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Information Architecture Basics

Information architecture (IA) focuses on organizing, structuring, and labeling content in an effective and sustainable way.  The goal is to help users find information and complete tasks.  To do this, you need to understand how the pieces fit together to create the larger picture, how items relate to each other within the system.

Why a Well Thought Out IA Matters

According to Peter Morville Site exit disclaimer, the purpose of your IA is to help users understand where they are, what they’ve found, what’s around, and what to expect.  As a result, your IA informs the content strategy through identifying word choice as well as informing user interface design and interaction design through playing a role in the wireframing and prototyping processes.

What You Need to Know

To be successful, you need a diverse understanding of industry standards for creating, storing, accessing and presenting information. Lou Rosenfeld and Peter Morville in their book, Information Architecture for the World Wide Web, note that the main components of IA:

  • Organization Schemes and Structures: How you categorize and structure information
  • Labeling Systems: How you represent information
  • Navigation Systems: How users browse or move through information
  • Search Systems: How users look for information

Lou Rosenfeld and Peter Morville’s venn diagram showing the Information Ecology: context, content, usersIn order to create these systems of information, you need to understand the interdependent nature of users, content, and context.  Rosenfeld and Morville referred to this as the “information ecology” and visualized it as a venn diagram.  Each circle refers to:

  • Context: business goals, funding, politics, culture, technology, resources, constraints
  • Content: content objectives, document and data types, volume, existing structure, governance and ownership
  • Users: audience, tasks, needs, information-seeking behavior, experience

IA Sub-Specialties

Since the field of IA is complex and when dealing with large information systems the task becomes more massive, sometimes experts choose a specialized niche within the discipline.  Some examples of IA sub-specialties include focusing on search schemas, metadata, taxonomy, etc.

References