This site contains selected research, publications, and perspectives on information architecture by Nathaniel Davis. It also includes resources from other practitioners. Due to ongoing research, content on this site is subject to change.
Illustrations & Posters
Sustaining conceptual clarity
Based on the my latest DSIA-based definition, I describe information architecture as a field of study that explores how to sustain shared understanding and alignment with conceptual clarity.
Information architecture (IA) is a term used to described one of the first Web professions in the late 1990s. However, the widespread adoption of user experience design and agile methods in the first two decades of the 21st century downplayed information architecture’s importance to user interface strategy and structure.
Today, the information architecture lens is narrowly associated with solving navigation, labeling, and content organization. Many teams fail to document the user interface’s essential conceptual foundations that inform design strategy. As a result, UI design teams often find themselves lacking much-needed clarity.
Some teams look to design thinking methods to fill this gap of confusion. But design thinking is a practice of generating solutions and as a consequence also requires a set of sound assumptions, constraints, and questions as inputs upon which teams can iterate. Fortunately, a skilled IA practitioner can close this gap for struggling teams.
Information architecture practitioners who specialize in alignment and sensemaking offer a unique lens for framing a wide range of strategic and design assumptions. Once inserted, an IA practitioner can help a team build consensus, synthesize insights, bring coherence to problem framing, and add greater continuity to conceptual foundations.
If digital teams want to create better solutions, they should consider introducing IA practitioners into their process.
Nate is an independent researcher, consultant and advocate for advancing information architecture as an area of study and practice. Nate is a former co-chair of the IA Summit and co-founded IAC (IA Summit spinoff from ASIS&T). He writes the information architecture column for UXmatters, is past contributor to the Bulletin for the Association of Information Science & Technology, and blogs on methodbrain.com.
Information Architecture: Beyond Navigation, Labels, and Organization
BY NATHANIEL DAVIS
It’s easy to misunderstand the aims of information architecture and its practitioners. This talk samples the brief history of IA framing and posits information architecture as an area of study. It also suggests how IA thinking brings value to strategy, design process and other forms of problem solving.
An Information Architecture Maturity Model
BY NATHANIEL DAVIS
In this World IA Day video, Nathaniel Davis discusses the general function of information architecture when creating user interfaces. It differentiates information architecture from design activity and introduces an IA maturity model. The presentation posits a value proposition of information architecture, four essential IA modeling activities, and six pillars of UI structure.
By Nathaniel Davis
DSIA articles are based on foundational research.
Information overload is a costly drain on productivity that stems from vast amounts of information and failure to filter information as presented. Information architects (IAs) are in a position to address the challenge.
“While IA practice may be known mostly as an art, its potential science and future internal theory lie in how we understand, strategize and find solutions for site structure.”
The one thing we know about information overload on the Web is that we don’t know enough. This article reviews six IO signatures to consider on your next project.
When to consider an IA practitioner
IA practitioners facilitate shared understanding and alignment with conceptual clarity in the following areas.
Note: The following is a draft and subject to change.
The language and conceptual assertions that teams use to describe a project’s scope can present a significant barrier to effective team communication. It’s important to have someone on the team to track and validate what things mean and how they are described.
A skilled information architect breaks down ambiguity at the beginning of and throughout a project to promote conceptual alignment and clear language. This greatly improves internal agreement and team communication.
Benefits: Contextual foundation | Stable vocabulary
Flag: Does your project team struggle with aligning on concepts and language?
When teams target a domain of behavior, they should establish a grounding hypothesis, theory or general understanding about the domain. For example, to understand a fallen apple, one may need to recognize the parts that give structure to the apple, but also how the apple falls from a tree; in a field; under certain weather conditions; within a region, etc.
Information architects tend to observe factors that make specific behaviors sustainable. This is a valuable perspective because it helps to identify critical systemic constraints, patterns, and assumptions that are often overlooked.
Benefits: Behavioral foundations | Systemic perspective
Flag: Does your team struggles to deduce actionable insights and patterns from research activities?
Skilled team contributors from design, engineering, and production disciplines will naturally ask questions that address gaps for a given objective. If a team struggles to create a solution for a project but has more questions than answers, the team may be struggling to coherently frame the intent and constraints of the project.
Seasoned IA practitioners are skilled at facilitating a summary of architectural intent and a governing framework of constraints to support it. An IA practitioner is happy to directly advise on design execution or work in collaboration with a lead design architect.
Benefits: Rational framing of intent | Actionable design constraints
Flag: Does your team have more questions than answers?
Systems have a mechanical nature, where repeated patterns of interconnected behaviors contribute to the overall structure. Exposing these patterns and their functional properties enable the most sustainable solution within a problem space. The desired outcome from this form of investigation generally promotes structural integrity and predictability.
IA practitioners with a more technical disposition study conceptual modeling/engineering to manage systemic relations across many forms, including but limited to: concepts, human behavior, content, interaction, user interfaces, and data.
Benefits: Sustainability | Structure
Flag: Is your team unable to trace and evaluate how a solution is structured to satisfy a project’s architectural intent?
© 2020. Nathaniel Davis
Edited: 1/2/2021 – Made significant rewrites to align with ongoing research.
Eyes On the Field of IA
Peter Morville reconsiders his previous framing of information architecture and provokes a conversation about practicing IA beyond business and the Web to change minds through linguistic and categorical alignment.
The “structural design of shared information environments” requires engineering. This article introduces a professional path for IA practitioners with a passion for modeling.
Jason Hobbs reflects on the void left by the closing of the IA Institute. The institute may be gone but the field must continue to build discipline to achieve its true relevance to society.
Yesenia introduces a framework that breaks down the understanding of user problems into modular, interconnected elements — similar to how teams break down the UI into modular elements.
Abby Covert’s 2020 keynote explores her experience with persistent problems and the soft skills practitioners will need to insert IA thinking into their organizations.
From practical to tactical. This articles explores ways of inserting IA thinking in a culture that’s focused on moving product out the door. It also reviews some of the fields challenges,
Tom and his LinkedIn friends wonder whatever happened to the information architecture discipline and whose going to take the reigns to keep it relevant? Someone has to do it, right?
Full collection coming soon.
Related Disciplines and Sciences
Recent articles related to the field of information architecture.
AI practitioners need to build partnerships with community members, stakeholders, and experts to help them better understand the world they’re interacting with and the implications of making mistakes.
This three part article provides a comparison of the strengths and limitations of Knowledge Graphs versus Property Graphs and guidance on their respective capabilities.
A review of ontologies and knowledge graphs, describing how they’re different and how they work together to organize data and information.
Additional entries coming soon.
“Why Computing Belongs Within the Social Sciences”
BY RANDY CONNOLLY
Because computing as a discipline is becoming progressively more entangled within the human and social lifeworld, computing as an academic discipline must move away from engineering-inspired curricular models and integrate the analytic lenses supplied by social science theories and methodologies.