocabularies. The structures may be primarily hierarchical or primarily faceted, although a combination, such as limited hierarchies within a facet, is also possible. The structure of the taxonomy provides context for tagging and supports interaction by users.

When a taxonomy is structured into facets, typically each facet serves also as a metadata property.  A hierarchical topical taxonomy can also provide values for a metadata property. Taxonomies are structures to organize controlled vocabulary concepts.

Examples of taxonomy facets include:

• Topics
• Activities
• Industries
• Product/service types
• Brand names
• Companies
• Organizations
• Names of people
• Types of people/Roles
• Events/Occasions

Thus, the types of things that are facets are usually not the same types of things that are considered attributes. 

Metadata schema are structures to organize data, whereas taxonomies are structures to organize controlled vocabulary concepts that can populate metadata properties.

Where Attributes and Taxonomies Overlap

Considering again the examples of different types of attributes for different things, there are some attributes that could be managed in a “taxonomy” instead of merely as “attributes”:

• For people:  Name
• For products:  Product type/category
• For documents:  Subject/topic

Technically, each of these characteristics is also an attribute, but it is usually more practical to manage them as taxonomies so that they can support the implemented benefits of a taxonomy, such as semantic tagging, searching (including type-ahead search suggest), and browsing.

Thus, when we talk about “attributes” in the context of taxonomies, we mean those characteristics of something that are better managed as attributes and not managed as taxonomies. The decision is one of knowledge modeling.

For example, to support the refinement of searches, a taxonomy of expert people for an organization may have the following taxonomy facets:

•  Name
•  Subject of expertise
•  Organizational unit
•  Location

Then in addition to the facets, the taxonomy may have the following attributes associated with each record of a person:

• Job title
• Academic degree
• Email address
• Phone number
• URL of headshot image

This is selected data of interest, but not values that are used in initial search or browsing for finding and retrieving content. Attributes are metadata, and taxonomy facets are also metadata, but that does not mean that they are the same, because different metadata can have different functions or purposes.

Ontologies: Bridging Taxonomies and Attributes

When we enrich a taxonomy with features of an ontology, not only can we add semantic relationships, but we can also add attributes to taxonomy concepts. Usually, when taxonomists first learn about ontologies, they think primarily of the addition of customized relationships between concepts, and they might not be aware of the importance of the addition of attributes.

In ontologies, semantic relationships are formally called “object properties,” and attributes are called “datatype properties.” Both are equally important. Meanwhile, the feature of “classes” in an ontology typically corresponds to taxonomy concept schemes or facets.

To add attributes to a taxonomy, the best way to do it is through adding an ontology, which can be very simple and not even include semantic relationships. As the availability of different attributes may vary based on a hierarchy branch of concepts, this can be managed by creating classes, which are assigned to hierarchical branches, facets, or concept schemes. Then, attributes (datatype properties) are applied and used with concepts based on the class the concept belongs to. 

Conclusion

The following table summarized the differences between taxonomy facets and attributes.

Taxonomy Facets	Attributes
Basic structure of many taxonomies	Additional data added to taxonomies
Controlled vocabularies	Controlled or uncontrolled terms, text, numbers, dates, Boolean options, etc.
Concepts as nouns or noun phrases	If text, any kind of text string
Top organizational level of a taxonomy	Values relevant to any taxonomy concept
Concept Schemes in SKOS, or Classes in an OWL ontology	Metadata on a concept, or datatype properties in an OWL ontology

Faceted Classification and Faceted Taxonomies

I have argued before that a taxonomy is not the same as a classification system, despite the original meaning of the word taxonomy as a system for classification. (See the blog post Classification Systems vs. Taxonomies.) Modern taxonomies that are used to support information management and findability are more similar to information retrieval thesauri and subject heading schemes than they are to classification systems. Another type of classification, the method of “faceted classification,” however, does apply to types of taxonomies. I would not consider “faceted classification” as exactly a synonym, though, to “faceted taxonomy,” as not all faceted taxonomies are the same.

What is faceted classification?

Facets for jobs

Facet means face, side, dimension, or aspect. In this sense, facets are meant to mean aspects of classification. A diamond, an object, or a digital content item is multi-faceted. A digital content item (text document, presentation, image, video, etc.) has multiple informational dimensions or aspects to it and thus multiple ways to be classified.

Classification is about putting an item, such as a content item (document, page, or digital asset) into a class or category. If it’s a physical object (a book) it goes into a shelf of its class. In faceted classification, an item cannot physically be in more than one place, but it can still be “assigned to” more than one class. So, while the book itself can be on only one shelf, the record about the book can be assigned to more than one class.

Faceted classification assigns classes/categories/terms/concept from each of multiple facets to a content item, allowing users to find the item by choosing the concepts from any one of the facets they consider first. Different users will consider different classification facets first. Users then narrow the search results by selecting concepts from additional facets in any order they wish, until they get a targeted result set meeting the criteria of multiple facet selections. The user interface of faceted classification is sometimes referred to as faceted browsing.

History of faceted classification

The idea of faceted classification as a superior alternative to traditional hierarchical classification, whereby an item (such as book or article) can be classified in multiple different ways instead of in just a single classification class/category, is not new. The first such faceted classification was developed and published by mathematician/librarian S.R. Ranganathan in 1933, as an alternative to the Dewey Decimal System for classifying books, called Colon Classification (since the colon punctuation was originally used to separate the multiple facets). In addition to subject categories, it has the following facets:

1. Personality – topic or orientation
2. Matter – things or materials
3. Energy – actions
4. Space – places or locations
5. Time – times or time periods

Although it was not adopted widely internationally due to its complexities in the pre-digital era, colon classification has been used by libraries in India.

In the late 20^th century, digital library research systems based on databases enabled faceted classification and search, with different fields of a database record represented in different search facets. Users interacted with through an “advanced search” form of multiple fields. Faceted classification and browsing gained widespread adoption with the advancement of interactive user interfaces on websites and in web applications in the late 1990s and early 2000s. Thus, facets started being displayed in more user-friendly ways that were no longer “advanced.”

Structure of facets

It’s not necessary to follow Ranganathan’s suggested five facets, but that’s a good way to get thinking about faceted classification. Another way to look at faceted classification is to consider a facet for each of various question words: What, Who, Where, When

• What kind of thing is it – content type
• What is it primarily about - subject
• Who is it for or concerns – audience or user group
• Where is it for/applicable, or where it depicts (media) – geographic region
• When it is about – event or season (not date of creation, which is administrative metadata, instead of a taxonomy concept)

The additional question words of “why” and “how” are relevant in some cases, but less common. An individual content item typically does not address all of these questions, but usually addresses more than one. When creating facets, most of the facet types should be applicable to most of the content types.  

Another good way to think about faceted classification is to put the word “by” after each facet, to suggest classification and filtering “by” the aspect type. A logical and practical number of facets tends to be in the range of three to seven.

A standard feature of facets is that they are mutually exclusive. A concept/type belongs to only one facet. This is typical practice for the design of classification systems. The difference is that in faceted classification it is merely the concept/type/term that belongs to just one facet, not the content item or thing itself that would belong to only one classification in traditional classification systems.

When a faceted taxonomy is not for classification

The design, implementation and use of facets to construct or refine searches has become so popular that it is no longer used just for classification aspects. Rather, a faceted taxonomy design may be used for any faceted grouping of concepts for search or metadata types that are relevant for the content and users.

Faceted classification is intended to classify things that share all the same facets. For example, all technical documentation content has a product, feature, issue, and content type, so these are faceted classifications. But with more heterogeneous content, facets are not universally shared. While the facets may still be useful tool, it would be best not call it faceted classification when facets are applicable to only some content types.

While faceted classification tends to be quite limited in the number of its facets, non-classification faceted taxonomies, whether based on subject types or separate controlled vocabularies, could result in a rather large number of facets.

Faceted taxonomies that would not be considered faceted classification include those where multiple facets are created for organizing and breaking down subjects or when multiple facets are created for reflecting multiple different controlled vocabularies. These faceted taxonomies stretch the meaning of “facet,” since the facets are not necessarily faces, dimensions, or aspects, but simply “types” suitable for filtering.

Facets for organizing subjects

In faceted classification we assign an object or content item to multiple different classes. However, for classification, these classes are relevant to the content item as a whole. This contrasts with indexing or tagging for subjects or names of relevance that occur within a text or are depicted within a media asset. These names and subjects can be grouped into facets for filtering/limiting search results, without being about the “classification” of the content item.  This is common for specialized subject areas. Faceted taxonomies provide a form of guided navigation and are easier to browse and use than deep hierarchical taxonomies, so a large “subject” taxonomy could be broken down into specific subject-type facets.

Examples of specific subject-type facets include:

• Organization types
• Product types
• Technologies
• Activities
• Industries
• Disciplines
• Job roles
• Event types
• Topics

The “Topics” facet is then used for the leftover generic subject concepts that do not belong in any of the other specialized facets. Unlike faceted classification, each facet is applicable to only some content items.

Any content item could be tagged with any number of concepts from any number of these facets. The facets make it easier for user to find taxonomy concepts and combine them. But the facets are not for “classifying” the content.

While faceted taxonomies should also ideally be mutually exclusive, in contrast to the principle of faceted classification, the occasional exception of a concept belonging to more than one subject-type facet (question word of “What”) does not create a problem in search. For example, the same concept Data catalogs, could be in the facet Product Types and Technologies, as long as this type of polyhierarchy is kept to a minimum to avoid confusion. This would not be considered a case of classic polyhierarchy, because it’s not simply a matter of different broader concepts, but rather different facets or concept schemes. It is an attempt to address a different focus or approach to the topic that results it being in more than one facet, offering an additional starting point for searchers.

Facets for organizing controlled vocabularies

Faceted filters/refinement may be based on different controlled vocabulary types: one or more of term lists, name authorities, and subject thesauri/taxonomies. The “facets” are based on how the set of multiple controlled vocabularies is organized rather than based on “aspects” of the content.

Facets could be used for any controlled vocabulary filters that are logical, such as:

• Named people (mentioned/discussed)
• Organizations (mentioned/discussed)
• Products/brands (mentioned/discussed)
• Divisions, departments, units (mentioned/discussed)
• Named works/document titles (mentioned/discussed)
• Places (mentioned/discussed)
• Topics (mentioned/discussed)

Because these facets reflect controlled vocabularies of concepts used to tag content for relevant occurrences of the subject/name and not for classification of the content, this kind of faceted taxonomy would not be considered faceted classification. There could, however, be additional faceted classification types, such as content type.

The Topics facet could contain a large hierarchical taxonomy or thesaurus. As such, this faceted search/browse structure, may not even be considered a “faceted taxonomy,” but rather merely a faceted search interface to a set of taxonomies. Thus, there is even a nuanced difference between a faceted browse UI that utilizes at taxonomy (among other controlled vocabularies), and a “faceted taxonomy.”

Facets for heterogeneous content

Finally, whether a faceted taxonomy is considered an implementation of faceted “classification” or not may depend on the context and type of content. If the content is homogeneous and all items share the same facets, then it may be considered faceted classification, but if the content is heterogeneous, and the facets are only relevant to some content, then it would not be considered classification.

Consider the following example of specialized subject-based facets for the field of medicine:

• Diseases or conditions
• Body parts (anatomy)
• Sign and symptoms
• Treatments
• Patient population types

If all the content comprised just clinical case studies, then these facets actually could be considered faceted classification, since they all apply to nearly all the content and are aspects of the content. The content is classified by these facets. On the other hand, if the content dealt with all kinds of documents that had something to do with health or medicine, then these facets would not be for classification of the content but rather just for grouping of subjects for search filters.

When faceted classification is not a taxonomy

Attributes for computers

Finally, I would not consider all faceted structures to be faceted taxonomies.

Taxonomies are primarily for subjects and may include named entities. Content types/document types may also be included in the scope of taxonomy. There exists additional metadata that may be desired for filtering/refining searches that is out of scope of a definition of taxonomy. This includes date published/uploaded, file format, author/creator, document/approval status, etc. If it is important to the end users, these additional metadata properties could be included among the browsable facets and be considered classification aspects.

Attributes are a form of faceted classification, but a set of attributes is not really a faceted taxonomy. Often ecommerce taxonomies are presented as examples of faceted taxonomies. In fact, ecommerce taxonomies tend to be hierarchical, as they present categories and subcategories of types of products for the users to browse. At lower, more specific levels of the hierarchy, the user then has the additional option to narrow the results further by selecting values from various attributes that are shared among the products within the same product category. These include color, size/dimensions, price range, and product-specific features. I would not consider numeric values to be a taxonomy, but some attributes, such as for features, are more within the realm of taxonomies. Whether these should be called facets or attributes is a matter of debate. More about attributes is discussed in my past blog post “Attributes in Taxonomies.”

Conclusions

Not all faceted taxonomies are faceted classifications, but some are. Not all faceted classifications are taxonomies, but some are. The differences are nuanced, and end-users may not care nor need to know these naming distinctions, as long as the taxonomist should. Having a deep understanding of facets helps taxonomists and information architects design the facets better. The goal is to serve the users with the most suitable faceted design to serve their needs and accommodate the set of content.

Attributes in Taxonomies

When I had done consulting for ecommerce taxonomy clients years ago, and they would refer to the taxonomy facets for products as “attributes,” I felt that might be confusing, because I considered “attributes” something else: a characteristic like metadata of a taxonomy term or a feature of an ontology. I have since come to realize that facets in some cases, especially in ecommerce, can be considered attributes, and they can even be managed in an ontology that is combined with the taxonomy.

Facets in a faceted taxonomy are various taxonomy term “types” that function as refinements or filters in the user interface for limiting search results on content that share similar types of terms or attributes. Users refine or filter their searches by selecting a term or value from each of two or more facets. In a periodical article research database offered by a library, facets might be subject, geographic place, named person, named organization, article type, publication name. Within an enterprise intranet of enterprise content management system facets might be topic, department, office location, and document type. In a health information service, facets might be symptom, body part, patient age, and  patient gender. In a corporate knowledge base for customer service, facets might be product type, brand name, market, region, issue type, and customer type. In most of these cases, a topical taxonomy is one of the facets, even if that topical taxonomy is hierarchical. The primary taxonomy design challenge in such cases is deciding what kind of information would be useful if separated out in its own facet, and what can remain in the generic topics facet. Using the SKOS (Simple Knowledge Organization System) model, each concept scheme serves as a facet.

In a product, ecommerce or marketplace taxonomy, the hierarchical taxonomy of product types is not one of the facets. This large, hierarchical taxonomy is typically the starting point for user browsing. While not constituting a facet, this hierarchy is linked to the facets. The user navigates or drills down through a hierarchical tree of product categories, until a specific product type is found, and then the facets (attributes) relevant to that product type are made available to the user, allowing the user to refine the search further, by selecting from each of several attributes, such as size, color, material, price, and features. This requires a different approach to the taxonomy design than for the faceted taxonomies described above, and thus these post-hierarchical-browse refinements are better known as and more appropriately called attributes.

Attributes can serve as refinements/filters in taxonomies for purposes other than ecommerce, such as job board taxonomies (attributes for job location, skill level, salary range, job type, employer/company, industry, date posted, etc.), an internal enterprise expert-finder (attributes for job title, department, office/work location, skills, subject areas of interest, academic degree, languages, etc.) or taxonomies of movies (attributes for genre, production company, production country, language, award winner type, release date, etc.)

The attributes generally pertain to specific named entities, such as the name of a product offered by a specific seller, the name of a job title at a specific employer, or the title of a movie. There can be attributes for more than one kind of named entity in the same set of taxonomies, such as for employer name in addition to job title in a job board taxonomy. Subjects, which are not named entities, usually do not have attributes, but some do, especially, in the fields of science and medicine, where they would be attributes on the names of species, chemicals, viruses, diseases, etc. I will discuss named entities in more detail in my next blog post.

Issues to consider in creating attributes

In a taxonomy where attributes are important, there are various issues to consider. First, shall there be a hierarchical topical taxonomy presented as an initial browse interface to the users? While this is typical for product/ecommerce taxonomies, it is not usually the case for job board taxonomies nor for a taxonomy for movies. However, it may be desired for a taxonomy of nonfiction books or periodicals, which users more often would categorize my subject. A producer or publisher of educational content will likely have a hierarchical taxonomy of disciplines or subject areas. A research-focused organization would also likely have a hierarchical subject taxonomy in addition to the facet-attributes dealing with location, type, funding source/sponsor, researcher name, etc. Having a hierarchical taxonomy outside of the attributes tends to be a user experience design decision, but it has an important impact on how the overall taxonomy is designed and managed.

More attributes may be created than usable for filtering/refining results. For example, products will likely have SKU numbers among their attributes, which can be displayed and perhaps even made searchable, but would not be one of the filtering-facets presented in the user interface. In a taxonomy for finding internal experts, contact information, such as an email address and phone number, would be attributes on each person’s profile, but these would not be searchable fields. Rather, they would display when the person profile is selected. Thus, another issue when creating attributes is determining which will display and function as filters/refinements and which will display only as additional metadata on a selected item.

If an initial hierarchical topical taxonomy is presented to the users, there arises the question of at what point in the hierarchy should the hierarchy of categories should end and further details should be treated instead with attributes? This question often comes up when designing ecommerce taxonomies. For example, to distinguish gas and electric stoves, should each of these types be a narrower term of stoves, or should energy source be an attribute of stoves?

Another issue to resolve is determining which attributes should be generic across all categories, and which should be category specific. For example, on which product categories in an ecommerce taxonomy is it appropriate to have an attribute for gender (as for clothing or a gift for a woman or for a man)? Related to that is the question of which categories should have their own unique attributes. Are some attributes relevant to major (the broadest) categories, and other attributes relevant only the most specific categories, and yet other attributes apply to various miscellaneous products? For example, color might be relevant for products in different parts of the hierarchy.

Attributes should be managed as belonging to different types based on their values, such as whether they are of controlled vocabularies, dates, currency, numbers, or a simply a Boolean yes/no, such as Remote being an attribute of jobs. If a hierarchical taxonomy resides outside of the attributes, then controlled vocabulary attributes are an additional part of a larger set of taxonomies/controlled vocabularies. How this is managed varies based on the taxonomy/ontology management tool. For example, such term lists might need to be managed as separate concept schemes in a SKOS taxonomy, even though they are used in ontology-based attributes. It can start getting complicated when an attribute type has different values for different categories in the same hierarchical taxonomy implementation. For example, the attribute of Material could have different values for tables than for clothing, and both categories are offered by the same ecommerce seller.

Attributes add another level or layer of expressivity to a taxonomy or set of controlled vocabularies, which brings it closer to an ontology. The distinction between taxonomy and ontology is not necessarily clear. It’s fine to have just some ontology-like features, such as attributes, but it is recommended to use a taxonomy/ontology management tool, such as PoolParty, which manages taxonomies and ontologies (and anything in between) according to Semantic Web/World Wide Web Consortium (W3C) standards.