60.4, November 2013

Developing a Sustainable Content Strategy for a Technical Communication Body of Knowledge

Craig Baehr


Purpose: To explore strategies, goals, and practices that are part of a sustainable content strategy for the evolution and development of the technical communication body of knowledge and, by implication, other bodies of knowledge.

Method: To develop a sustainable content strategy for the body of knowledge project, informed by content analysis, user generated survey data, and benchmarked trends from other knowledge bases.

Results: An important part of content strategy for a large-scale knowledge base, such as the TCBOK, involves innovating practices with regard to the information taxonomy, tools, content assets, and information development standards, as the product and user base matures. Successful technical communication knowledge bases employ taxonomies with higher level topics that represent specific disciplines and sub-disciplines within technical communication. Integrating the human user into content strategy involves a complex interplay of user expectation and feasible decision making.

Conclusions: Developing a body of knowledge, particularly over time, may require an integrated or hybrid approach to content strategy, involving a complex set of factors that include the human user, content assets, and sustainable practices. Content strategy goals and objectives are also a function of the maturity of the user base and the content itself within a body of knowledge.

Keywords: content strategy, body of knowledge, information taxonomies and tools, content management, user engagement, knowledge base

Practitioner’s Takeaway

  • Effective content strategy is iterative and evolving; over time it is sustainable, and closely linked to both standards and practices that define a body of knowledge.
  • A significant success factor in any mature knowledge base includes maintaining both a vetted taxonomy and tools that emphasize content findability.
  • User preferences cannot always be mapped directly onto an existing information taxonomy or its tools, but they are essential for a sustainable content strategy.


A body of knowledge defines the scope and reach of foundational knowledge, trends, and expertise areas within a particular field. Certification, licensure, industries, jobs, professional organizations, conferences, and others all have an influencing factor on how a field defines its boundaries and knowledge domains. The interdisciplinary nature of what technical communicators produce, develop, design, manage, research, and the tools, collaboration models, and standards make particularly complex the task of developing a tangible knowledge base to capture the field’s body of knowledge. While many fields have their own body of knowledge, “the challenge of ours is that it is dispersed: in our own publications such as Technical Communication and Intercom, in many important books, in the academic programs that we teach, and as our profession is so interdisciplinary, across other professional organizations in our field and the many closely related fields” (Technical Communication Body of Knowledge). This article explores how bodies of knowledge are defined, codified, sustained, and matured. Specifically, it examines the case of the Technical Communication Body of Knowledge, the evolution of its content strategy, and how that strategy is closely linked to both standards and practices that define the field.

What Is a Body of Knowledge? 

A body of knowledge represents breadth and depth of knowledge in the field, with overarching connections to other disciplines and industry-wide practices. Within the field of technical communication, some examples of knowledge bases that attempt to capture a body of knowledge include the E-Server Technical Communication Library, a searchable database of publications, and the Technical Communication Body of Knowledge (TCBOK) project, a collaborative wiki on a wide range of topics in technical communication. Smaller knowledge bases exist that focus on a single topic, format, organization, or function, with depth on a particular topic. Universities such as Purdue University’s Online Writing Laboratory and the University of Alabama at Huntsville’s Technical Communication Online Resources offer information resources on specific topics such as writing assistance and online resources. Professional organizations in the field also have Web presences and publication clearinghouses that represent specific topics, groups, interests, and research priorities of the field. Some of these include the IEEE Professional Communication Society, Council for Programs in Technical and Scientific Communication (CPTSC), the Association of Teachers of Technical Writing (ATTW), and the Society for Technical Communication (STC). Corporate and government workplaces have knowledge bases that contain best practices, procedures, technical manuals, and white papers that contribute to the advancement of knowledge in the profession, both locally and globally. These smaller collections, while they have more depth than breadth, have an undisputed influence on how the field defines the boundary and content of its body of knowledge. Developing a sustainable content strategy for the evolution and development of the codified product is essential to ensure it adequately represents the corpus of knowledge and its constituents.

How Do Bodies of Knowledge Evolve? 

Two dominant, perhaps philosophical, approaches that characterize how tacit knowledge evolves into a more concrete product are folksonomy, a user-driven approach, and a taxonomy, or content-driven approach. Governor, et. al., (2009) articulates this divide as tagging (folksonomy) vs. directories (taxonomy). These approaches underscore two important aspects of the knowledge base: the user and the content. The folksonomy approach is characterized by a dominance of user preference and consensus as the guiding mental model for developing a list of topics in a knowledge base. Smith (2008) defines it as a bottom-up classification strategy that emerges from user-generated content and preferences, including content tagging. Content tagging allows users to “create their own classifications” adding descriptive keywords (or tags) to their contributions and creating links to other content (Governor et. al, 2009, p. 58). Some challenges to this approach include inconsistent uses of terminology, metadata, and editing, among a user base, which can create usability and findability problems. And, while it has a strong user-centered component as an underpinning, this approach tends to rely on social construction of knowledge over and specific information design theory, information taxonomy, or trends in the content inventory.

The taxonomy approach relies on the content assets, and in some cases, a small group of subject matter experts, to drive decisions made in organizing material into topics. These decisions might be based on a number of factors including existing content patterns, metadata, content volume, trackbacks, links, and other factors. Adaptive content, which adjusts, filters, and displays content within a content management system, can also create unforeseen challenges for users (Rockley & Cooper, 2012). Within adaptive content systems, information taxonomies might be auto-generated by the system, which can create potential usability problems if users fail to comprehend the taxonomy or navigation structure. A taxonomy approach also differs from the folksonomy in that it may not incorporate specific user preferences in organizing content. This approach might have a tendency to favor the content product itself over users, which might impede usability and accessibility.

Value propositions and a body of knowledge are closely linked in scope and reach. While the former outlines the idealized value of work the field is capable of producing, the latter has the responsibility of communicating domain-specific knowledge in the various specializations, products, and skills to its constituents (practicing technical communicators and those who work with them). The value proposition for technical communication has gone through an iterative process of development, and the current version states:

Technical communicators clarify the complex for a wide variety of organizations, fields, and industries. Through expert development, management, and dissemination of information, technical communicators help increase corporate revenue, customer satisfaction, and public safety, while reducing product development time, technical support, and other direct and indirect costs. Using a wide variety of technologies, tools, and processes, technical communicators deliver a positive user experience and the right information to people, when they need it and how they need it. (Technical Communication Body of Knowledge)

These statements might drive a content-driven approach by helping define the breadth and boundaries of knowledge within the field, and can be extended to the field’s body of knowledge. They are also often written by a small group of experts in a particular field or discipline, acting as a guiding principle that informs the overall content strategy.

Content Strategy and Bodies of Knowledge 

As part of an effective content strategy, it is important to determine what factors will influence and drive the organization of content, information taxonomies, and tools users will need to effectively contribute and access content within a body of knowledge. Content strategy draws from several related disciplines and their practices, including knowledge management, content modeling and user experience. The process includes analyzing users, content, organizational needs, processes and technology to develop a strategy that is sustainable and standardized (Rockley & Cooper, 2012). Knowledge management involves a systematic approach to capturing, organizing, maintaining, and delivering information throughout an organization, both tacit and explicit (Dalkir, 2011). Content management is the “process of managing electronic content through its lifecycle—from creation, review, storage and dissemination to destruction” (Parapadakis, as cited in Clark, 2008, p. 38). Rockley and Cooper (2012) further describe it as “a repeatable method of identifying all content requirements up front, creating consistently structured content for reuse, managing that content in a definitive source, and assembling content on demand to meet customer needs” (loc. 467).

An important part of an ongoing content strategy is content modeling, or defining (and maintaining) the structure and granularity for the content assets contained within an information product, such as a knowledge base. Content assets include all types of content in a given information product or database, such as topics, articles, chunks, and multimedia. Content modeling involves a hierarchical or topical ordering of content components into a coherent organizational structure (Rockley & Cooper, 2012). Hackos (2007) uses the term topic architectures in place of content models, which involves a categorizing content from general to specific in a hierarchical structure, which might resemble a file folder structure. Within such a structure or model, hypertextual (or intertextual) links are also possible and necessary for cross-referencing and more flexible navigation within digital publications, including wikis and other content management systems. Intelligent content design involves tagging, structuring, designing, and preparing content for discovery and reuse, and ensuring searchable, tagged, predictable, or structurally rich (Rockley & Cooper, 2012). Intelligent content is structurally rich and semantically categorized, making it discoverable (findable), reusable, reconfigurable (modular), and adaptable (Rockley & Cooper, 2012). Content models also define the information architecture of the information product and serve as micro units of interconnecting content sections that inform the contextual navigation for the product (Rosenfeld & Morville, 2007). Subsequently, content models can be used to create authoring templates, structured authoring guidelines, stylesheets, and so forth. They guide authors in content creation, facilitating reuse of content, and also support adaptive content (Rockley & Cooper, 2012). The ability to share knowledge, reuse it and to innovate the ways in which both are achieved can be essential to effective content management (Dalkir, 2011).

A significant success factor of content strategy and knowledge management for electronic distribution and delivery, is technology. This involves choosing the right platform and tools. Most content management systems (CMS), incorporate “markup, metadata, and tools to break documents into component parts, to a level of granularity…set by organizationally defined information models, and labeling each part with metadata that describe its meaning and relationships to other content” (Clark, 2008, p. 39). One advantage of such an automated or adaptive content model is scalability, where the system accommodates new content by growing the structure. Automated indices, navigation tools, content editors, information templates, and stock design elements are also often components that can be integrated from content libraries within the system. Some disadvantages include a lack of customization options or usability problems from automatically generated information structures or navigation tools, which are inconsistent or uninformed by user’s mental models or expectations. These systems often require system level knowledge, such as advanced scripting and programming languages to make highly customized changes to account for these limitations. Technological systems are also not yet complex enough to personalize and customize the user experience in every possible context, emphasizing the importance of the human user in the process (Morville, 2005).

Integrating the Human User 

Dalkir (2011) also stresses the importance of the human component in knowledge management practices, which is applicable to content strategy for a body of knowledge. The practical side of developing information taxonomies and navigation tools involves user experience and other human factors. Information taxonomies must be understood by users for them to be viable information tools and helping users comprehend the structure and presentation of information. Morville (2005) stresses the importance of findability, or “the degree to which a system or environment supports navigation and retrieval,” in electronic information systems (p. 4). Findability is inherently a human factors problem, focusing on making content widely and easily accessible to users of electronic systems.

User experience design (UX) integrates three essential tasks in content strategy and information development, which to be successful, focuses on the user. These tasks include information architecture, interaction design, and user research (Unger & Chandler, 2009). This translates to an iterative process of developing site maps (overall site structure), task flows (procedural or process-oriented activity paths), annotated wireframes (interface layouts), and prototyping (working models) to design and optimize interactive experiences (Unger & Chandler, 2009).

An extension of user experience is considering how to involve users integrally as part of content strategy. Community engagement is a strategy for fostering a sense of shared or “joint enterprise” and creating opportunities for engagement, activity, and productivity (Kline & Barker, 2012). Some of the ways in which information products can successfully achieve this is through activity-based collaboration, including persona development, use of Web 2.0 social media tools (such as a LinkedIn group), and taxonomy building activities. Challenges include a lack of engagement in content writing and disputes over intellectual property and content ownership issues (Kline & Barker, 2012).

Users construct a cognitive whole or mental model of these elements based on their comprehension of content models, site maps, indices, navigation tools, and headers. Garrett (2010) conceptualizes user experience as a layer of both concrete and abstract elements, including visual design, interaction, navigation, information architecture, and rhetorical concerns, working together to create the interactive product. Effective content strategy and content modeling is a user-driven process, focusing on making choices in structure and navigation that are feasible within the constraints of the content assets and user expectation. Clark (2008) argues that effective content management involves a meaningful integration of presentation and content for the user, although in development these two activities may occur in isolation. Within content management systems, navigation tools (lists, menus, site maps, taxonomies) help connect what users see (visual presentation) and what they read (content). These tools have the potential to communicate structure, content relationships, context (location), and conceptual information about the material being accessed. Although users have different task and information priorities, the user population shares common mental patterns, attributes and expectations informed by basic psychological processes (Raskin, 2000). One approach that accommodates these psychological processes is visual thinking, which considers perceptual and cognitive acts users actively engage when conceptualizing the meaning of content in their visual field. Since electronic environments emphasize the visual and spatial presentation of content, this approach can be particularly useful in determining user expectations.

While this and other applied approaches can be informative in basic processes of how users think, perceive, and interpret visual content, it’s important to also study users in a working context since user habits and behaviors may sometimes override these instinctive behaviors, but not initially, and not without prior conditioning or experience. For example, from a content strategy perspective, developing tools and taxonomies that build on previous experiences, suggest function, and are tested, can help users solve information problems within knowledge bases. Also helpful is developing navigation tools that suggest meaning, function, structure and that incorporate familiar iconography, text-image pairing, visual conventions, consistency, and contrast. Finally, using a range of tools that corresponds to the range of user needs and content is important (Baehr, 2007).

A Body of Knowledge for Technical Communication

Started in 2007, the Technical Communication Body of Knowledge (TCBOK) is an evolving knowledge base that covers a wide range of topics in technical communication. The TCBOK exists on a wiki platform moderated by a managing editor and technical manager, with its own internal documentation policies for content writing, editing and reviewing. The document types it contains include topic introduction pages, supporting content pages, reference pages, and annotated bibliography pages. Additional content assets include an alphabetical page index, glossary, dictionary, bibliography, and portal map. The navigation tools include a hierarchical navigation menu, keyword search, personas, and alphabetical topic index.

From 2007 to 2009, the initial phases of the project included developing a framework, refining the framework, and developing strategic governance (Coppola, 2010). In 2009, the TCBOK became an online presence in the form of a collaborative wiki and since the two years that followed this initial and important groundwork, the TCBOK has functioned in a production phase, with periods of high and low activity, as users contributed content to the growing knowledge base.

The initial guiding metaphor of the TCBOK has been the user persona, or more specifically the unique range of users and their information needs (Coppola, 2010). Throughout its history, the development and restructuring of the framework has been informed by user feedback, through surveys, interactive mind-mapping (card sorts, “walk the wall” event), conference focus groups, and user feedback. With its history, the project has been vetted, organized, commented on, and informed by a wide range of academics, professionals, and subject matter experts representing a breadth of user experience.

As a large-scale collaborative authoring project, the body of knowledge project enlists academic and workplace practitioners in an ongoing dialog of what knowledge defines the boundaries of the field. Ideally, a body of knowledge, such as the TCBOK, is designed based on best practices and trends from other knowledge portal paradigms and frameworks from other professions with close ties to technical communication (Coppola, 2010). Two challenges that have been ongoing throughout the lifecycle of the project have involved semantics (naming) and structuring (content organization). Kline and Barker (2012) attribute these challenges to differences in discourse styles, employment structures, and collaboration structures, among others, common to academic and industry partnerships. The ongoing development of such a project is sustained largely by online, virtual collaboration, face to face meetings, workshops and the other related activities previously mentioned. And, a body of knowledge evolves with changes in the global workplace, technology, and other factors.

Current Content Strategy Goals 

In summer of 2012, a new team of facilitators began developing a content strategy for the TCBOK based on current research and best practices in the field. Three important elements of the content strategy involve the users and their experience, the content itself, and the facilitators who currently oversee the project. As the project has matured, the user base has widened in expertise and size, the content has grown in volume, and the experts who oversee the project have transitioned on and off the project. From September 2012 to August 2013, the TCBOK has had more than 67,000 visits, 255,000 pages accessed, and a total of 465,272 hits (TCBOK). To date, there are more than 600 authored content topics and 100 contributing authors (Technical Communication Body of Knowledge).

As users have contributed more content in recent years, the taxonomy has expanded beyond its initial structural model. A significant part of the content strategy for the body of knowledge also involves user expectations and benchmarked trends in the field. Collectively, these elements become specific goals to help the project continue to be sustainable and grow as a body of knowledge and valuable resource. As part of the content strategy, the facilitators are using a hybrid folksonomy and content-driven approach that considers both human factors (user preferences, mental models) and content factors (existing content assets and information taxonomy). Also, the project has a long history of user engagement and a significant content volume, which suggested the hybrid approach. The specific content strategy goals for this approach included the following:

  • Analyze and evaluate existing content assets to see what trends (and problems) might suggest and improve findability and social engagement opportunities
  • Gain an understanding of the mental models of users and how they comprehend the information taxonomy of a body of knowledge
  • Synthesize findings in a discussion-based format with the facilitators’ team to determine production tasks including revision to content, information taxonomies, navigation tools, and publication standards

As part of the re-formulated content strategy, these objectives and their corresponding tasks were assigned to one of three teams: content restructuring, social engagement and publication standards. As the volume and users for such a large-scale project grow,
the information taxonomy complexity increases, affording opportunities to consider different approaches to searching and browsing, engaging users, and publication standards. An initial task was to develop prototype subject or topic based indices that would broaden the tools available to users, accommodating both seasoned expert and novice technical communicator. Other tasks considered were a tagging strategy for content and making adjustments to the information taxonomy and site navigation menus towards the goal of improved findability.

Evaluating Existing Content Assets and Models 

The first content strategy goal was to analyze and evaluate existing content assets to see what trends (and problems) might suggest improved findability and social engagement opportunities. This involved two important tasks, the first being a comprehensive review of the information taxonomy, including the alphabetic index and information model map. The second task was to examine data collected from other knowledge portals, including topic lists, navigation tools, and patterns. Collectively, these data potentially reflect patterns and problems that may suggest ways to improve a body of knowledge.

Screen Shot 2014-01-06 at 2.54.14 PMOne important distinction to make while reviewing the inventory was separating domain knowledge topics, such as information design, from meta-content, such as user comments, historical timelines, and procedural documentation for the TCBOK project itself. Domain knowledge content includes a wide range of topic entries on everything from information development, project management, usability testing, and instructional design, to structured authoring, and professional organizations. The topics represent trends in research, publications, conference topics, courses, and professional development topics. The meta-content includes content about the body of knowledge project, its history, background, development, and user comments. This content provides more contextual information and background on the project as do discussion points raised on individual domain knowledge topics. Both individuals and groups have contributed to content in the TCBOK, from the academic and industry sectors. Several tools were available to search and browse content, including an alphabetical index, information model map, and
multi-level hierarchical navigation menus.

The alphabetic index of content topics is an auto-generated list that also provides direct links to each content topic by its individual title. The index includes individually titled pages that contain domain content, meta-content, node pages, and other content (see Figure 1).

The titles of some topics, which varied in style based on individual contributor, created some obvious indexing problems. For example, “A Guide to Proposal Writing for Technical Communicators” was previously listed under A, whereas a more keyword and index friendly title might be “Proposal Writing Guidelines.” As a navigation tool, the index was useful in finding information, particularly when the keyword search was less helpful. For example, when looking for “science writing” using the search tool, the desired page fails to appear on the first full page of results, but looking for the same keywords under the alphabetic index was more helpful.

Screen Shot 2014-01-06 at 2.54.24 PMThe information model map, generated from comapping.com, provided a hierarchical list of topics from general to specific. The top level of the taxonomy includes four major categories: about technical communication, careers, producing technical communication, and research (see Figure 2).

While the existing structure was favored by users in the survey and preferred, one of its unfortunate limitations is the inability for users to easily access these topic pages in higher levels of the information structure. For example, more specific domain knowledge topics were found in levels 3-5, such as information design, usability, and technical editing. From the second level category “designing and developing information”, the corresponding third level topics include: information management, information design, information development, information delivery, quality assurance, translation, localization, globalization, and e-commerce. Within the third level topic “information design” heading, the fourth level topics include: design theory, needs assessment, information architecture, accessibility, content strategy, visual design, instructional design and information mapping. These topics at the third, fourth and fifth levels were more frequently represented in other information taxonomies studied.

Screen Shot 2014-01-08 at 3.11.13 PMLooking at other technical communication knowledge portals was helpful in identifying trends and differences in information modeling, when compared to the TCBOK. The sample models examined included the Certified Professional Technical Communicator (CPTC) certification domain areas, E-Server Technical Communication library, Wikipedia listing of technical communication job titles, STC list of Special Interest Groups (SIG), and the 2012 STC Summit program progression topics, as shown in Table 1. The goal was to examine the top-level information taxonomies from a range of knowledge portals, while keeping the sample small, manageable, and representative of higher level trends in information organizing patterns. The range of samples includes publication portals, conference tracks, certification models, and disciplinary emphasis groups within technical communication. Although several models were STC information resources, the samples had too much variability in the organization and topics of the information taxonomies to be useful as a model for the TCBOK.

The models in Table 1, which are examples of successful technical communication information models, tend to have taxonomies with higher level topics that are reflective of specific disciplines and sub-disciplines within technical communication, such as information design, user experience, technical editing, content management, and so forth. While there were overlapping topics in these models, there was still a significant breadth suggesting there is no ideal, perfect, or complete model in existence. Some of the suggested topics from the survey, such as marketing communication and science communication, were present in these models. Examining these models also reveals a broader range, which might suggest the potential reach of a body of knowledge, one which the current TCBOK has not yet achieved in scope. In turn, these representative models might suggest how the body of knowledge might expand to incorporate new topics that best represent the breadth and depth of the field.

Screen Shot 2014-01-06 at 3.06.55 PM

Understanding User Expectations 

For the facilitation team, incorporating the human user into the content strategy was essential not only from a user experience perspective, but also to create a more integral role for users. Toward this content strategy goal, a survey was developed to determine user-specific expectations and preferences with respect to the existing taxonomy, navigation tools, and content needs. The purpose of this survey was to better understand the mental models of users and how they comprehend the information taxonomy of a body of knowledge. The participants included users with a basic familiarity with the portal, specifically, current and previous volunteers on the project. Although approximately 50 users were selected, only 16 completed the entire survey, or 32% of the target population. Other information taxonomies, such as the E-Server Technical Communication library, STC’s list of Special Interest Groups (SIGs), and recent STC Summit programs, were consulted to provide a high level filter for possible categories and choices provided to the users in the survey.

The survey consisted of three sections. The first question asked users to examine an undifferentiated list of topics in the top three levels of the existing information taxonomy and rank them as first-level, second-level, third-level, or do not include. The second question required users to select from an alphabetical content index, compiled from the other portals, and rank each as first-level, second-level, third-level, or do not include in a possible subject index for the TCBOK. This question served as a modified version of a card sort. The third question asked users to rank usefulness of existing navigation tools on a modified Likert scale (often, seldom, somewhat, never). Each section included an open-ended question permitting participants to suggest other items or to comment on their responses.

Participants showed a preference for the existing structural model, whether by design and/or by vested interest in the previous work that had been done to create it.

For the first section, a significant majority of participants ranked categories exactly the same as the existing structure, suggesting that existing information taxonomy conformed fairly well to their mental models.

For the second section, a majority of users selected the following topics as first-level choices in a topic index: academic, e-learning and instructional design, information design, information development, technical writing and editing, and user experience (see Table 2). From the list of topics provided, none were rated “don’t include” by a majority of users. Suggested categories included marketing communication, globalization, translation, standards, and social or user-generated content. Other suggestions concerned terminology semantics, such as using content management in place of information management.

For the third section, users ranked the usefulness of tools used in knowledge portals, including the TCBOK. Five options were listed: community social media tools (forum links, social bookmarking), content assets (publication libraries, papers, and multimedia), keyword search, subject index, and user personas. While tools for keyword search, content assets, and subject index were listed by more than 90% as often and somewhat used, social media and user personal tools were rated highest as seldom or never used. Participants mentioned three other tools they preferred, including free text search, crowdsourcing and social tagging.

Despite inherent limitations to the survey, such as a small sample, overlapping responses, limited topic lists and number of questions, and users sometimes commenting outside the parameters of given instructions, there were two important insights that are applicable to a sustainable content strategy. Building or improving existing navigation tools was preferred to making significant changes to the existing information taxonomy. And, the interest in creating new or improved tools, such as a subject index and content asset list, suggested the need to promote greater access to content within the TCBOK, not only from the ratings, but in particular, from the open ended comments and suggestions provided.

Focus Group Discussion and Production Tasks 

The third major content strategy objective involved synthesizing the findings in a discussion-based format with the facilitation team to determine production tasks including revision to content, information taxonomies, navigation tools, and publication standards. Due to the overlapping nature of the specific content strategy goals and team functions, frequent discussion meetings that involved a shared decision making process were important. In some cases, the discussion involved the larger production team, content topic authors, and volunteers. For example, a full team presentation meeting was conducted to report on progress, present survey results, gather open-ended feedback on tasks, and solicit potential involvement in smaller projects. Several meeting attendees included participants from the user survey.

Information findability was one of the problems that had come up multiple times in discussions, including at larger group meetings and presentations at recent STC Summits. Users reported difficulties finding domain topics within the field, regardless of expertise. Some users felt the range of existing tools failed to provide novices or practitioners easy access to domain level topics, such as visual design (found four levels in the existing information taxonomy). In some cases, a keyword search was the only way for inexperienced users to easily find content that was found at four or five levels within the information structure. As a result, a significant part of the solution needed to ensure third, fourth and fifth level topics more visible to users.

Users preferred the existing information taxonomy but still had findability issues in locating specific topics within the knowledge base. A subject index was listed as a preferred tool, and we considered exploring ways to integrate one or more as navigation tools. We also had to be mindful of the semantic differences between a subject index appropriate for a print publication and an electronic one. The former categorizes major topics and related keywords with related detail, much like a print-based index, while the latter is more of an associative information structure categorizing specializations and topics from the general to the specific. As a result, several prototypes were developed and tested, including an alphabetic subject index and potential subject lists based on user survey preferences and suggestions.

Developing a Conventional Subject Index.  A prototype subject index was created to determine how a typical print-based subject index prototype might inform the development of a tool and its viability within a wiki-based information structure. The index was developed by selecting a random section from within the existing taxonomy and generating a list of terms for a single letter of the alphabet. While a useful tool for a print-based volume, there were many problems with using this kind of information model for an electronic-based delivery system. Many of these are indicative of the differences between print-based and electronic-based indexing. First, topics within a wiki have no page numbers, which is problematic for software tools and frustrating for indexers. Most content management systems organize content by Screen Shot 2014-01-06 at 3.07.13 PMtopic title, rather than page number, keyword, or other method. Second, as a continually evolving and changing document, maintaining an alphabetic subject index would require constant updating without a tool or module to automate the process. Third, online documents open up the possibility for more complex tagging and cross-linking. Online documents make use of more macro-level indexing through hyperlinks, navigation menus, and other indices. For example, within the index for “Cloud Computing,” healthcare industry, and software as a service are listed, but the index is built only to index relationships with other content within the same topic on a micro-level. These kinds of semantic complexities could only be managed by a human user with sufficient context sensitivity to make meaningful changes to the index.

Developing an Improved Information Taxonomy and Tools.  Specific suggestions from the survey stated that user topic preferences should inform any new tools or changes to existing ones. The existing information model was somewhat problematic in finding specific topics such as “visual design” or “technical editing” from the navigation tools provided. In addition, the complexity of the information structure sometimes makes it difficult for users to discern domain knowledge from meta-content. The first task in addressing this complexity was to revise the main navigation to split content choices from function choices, and to simplify terms to reflect the semantic differences (see Figure 3).

The previous version intermixed content choices and functional choices and used titles that created indexing problems due to editing issues. The modified version simplifies titles and separates the domain content choices (home, about, careers, producing, research) from the meta-content (contribute, personas, LinkedIn, about us, contact us).

The second task was to create a subject index appropriate for TCBOK, which improved overall information findability. Successful navigation tools tend to mirror patterns and show close alignment to the information taxonomies they support (Baehr, 2007). To create a subject index based on user preferences, the first and second level topic choices from the second question of the survey were combined. But the list was not completely representative of all user suggestions and benchmarked trends. User comments from the survey echoed many trends in the field, publications, conferences and other portals studied. The list represented also a range in individual interests and potential trends in the field, both of which are important to a body of knowledge. Some topics varied in the use of terminology, such as structured authoring and topic-based authoring while others had no content topics within the TCBOK, such as scientific communication and multimedia. The facilitators’ team discussed many of these factors and drafted a three-tiered list. Three topic lists were created, instead of one, in an attempt to satisfy the needs for a subject index and topics that might be emerging or important (see Table 3).

Emerging topics included those that were suggested by users or started as new topics within the TCBOK but never finished. Trending topics included suggested topics that were highly visible in current research. User feedback, Web analytics, expert focus groups, journal special issue topics are all potential sustainable sources of new items to add to the emerging and trending lists. As a sustainable content strategy goal, such lists can be advertised or featured within the body of knowledge to encourage new content contributions. Subsequent surveys, feedback, and integration of new tools and platform choices may also help these information taxonomies evolve to better suit the needs of users and represent trends in the field.

The third task involved revising policies and procedures for contributing and editing content. While only minor editorial changes were required, the revisions covered sections of the content and copyright standards, style guidelines, and contributing content. As the body of knowledge expands and evolves, these standards must be updated to reflect how users contribute, comment and use content in meaningful ways. Such sustainable practices can lead to effective content strategy.

Screen Shot 2014-01-06 at 3.07.26 PM


Within the scope of an information development project that seeks to represent and codify a body of knowledge, complexities in content strategy exist with users (what is preferable and expected), information modeling tasks (what is comprehensible and consistent) and technology (what is feasible). User preferences cannot always be mapped directly onto a usable information model, but can be an essential part of a sustainable content strategy. Research was very revealing about user topic and navigation tool preferences, which helped make user-centered decisions on building navigation tools and lists for topic indices. The nature of the content itself and other field specific trends and terminology, however, must also have a discernible role and often determine the feasibility of user generated preferences and suggestions.

A significant success factor in developing a body of knowledge is maintaining an information taxonomy that makes content findable and accessible for its users. The breadth of possible topics from which to build an information taxonomy for a body of knowledge was quite large, as shown in the range of responses from the user survey and in the existing models studied. Integrating topics from within an existing knowledge base with topic suggestions from users and other taxonomies can be particularly challenging, though it is crucial to determine the optimum balance of user expectations and feasible choices in maintaining a viable information taxonomy and usable navigation tools.

Effective content strategy is iterative and evolving; over time it is sustainable and closely linked to standards and practices that govern a body of knowledge. Broad research of other models can help identify benchmarking trends among various venues within a discipline, and are but one piece among many in making decisions on information tools. However, there is no guarantee that users familiar with other information taxonomies will transfer their knowledge of using them, if newer models incorporate these trends.

Developing a body of knowledge, particularly over time, may require an integrated or hybrid approach to content strategy, involving a more complex set of factors. These include the human user, content assets, and sustainable practices to guarantee information findability and maximize usability. Content strategy goals and objectives are also a function of the maturity of the user base and the content itself within a body of knowledge.


Baehr, C. (2007). Web development: A visual-spatial approach. Upper Saddle River, NJ: Prentice Hall.

Certification. (2013). Society for Technical Communication. Retrieved from https://www.stc.org/education/certification/certification-main

Clark, D. (2008). Content management and the separation of presentation and content. Technical Communication Quarterly, 17, 35-60.

Coppola, N. (2010). The technical communication body of knowledge initiative: An academic-practitioner partnership. Technical Communication, 57, 11-25.

Dalkir, K. (2011). Knowledge management in theory and practice (2nd ed.). Cambridge, MA: MIT Press.

E-Server Technical Communication Library. (2013). EServer.org Accessible Writing. Retrieved from: http://eserver.org

Garrett, J. (2010). The elements of user experience: User-centered design for the web and beyond (2nd. ed.). New York, NY: New Riders Press.

Governor, J., Hinchcliffe, D., & Nickull, D. (2009). Web 2.0 architectures. Sebastopol, CA: O’Reilly Media.

Hackos, J. (2007). Information development: Managing your documentation projects, portfolios, and people. Indianapolis, IN: John Wiley.

Kline, J., & Barker, T. (2012). Negotiating professional consciousness in technical communication: A community of practice approach. Technical Communication, 59, 32-48.

Morville, P. (2005). Ambient findability. Sebastopol, CA: O’Reilly Media.

Raskin, J. (2000). The humane interface: New directions for designing interactive systems. Boston, MA: Addison-Wesley.

Rockley, A., & Cooper, C. (2012). Managing enterprise content: A unified content strategy (2nd ed.). Berkeley, CA: New Riders.

Rosenfeld, L., & Morville, P. (2007). Information architecture for the world wide web (3rd ed.). Sebastopol, CA: O’Reilly Media.

Smith, G. (2008). Tagging: People-powered metadata for the social web. Berkeley, CA: New Riders.

Technical Communication as a profession. (n.d.). Retrieved from the Wikipedia Wiki: http://en.wikipedia.org/wiki/Technical_Communication

Technical Communication Body of Knowledge – TCBOK Home. (n.d.). Retrieved from the Technical Communication Body of Knowledge Wiki: http://stcbok.editme.com

Unger R., & Chandler C. (2009). A project guide to UX design. Berkeley, CA: Peachpit Press.


About the Author

Craig Baehr is an STC Associate Fellow and associate director of Technical Communication and Rhetoric at Texas Tech University. He is program director of the STC Academic SIG, content team facilitator for the Technical Communication Body of Knowledge project, and faculty sponsor for the STC Texas Tech University Student chapter. He is author of Web Development: A Visual-Spatial Approach and Writing for the Internet: A Guide to Real Communication in Virtual Space. Previously, he worked as a technical writer and trainer for ten years for the U.S. Army Corps of Engineers. Contact: craig.baehr@ttu.edu.

Manuscript received 3 September 2013; revised 4 October 2013; Accepted 16 October 2013.