Taxonomy Governance

Recently I was asked to speak on a panel on taxonomy governance, so this gave me an opportunity to reflect more on the subject. "Metadata Enhancement for Improved Content Management - Taxonomies and Governance" was the title of a panel I spoke on at the Gilbane Conference 2013: Content and the Digital Experience in Boston on December 3.

When I had first heard of "governance" with respect to knowledge management and taxonomies, in 2005, it did not sound like a subject of interest to me. Perhaps I was thinking of it in terms business process management in general, which is not my field. Over the years I have come to realize that governance is a very important part of any taxonomy, and while governance can be limited to the governing the taxonomy itself it can extend to other areas that are related to the taxonomy, such as indexing and content management. Most significantly, though, there is a synergy or dualism of taxonomies and governance: to be effective taxonomies must be governed, yet the existence of a taxonomy itself is a form of governance.  A taxonomy, after all, is a kind of controlled vocabulary, and “controlled” means governed. It's better to describe what taxonomy governance entails than to try to define it. Taxonomy governance comprises the policies, procedures, and documentation for the ongoing management and use of taxonomy. 

My main points in my brief presentation were:

• Governance process begins when taxonomy development begins.
• Each taxonomy is unique and has its own governance policy.
• Governance includes both:
  • Documented editorial policies
  • Taxonomy management procedures and responsibilities
• There are minimal guidelines to a taxonomy when it is started.
• Decisions reached to questions as they come up in the process are documented and eventually become policy.
• Taxonomy policy/guidelines includes both:
  • Taxonomy specifications, style and maintenance
  • Taxonomy usage and indexing/tagging/categorization policy (manual or automated)

Reflecting on the different taxonomy jobs I have had and projects I have worked on, taxonomy governance has taken many forms beyond the obvious of documenting the taxonomy editorial policies. Even though I did not hear of taxonomy governance until I had been working for years with taxonomies, I actually had been involved with governance for many years prior, just not by that name. My first job working with taxonomies (called then controlled vocabularies) was with the title of Vocabulary and Quality Management Specialist. In addition to maintaining the controlled vocabularies according to prescribed procedures, my duties included writing guidelines for the indexers using the vocabularies, especially for new topics and current events, and checking the published content for possible vocabulary-related quality issues. At my next employer, a developer of search software with built-in taxonomies, documenting how to create the taxonomies in a consistent style was simply a part of the documenting how to use the software. Later, on an assignment with a consulting firm, on ongoing contract involved making regular updates to ecommerce client's product taxonomy, following a certain procedure and workflow that was tracked in SharePoint. Finally, in more recent years as an independent taxonomy consultant, I have made sure that taxonomy editorial policies and maintenance guidelines are always a part of my project plans.

When a taxonomy project is short on time or budget, there may be a temptation to skip the governance documentation and planning. But in the long term, that will cost more. Time will be wasted by the taxonomy editors going back through old emails to try to find out what was decided when individual questions came up. Taxonomy editors will also waste time having to redo some of their work, after realizing that they were not following a consistent style or policy. Finally, and most crucially, lack of governance will likely result in an inconsistently developed taxonomy, which in turn leads to inconsistent indexing/tagging, no matter the method used. Then the main purpose of the taxonomy is defeated.

Taxonomy governance might not be as hot a topic as it was a few years ago, but that's only because it has become standard, accepted practice. Yet there is still a lot that an organization owning a taxonomy can learn about governance in the form of best practices and case studies. While organizations may not want to share their taxonomies, as intellectual property, hopefully they will share their experiences and tips on taxonomy governance.

Information Architecture and Taxonomies

While interest in “information architecture” by that name has declined in the past decade, interest in what information architecture involves continues to be strong, and perhaps there is some merging of the fields of taxonomy and information architecture.

At one point in my career I wanted to be an information architect, to organize the pages and menus of websites and intranets.  The discipline’s leading professional association, the IA Institute additionally describes the field as “The structural design of shared information environments.” But within a couple of years, I found that interest in my information architecture skills, at least for small websites (“little IA”) was getting squeezed out for skills in either graphic design or technical web development. Over time it also seemed as if information architecture was being replaced by the growing field of user experience design (UXD). Indeed Google search trends show a definite decline in interest in the phrase “information architecture” during the same period of a steady growth in interest in “user experience.”

I was therefore pleasantly surprised to find that information architecture was one of the themes at this year’s Taxonomy Boot Camp (Washington, DC, November 5-6, 2013), the leading conference dedicated to taxonomies.

Information architecture was a central part of the keynote “Taxonomy Is Power: Bringing It All Together,” presented by Bob Boiko. He started off explaining that information systems are a triad of people, information, and technology. But he, too, had observed that information architecture (IA) has often been “captured” by user experience (UX), moving away from technology toward the user, but the “information” piece of the triad sometimes gets lost along the way and needs more attention. Bob defined information architecture as “the art and science of designing information structures” and that information architects live in the space between art (design) and science (technology). Information architecture is also about naming things, and taxonomies can help engineers and designers name things for both the front end and back end of an information system. Bob said that taxonomists should look at and “own” the concept of information architecture.

The conference also featured a session of three presentations under the heading “User Experience (UX) in Taxonomy Design.” Michael Rudy, of  the consultancy Factor, spoke on the benefits of integrating user experience  with information management, and Bram Wessel, also of Factor, presented on how different methods of user research, common in user experience design, such as card sorting, tree testing, personas, and prototyping, are also applicable to taxonomies. Taking a different angle to the issue, Ben Licciardi of PPC presented methods of designing the manual indexing/tagging interface for taxonomy use.

There are various perspectives and approaches to this field, whether stressing structure as in “architecture,” naming, as in “taxonomy,” or meaning, as in “semantics.” Different labels may resonate better with different audiences. The week of the conference I was also indexing a book on user experience design (a small project to do on the plane and to broaden my knowledge of the subject). While “taxonomy” was not mentioned in this light book, “semantic design” was the name of a section which mentioned information architecture, organizing information, and metadata.

Several years ago, perhaps 2007, when I introduced myself as a taxonomist to someone at a professional conference, I was asked what the difference was between taxonomists and information architects. My answer then is the same as it is now: there is definitely a significant area of overlap between the skills, tasks, and responsibilities in both professions, although there are some areas that concern information architects and not most taxonomists, and there are areas that concern taxonomists and not most information architects. So, it may only depend on what kind of information architect or kind of taxonomist you are. I hope one day to also attend the main information architecture conference, the IA Summit and continue this discussion, as interest in taxonomies is remaining strong.

Taxonomies and Text Analytics Compared

Last week (September 30 – October 1) I attended the Text Analytics World conference in Boston as an invited speaker.  This is the second year was fortunate to present at and attend this conference, which also meets in San Francisco in the spring. I posted a blog about the conference last fall, “Text Analytics and Taxonomies,” discussing the strong connections between taxonomies and text analytics in serving similar data/information retrieval goals. That connection between the two was again apparent at this year’s conference, with many speakers mentioning taxonomies, and I came away with additional analogies, beyond their shared purpose.

Problematic definition

Both taxonomies and text analytics are not well defined, and can have both a narrow definition and a broad definition. For taxonomies, the narrower meaning is a hierarchical tree of concepts arranged with broader and narrower relationships. The broad meaning of taxonomy is any controlled vocabulary, whether hierarchies, facets, thesauri, authority files, or simple terms lists to fill metadata fields. For text analytics, the narrower meaning is “text mining”, the process of deriving high-quality information contained in natural language text. But the conference chair, Tom Reamy of the KAPS Group, explained that the conference takes a broader definition of text analytics to include not only text mining but also, auto-categorization, sentiment analysis, predictive analytics, entity extraction, and machine learning.

There is also the issue of whether the name is appropriate. Some people don’t like the name taxonomies, and try to avoid it. Similarly, there are issues with the designation of “text analytics.” Discussion in the conference’s expert sessions and closing session, brought up the issue that perhaps a better name is needed for the field. Both “text” and “analytics” have issues, as they both have assumed narrower meanings. It comes out of the field of knowledge management, but that field is too broad. A more accurate label that Tom Reamy suggested was “unified data insights,” but it will stay text analytics for now.

Technology and human effort

Both taxonomies and text analytics rely on technology/software, but neither is a 100% automated solution, nor can the software products be used an out-of-the-box solutions without significant trained and skilled usage. If we consider the software as “tools” rather than “solutions,” we have a more realistic understanding of what the software can do. The process of building a taxonomy is aided by taxonomy or thesaurus management software, which is kind of a tool that an experienced taxonomist uses to manage the terms, relationships, synonyms, notes/definitions, and other term attributes. Similarly text analytics software, and auto-classification software in particular, requires expertise to leverage the tool for desired results. This was the theme of a presentation on selecting text analytics tools by Janine Johnson of Versik Analytics (who also used “tool” in her presentation title).

As I explained in my presentation, “Taxonomies for Auto-Tagging Unstructured Content,” both of the leading methods of auto-categorization, rules-based machine learning statistical methods, require considerable human input. In rules-based auto-categorization, experts need to write or edit rules for each taxonomy concept that leverage combinations of synonyms and proximity or other Boolean operators; and in machine-learning auto-categorization, experts need to identify and essentially pre-index a large set of sample documents for each taxonomy term, for the system to learn from the human indexed example.

Multidisciplinary background

Both taxonomies and text analytics are seen as a fields of expertise, methods of knowledge management, and at least parts of a solution to an organization’s information management problem. However they are not academic disciplines or majors. Rather, the educational background and skills of people who work in the fields of both taxonomies and text analytics is somewhat varied and multidisciplinary.

In taxonomies, library/information science is the most dominant background, but probably does not account for any more than half of practicing taxonomies. Information architecture/user experience design, database design, knowledge management, editorial, and subject matter (health, law, science, business, etc.) expertise are also common backgrounds.

In text analytics, computer science is the most common background. A show of hands of the conference participants indicated that the majority had computer science or engineering backgrounds. But linguistics is also important (although the small minority at this conference were more hesitant to reveal themselves). The keynote speaker, Dr. James Pennebaker, was a psychologist and explained why psychology is also important to text analytics. Participants in the closing expert panel answered my question on educational background with a similar answer of a combination of computer science/programming, linguistics, and cognitive sciences.

In addition to the interdisciplinary background of taxonomists and text analytics professionals, the applications of taxonomies and text analytics also span all disciplines and industries. Conference case studies included applications of text analytics in education, pharmaceuticals, healthcare, publishing, telecommunications, and federal agencies.

Taxonomy Terms with “And”

In considering best practices for developing taxonomy term labels or names, there is the question about the use of the word “and” within taxonomy terms. My previous two blog posts were called “Tags and Categories” and “Card Sorting and Taxonomies,” which demonstrate how common it is to have the word “and” in titles, headings, or other labels. By extension, does it work in taxonomy terms?

The standards for taxonomies, ANSI/NSIO Z39.19 Guidelines for the Construction, Format, and Management of Monolingual Controlled Vocabularies and ISO 25964-1 Thesauri and Interoperability with Other Vocabularies make no mention of terms with the word “and.” While it is not explicitly prohibited, it is neither mentioned as an acceptable form among the rather exhaustive list of term format types. Even the section on compound terms makes no mention of terms with the word “and.” So, one might conclude that terms should not have the word “and” within them. Yet it is not uncommon, especially in larger, more specialized taxonomies and thesauri.

The simple little word “and” can actually have two different meanings:

1)      the intersection of two concepts, to include only that which belongs to both, which is the Boolean operator AND

2)      the combination or union of two concepts, to include any of either, which is actually the Boolean operator OR.

When it comes to taxonomy terms, the word “and” could have either of the above two usages, and it’s very important to know which it is in which case.

“And” meaning AND

My blog post title “Card Sorting and Taxonomies” involves the first meaning, the intersection of both concepts, which in this case is the use and suitability of card sorting specifically for taxonomies. “Card Sorting and Taxonomies” is more concise than saying “the suitability of card sorting for taxonomies,” and taxonomy terms need to be concise. Examples of the use of “and” in this (Boolean AND) meaning in taxonomy terms that I have run across include:

    Children and Television

    Gender and Poverty

The choice of using “and” is significant. It means any intersection/relation of these two concepts. “Children and Television” comprises all of the following: children’s television shows, the impact of television (not just children’s programming) on children, the depiction of children in television, etc. Similarly “Gender and Poverty” covers various issues, such as data on poverty rates by gender, how poverty effects the genders differently, and reasons why more women are poor in developing countries.

It is easy to identify this meaning of the word “and” when the two concepts linked by the conjunction are quite distinct. In many taxonomies, the preferred policy is to avoid creating such terms, lest the taxonomy become too large and complex.

“And” meaning OR

My blog post title “Tags and Categories” involves the second meaning, the combination of both concepts. I described what tags were and what categories were and compared them. Examples of the use of “and” in this (Boolean OR) meaning in taxonomy terms that I have run across include:

   Measurement and Analysis

   Laws and Regulations

   Roads and Highways

   Maintenance and Repair

An additional example is the title of the online course I teach: “Taxonomies and Controlled Vocabularies.”

The main reason to create such terms is that, while some content deals with one or the other of the two linked words, a significant amount of content really has to do with both, and users probably don’t care to make the distinction either, so it’s better to have just a single concept in the taxonomy. But one word is not equivalent to the other, so a taxonomy term cannot be created from just one word and the other designated as its nonpreferred term/synonym. Another situation for these types of taxonomy terms is a small browsable taxonomy that does not utilize/support synonyms. An additional reason to create them is that they can boost SEO (search engine optimization) in website labels by giving more words prominence. Finally, the combined terms can also appease competing stakeholders who both want their preferred label as part of the term name.

The difference in a taxonomy

If you have taxonomy terms with the word “and” in them, it needs to be clear which of these two Boolean meanings it is, not only to ensure accurate content tagging, but also to ensure the proper relationship of the term to other terms in the taxonomy. Recently I was reviewing a taxonomy with the term “Investment and Trade” and by itself, I could not determine whether it meant the intersection of combination of these two words, so I didn’t not know how it should be related to terms of “Investment” and “Trade.”

A term with the Boolean AND is a narrower term to terms of both its component parts, what is known as polyhierarchy. “Children and Television” is narrower to both “Children” and to “Television.” When there occurs a term with Boolean OR, such as “Measurement and Analysis,” it is expected that the component words to not exist as preferred terms in the taxonomy. Rather, each word “Measurement” and “Analysis” could be nonpreferred terms/synonyms for “Measurement and Analysis.

Card Sorting and Taxonomies

Card sorting is a common technique in information architecture for developing the organization of menu labels or categories on websites. It would thus seem to be a very suited methodology for developing all kinds of taxonomies, but in actual practice card sorting is not utilized for most taxonomy projects, at least not in my experience.

Card sorting gets its name from the paper-based approach of having numerous category or concept names written down each on a small index card, and then the cards can be sorted on a table into logical categories. Multiple stakeholders and/or test users are given the opportunity in turn to organize the cards as they deem appropriate, and the person administering the card sort, takes note of the choices and considers them for the actual organization structure. Today, card-sorting software, especially that which is web-based to allow remote access, has largely replaced the physical cards.

There are two variants to card-sorting exercises, the open card sort and the closed card sort. In an open card sort, participants sort the labeled cards in any groupings they see fit and then they assign their category groups with any group name they want. In a closed card sort, the participants are already presented with a set of named top category groups that they cannot change, and are asked to sort the labeled cards into the pre-assigned categories. Each type of card sort has distinct objectives and is suited for different stages of the project.

Open card sorting is a good way to get a new taxonomy from scratch off the ground when you have some concepts (extracted from the content) and don’t know how to organize them. However, this is increasingly no longer the scenario. It’s rare to start creating a taxonomy from scratch with no other reference for top categories. There are so many taxonomies in existence now for all subjects, that it’s easy to find a starting point as a model. Furthermore, the owner of a taxonomy may have already designated the top categories for business reasons.

The aim of closed card sorting is to determine in what broader category narrower categories belong, especially if there is uncertainty. But if a narrower category could rightfully belong under more than one category, rather than force a choice between one or the other based on a card sort, the subcategory could belong under both. This is what taxonomists call “polyhierarchy,” and it acceptable as long as the hierarchy is sound and valid in both locations. Thus, closed card sorting is only needed when you have decided you do not want polyhierarchy.  Polyhierarchy is generally a good thing, because it provides more than one navigation path to the same results, and different people choose different paths. Sometimes, however, polyhierarchy is avoided near the top levels of a taxonomy in order to maintain a sense of tree structure.

Card sorting is most practical for just two levels of hierarchy: concepts and their immediate parent categories. It’s possible but unwieldy to suggest to users that they may create three levels, and some card sorting software does not even allow it. Often it is more reliable to just run a second series of card sort testing for another hierarchical level in the taxonomy. However, running multiple card sort exercises for different hierarchical branches of a taxonomy can be quite impractical, if not also costly and time-consuming.

Finally, card sorting works only for traditionally hierarchical taxonomies. It does not work for faceted taxonomies, where terms from different facets/attributes are selected in combination to limit or filter search results. Faceted taxonomies are becoming increasingly common.

Card sorting continues to be useful for information architecture, though. When designing the structure of a website and its main and submenus, it can be difficult to decide what the categories should be, because the content of  a site can be unique or nonstandard. Additionally, polyhierarchy is not expected in submenus and could be confusing. Finally, website navigation is often not deeper than two or three levels, unlike many taxonomies that are often four or five levels deep and thus impractical to thoroughly design or validate with card sorting.