A review of multiple meanings.

Articles by Nathaniel Davis.

A formal collection of proposed and existing IA-related terms.

DSIA Lab

Coming Soon.

DSIA

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.

What is Nate up to?

Poor website structure costs more than we think.

Every digital user interface has structure. When site structure is insufficiently documented, it affects everything from team collaboration and site user experience to business outcomes. 

This upcoming insight explores a practical method for calculating the soft and hard costs of UI structural debt .

IA viewpoint: Nathaniel davis
December 7, 2o20

Facilitating conceptual clarity

Based on the my latest DSIA definition, I describe information architecture as a field of study “that explores how to facilitate shared understanding and alignment with conceptual clarity.” In context to the most recent trends, it’s the thinking you do before design thinking.

Information architecture (IA) was the 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 over the last two decades 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.

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 reintroducing IA practitioners into their process. Information architecture practitioners who specialize in alignment and sensemaking offer a unique lens for framing a wide range of strategic and design assumptions.


Check back next month for my latest thought on information architecture and other related topics.

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.

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.

Uday Gajendar argues how the professional future of design practice will require teams to go “meta.” 

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 and a bit of clarity 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.

Industry-based Proposals and Recommendations Contributed by Nathaniel Davis

Information architecture is an area of study that does not have an official home. You can find information architecture discussed in both academic and professional forums. Nathaniel periodically contributes 

Disambiguation of Information Architecture

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Signatures of Information Overload

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Architecture Risk Principle

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Information Architecture Common Set

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UX Design Practice Verticals

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Project Accountability Model

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Boolean IA Maturity Assessment

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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.

Consensus

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?


Synthesis

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?


Coherence

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 the design execution or work in collaboration with an architecture lead.

Benefits: Rational framing of intent | Actionable design constraints

Flag: Does your team have more questions than answers?


Continuity

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 promote 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

Published: 12/2/2020
Edited: 1/2/2021 – Made significant rewrites to align with ongoing research.

DSIA-based Articles

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.

Theory—as a synthesis of what, how, and why we do what we do—can provide the frameworks to reinforce IA discipline. This article offers an example.

BY NATHANIEL DAVIS

Disambiguation refers to the removal of ambiguity by making something clear. This working document tackles the meaning behind multiple uses of the information architecture term and expresses a breadth of topics that are of interest to academics, researchers, and practitioners.

Read more about information architecture >>

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. 

More about this video >>

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.

“Widely used image-recognition data set is teaching computer-vision software to classify images using racist and misogynistic slurs.”

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.

Illustrations & Posters

By Nathaniel Davis
Previously published or presented at industry conferences.