Information Architecture provides the methods and tools for organizing, labeling, building relationships (through associations), and describing (through metadata) your unstructured content. Information Architecture is not only important for producing usable systems that provide content, making content more consumable for users and improving search and findability. IA is also a necessary component in content curation for machine learning applications to enable data analytics to be effective for your organization.
Information Architecture Framework (IAF) provides the principles and practices on how to create and implement Information Architecture (IA). An IAF is a structural scheme, providing a methodology for describing information assets that focuses on organizing and relating the content associated with the information view of an architecture. I will briefly describe the two (2) primary IA Frameworks, the Enterprise Information Architecture Checklist (EIAC) and Darwin Information Typing Architecture (DITA) and how they are used.
Enterprise Information Architecture Checklist (EIAC)
To prepare your organization to develop an IA, you must consider the structure and composition of a repository (or website), the information collection and individual document intelligence, accessing content (search and retrieval), as well as being able to locate and/or navigate to the content. In developing the IA structure, Downey and Banerjee (2011) describe a checklist in order to provide a consistent method in constructing the IA. The IA checklist presented (see Figure 4.1) evolved over a few iterations before a final IA checklist was formed. The checklist focuses on the essential areas of the IA such as the model, taxonomy, and metadata. It also identifies significant supporting areas such as information access, governance, and quality of service (security, availability, and reliability).
Enterprise Information Architecture Checklist (EIAC)
|Questions to Consider
|General The IA will consume unstructured content from various sources throughout Organization. Availability This refers to the state of readiness of content to its various consumers. Metrics This provides measurements for volume planning and success measures. (Note: This is a recurring theme throughout the checklist)
|Is the solution going to consume unstructured content (information/ knowledge) made available by other internal or external sources? Are there mechanisms to extract the needed content from multiple internal and external sources in order to support search, content discovery and analytics? Are there requirements to measure and evaluate the usage of internal and/or external content? Is there a plan for ongoing measurement and evaluation of the usage of internal and/or external content?
|Gather the requirements for content, search, as well as measurement and evaluation criteria. Perform Content (Knowledge) Audit to determine what content is ready to be consumed, evaluate the quality of content, determine the gaps in content, and identify the measurements to determine what content is used (and not used).
|General The IA has the potential to identify gaps in content where there would be a need to generate unstructured content from various sources and be consumed by various groups throughout the organization. Extraction This refers to the mechanisms to extract content from multiple sources in order to support search (Federated Search), information discovery and analytics. Characteristics This refers to the features of the content (i.e., purpose, audience, topic, Line of business) or any other descriptor (usually in the form of metadata). Metrics This provides measurements for volume planning and optimization of resource utilization and performance.
|Is the solution going to generate (create) unstructured content (information/ knowledge) to be used by internal and/or external sources and will it be available for the enterprise? Are the characteristics (i.e. metadata) of the content determined? Has the reuse of content available elsewhere in the enterprise been considered to avoid redundancy (avoid duplication of content)? Is there a requirement to measure and evaluate the volume of content (information & knowledge) being generated?
|Gather the requirements for content creation/ generation. This includes requirements for templates and style sheets. Continue performing Content (Knowledge) Audit focusing on determining the gaps in content, identifying the content sources and Identify specific content characteristics/ metadata (Utilize Content Scoping Spreadsheet) Metrics to measure and evaluate the volume of content have to be determined.
|Modeling The information (content) model depicts a graphical representation of concepts (in the form of content types), relationships, business rules and metadata. This provides a sharable, stable, and organized structure for content (information and knowledge) for the enterprise. Classification The classification of content will be in the form of one or more taxonomies. Classification of information will also be realized through controlled vocabularies and thesaurus. Semantics Semantics will address the meaning of the concepts identified in the content model as well as the meanings of the relationships between the concepts (usually expressed as business rules). Structure (Taxonomy/Navigation Scheme) The structure refers to the methods to aggregate the concepts, taxonomy and metadata depicted in the content model into a meaningful presentation for users to interact with. These methods include but are not limited to card sorts, building navigation maps, content schemes and wireframes. User Experience (UI/UX Design) The user experience evaluates, validates and leverages the classification, taxonomy and metadata depicted in the information (content) model. This will enable the UI/UX Designers to render an intuitive user experience for all users of the applications which implement the information architecture.
|What are the different types of content elements that should be modeled? What is the composition (definition & characteristics) of each content element? What are the relationships among the various content elements? Is there a content classification strategy? Has a plan for taxonomy design, creation, usage and maintenance been established? Is there a requirement for tagging content elements and their relationships? Is there a requirement to use user defined tagging? Is there a metadata strategy? Have any metadata methods been identified (i.e., taxonomy, controlled vocabulary, and/or thesaurus, etc.)? Are there any metadata standards available? Have the semantic relationships between content been identified? Is there a mechanism to search related content based on content semantics? Is there a mechanism to analyze related content based on content semantics? Is there a plan to evaluate and validate the content model, taxonomy, and metadata schema?
|Perform the following activities: Content Model creationContent area AnalysisProvide definitions of all ContentBusiness Rules to identify relationships between contentCreate Metadata schema to document content characteristicProvide definitions of all Metadata fields and valuesPerform card sort exercises to further determine classification of content for taxonomy and navigation schemas (Utilized for UI/UX design)Construct Content TaxonomyDevelop standards and guidelines for content assembly and metadataConduct EIA/IA review to evaluate and validate the content model, taxonomy, and metadata schema
|Search This area refers to establishing the standard types of search. This includes but is not limited to keyword, guided, faceted, and federated search. This also includes the parameters in which search results will be presented including but is not limited to topic/subtopic, line of business and product. In addition, search strategy, indexing, accessing multiple sources (federated), and search analytics need to be considered here. Discovery Discovery is focused on identifying relevant information leveraging the information (content) model to facilitate relationships between the various information elements. Analytics This refers to utilizing search analytics (as well as the search logs) for search engine optimization (SEO) and search tuning. User Experience (UI/UX Design – Refined) This involves analyzing the findability of content and how it should be presented as well as incorporating the how the various users will interact with information. Navigation Navigation at this point refers to the ongoing measurement, evaluation and subsequent refinement of the navigation scheme. System Interfaces (if necessary) System Interfaces refers to the decision if the content needs to be made available to one or many systems. Metrics This provides measurements for usage statistics, search statistics and success measures.
|Has the scope of search been determined? Have the standard types of search been evaluated for use (i.e., keyword, faceted, parametric, etc.)? Is there a plan for search analytics (i.e., query analysis, no results found, identification of best bets, etc.)? Is there a requirement to perform search across multiple data sources? Is there a requirement to federate search results from multiple sources? Has the presentation of search results based on content type, topic, subtopic, etc. been determined? Does the mechanism for indexing take frequency of update into consideration? Will the EIA facilitate the discovery of related content? Is there a mechanism to leverage information for business analytics and optimization? Is there a plan to document who the users of the content are and how they are (or will) using it? Has the findability of content been analyzed? Is there a prescriptive navigation scheme and is it being followed? Is there a plan for ongoing measurement and evaluation of navigation? Is there a plan for ongoing measurement and evaluation of usage, navigation, and search?
|Gather the requirements for Search and determine the scope as well as the standard types of search that will be utilized. Develop Search Strategy, include details for search analytics, ongoing measurements and evaluation of usage and content navigation Develop Search Standards and Guidelines
|Content and Classification Stewardship The focus here is on establishing accountability for the accuracy, consistency and timeliness of content, content relationships, metadata and taxonomy within areas of the enterprise and the applications that are being used. IA Management and Maintenance This refers to the specific details on how the enterprise manages and maintains changes to content, content relationships, metadata and taxonomy. This is facilitated through the use of specific process and workflows. Policies and Procedures This refers to establishing and /or conforming to information policies for generation, consumption and access of content (information and knowledge)This also addresses how information is handled – Organization has detailed information policies associated with specific information types (i.e., Guidelines, Manuals, Strategies, Lessons Learned) Enforcement Enforcement of governance pertains to the implementation and execution of the policies and procedures identified in the governance plan. Establishment of a governance board will be the organizational entity to carry out the enforcement of governance, while the applications/tools must be configured to enforce governance of content on a day-to-day basis.
|Is the accountability for the accuracy, consistency, and timeliness of content (information & knowledge) within the enterprise (or specific application) been clearly established? Is the accountability clearly established for the accuracy, timeliness and consistency of metadata?Does any new vocabulary (terms) need to be mapped to an existing/proposed taxonomy? Are there any Organization content (information /knowledge) policies that should be followed? Does the content generation, consumption and/or access conform to Organization and/or government specific regulations?
|Gather the requirements for Content Governance. Develop Content Governance Plan Include the following: Policies for managing/ maintaining Content, Metadata and TaxonomyGovernance enforcementSecurity and Access privilegesGovernance roles and responsibilities
|Content Quality of Service
|Security Security will be focused on the practice of defending content (information/ knowledge) from unauthorized access, use, disclosure, disruption, modification, perusal, inspection, recording or destruction. Adherence to the Organization established information security protocols will be incorporated. Availability Availability is concerned with eliminating or minimizing disruptions from planned system downtime; eliminating or minimizing delays and latency from your content (information/knowledge) and business processes, speeding up the ability of your employees, and customers to act, to buy, to decide, to analyze, to share, to market, to deliver on time, to service, to expand and to profit. Reliability Reliability is concerned with making sure that the content that is accessed is from and/or based on the authoritative or trusted source, reviewed on a regular basis (based on the specific governance policies), modified when needed and archived when it becomes obsolete. Scalability Scalability as it pertains to content is the inherent ability of that content to behave the same no matter what application/tool implements it. Content is also considered scalable when it is flexible enough to be used from an enterprise level as well as a local level without changing its meaning, intent of use and/or function. Usefulness The usefulness of the content will be ensured by tailoring the content to the specific audience (i.e., associate, executive, or customer). Additional factors to ensure that the content will be useful includes leveraging style guides, templates, and plain language and information design (PLAID) to ensure that the content serves a distinct purpose, helpful to its audience and is practical.
|Have the security needs for accessing the content been determined? Has the content been classified for the right security level? Is there a need for an authorization scheme to protect tagging based on user roles? Are availability and reliability requirements for content determined? Has the volume and usage analysis on content been performed? Has the time span for the use of content been analyzed? Has the time for updating the content been scheduled?
|Gather the requirements for the Security, Availability, Reliability, Scalability, and Usefulness of content. Include specific policies within the Security and Access Privileges section of the Governance Plan to reflect quality of service requirements for content (reference style guides, templates, and plain language and information design (PLAID) approaches for content). The EIA (Content Model, Metadata, and Taxonomy) must be designed to reflect scalability across multiple areas and applications within the enterprise.
The EIAC can be used to perform IA activities on a project or can be used to review the design of IA. The EIAC focus more on process, design, and design review, and do not include issues of infrastructure, platform, services, technology, policy, and standards. The goal in designing the IA checklist as part of the architectural review process is to create a set of questions that gets people thinking about and discussing IA in terms of infrastructure, existing technology, services, and platform across the enterprise as well as information generation, delivery, consumption and governance in order to lay the foundation that can then be fully exploited and realized at the user interface level. This broad perspective encourages a collaborative approach to creating an IA solution.
Darwin Information Typing Architecture (DITA)
DITA, which was originally developed by IBM is an open standard that describes the architecture for creating and managing information. DITA framework separates the content from the formatting, this allows for a more streamlined content creation process, and simpler ways of publishing to new technology platforms such as mobile devices. Through the donation by IBM DITA is no owned and maintained by OASIS, where volunteers who are experts in information continue to evolve the framework. As an XML-based, end-to-end architecture for authoring, producing, and delivering technical information, DITA consists of a set of design principles for creating “information-typed” modules at a topic level and for using that content in delivery modes for all types of systems that contain content.
The Problem that DITA Solves
DITA is a framework that allows content to be easily reused or repurposed. By leveraging XML DITA enables you to write and store your content so you can manage it like an asset. XML (eXtensible Markup Language) enables your content to be intelligent, versatile, manageable, and portable. DITA content can be published to (and fully branded) PDF, HTML, RTF, PowerPoint, and mobile while improving consistency, quality, and usability on all content by: streamlining your content creation process; increasing the quality of your content by standardizing it; content reuse, publishing to multiple formats; and makes efficient use of your content saving time and money.
DITA XML organizes your content into topics. However, not all XML does this, but DITA has a core set of topic types that can be used to align content to a specific topic type, this creates highly usable content. XML separates content from format, making it portable and versatile. Words and format are no longer combined and can be managed and updated independently. XML allows the content to be transformed into many other formats. DITA XML provides a structure and flexibility in its architecture that enables content to be delivered in multiple outputs and channels.
What DITA Is Not
- DITA is not a particular tool. Many different tools allow you to author in DITA. In fact, selecting your tool set is part of the process of DITA adoption.
- DITA is not a template, although authors often use templates to make it even faster and easier to write.
- DITA is not a style guide, although authors certainly benefit from one, with or without DITA content.
More on the OASIS DITA Framework can be found here: OASIS Darwin Information Typing Architecture (DITA) TC | OASIS (oasis-open.org)
The outcome of a comprehensive IA implementation is a systematic description of the content of a given product, service, or environment. This type of detail contributes to the understanding and documenting of the complexities of system design to enable intricate solutions to be functional, transparent, and user-friendly. IA also forces clarity upward into the user interface and downward into the system architecture, contributing to simplifying design, development, and implementation. The IA in essence creates a common ground between designers and developers by bridging the gap between the user interface and underlying systems or technologies.
A well-defined IA not only helps you expand the function of your designs, but it can also inform consistent experiences and paths for the evolution of future designs across many variants within a family of products, services, or environments.
IA has become an essential ingredient to ensure a competitive advantage for organizations of all sizes. Organizations continue to search for practical ways to create business value by getting their arms around the content of the enterprise to enable its employees to take action not only to perform their day-to-day activities but also to service the customer. Organizational benefits of IA include unlocking content to let it flow rapidly and easily to people and processes that need it; cost-effectively store, archive, and retrieve the right content, in the right context, at the right time; protect and secure that content to meet compliance requirements, and make it accessible for business insight where and when necessary; and finally mitigating risks inherent in business decision making by providing knowledge assets when and where necessary and in its proper context. To gain valuable knowledge on the principles, practices and implementation of Information Architecture check out my course offered through a partnership between A,J, Rhem & Associates and Knowledge Management Institute.
(see Chapter 4: Knowledge Management in Practice: Knowledge Management in Practice – 1st Edition – Anthony J. Rhem – Ro (routledge.com) for more details on Information Architecture and the EIAC)