A Brief (and Practical) Introduction to Information Architecture

A Brief (and Practical) Introduction to Information Architecture Usability and Accessibility for the Web International Seminar Monterrey, Nuevo Leon July 26, 2007 Louis Rosenfeld www.louisrosenfeld.com

My path and biases

The “Polar Bear” book

Agenda: emphasis on practical

Introduction to information architecture

How to think like an information architect

Some practical advice on methods and design approaches

Where the field is going

Questions? Please write them down

Introduction: IA in six slides

A definition and a diagram

Definition: the art and science of structuring, organizing and labeling information to help people find and manage information

Balances characteristics and needs of users, content and context

Where we’re from/what we do: User-orientation

Usability testing

Contextual inquiry

Card sorting

Persona and scenario development

Human Computer Interaction

Anthropology

Marketing

Sociology

Methods Disciplines

Where we’re from/what we do: Content-orientation

Content inventory and analysis

Content modeling

Metadata development

Server and search analytics

Librarianship

Technical communication

Graphic design

Journalism

Computer science

Methods Disciplines

Where we’re from/what we do: Context-orientation

Stakeholder interviews

Project planning

Specifications development

Management

Systems engineering

Organizational psychology

Methods Disciplines

What we do: A series of balancing acts IAs improve knowledge of the former; neutral balancers Customers vs. business Technology agnostics who go beyond tech requirements Build vs. buy IAs integrate both as part of broader info ecology Formal vs. emergent IAs develop balanced workflows and processes Centralization vs. autonomy IAs stronger in the latter, though data is ascendant Structured vs. semi-structured

Information architecture’s single rule

Pareto Principle (“the 80/20 rule”)

Information architecture is all about prioritization: determine which 20% is most important (information needs, content, design)

There are no other rules, just guidelines

Before we continue: A question

Aren’t usability and information architecture really just the same thing?

CiteSeer: Strong on findability, weak on usability

UseIt: Strong on usability, weak on findability

IA for novices and veterans: Start with Two Big Questions

My questions for you

Who are your site’s major audiences?

What are each audience’s primary information needs (and how well are you addressing them)?

Are you confident in your answers?

Q1: Who are your site’s major audiences?

Audience definition is surprisingly difficult

Too little data… or too much

Who/what/where/why/when/how questions

Political challenges

Defining audience by silo leads to stakeholder infighting

Goal: err toward apolitical segmenting that cuts across silos; examples:

Job functions (admin, clerical, research, mgmt)

Demographics

Q2: What are their major information needs? Photos: http://www.flickr.com/photos/alexin/

Information needs are common tasks and topics

Examples

How do I obtain a driver’s license?

Are there scholarships available for my 18-year old son?

Who are my elected representatives?

Can the state government help me find investors?

Uncovering information needs: Ask people who would know

Webmasters and the “hate mail” they receive

Switchboard operators and their FAQs (Frequently Asked Questions)

Subject Matter Experts and the people who bother them

Who else?

Avoid: focus groups

Uncovering information needs: Analyze behavioral data

Switchboard logs

Server logs (Web Analytics)

Search logs (Search Analytics)

Information and call center logs

Where else?

Grouping log data can help you (re)define audience segments

Big Answers for Big Questions

The end of redesigns

Redesigns are

Expensive and wasteful

Cosmetic

User-hostile

Pointless

Instead, institute a process

Ask and answer these Big Questions on a regular basis

Allows all aspects of IA and UX to become procedural and institutional

Sample Method: Search Analytics

Anatomy of a search log

Google Search Appliance; critical elements in bold: IP address , time/date stamp , query , and # of results:

XXX.XXX.X.104 - - [ 10/Jul/2006:10:25:46 -0800] "GET /search?access=p&entqr=0&output=xml_no_dtd&sort=date%3AD%3AL%3Ad1&ud=1&site=AllSites&ie=UTF-8&client=www&oe=UTF-8&proxystylesheet=www&q= lincense+plate &ip=XXX.XXX.X.104 HTTP/1.1" 200 971 0 0.02

XXX.XXX.X.104 - - [ 10/Jul/2006:10:25:48 -0800] "GET /search?access=p&entqr=0&output=xml_no_dtd&sort=date%3AD%3AL%3Ad1&ie=UTF-8&client=www&q= license+plate &ud=1&site=AllSites&spell=1&oe=UTF-8&proxystylesheet=www&ip=XXX.XXX.X.104 HTTP/1.1" 200 8283 146 0.16

XXX.XXX.XX.130 - - [ 10/Jul/2006:10:24:38 -0800] "GET /search?access=p&entqr=0&output=xml_no_dtd&sort=date%3AD%3AL%3Ad1&ud=1&site=AllSites&ie=UTF-8&client=www&oe=UTF-8&proxystylesheet=www&q= regional+transportation+governance+commission &ip=XXX.XXX.X.130 HTTP/1.1" 200 9718 62 0.17

Full legend and more examples here: http://www.rosenfeldmedia.com/books/searchanalytics/blog/log_sample_google_appliance/

The Pareto Principle in action Sorting queries by frequency results in a Zipf Distribution Can we improve performance for the most popular queries?

What users want and when: Sorting and clustering queries

Diagnostics from search analytics: What can you fix or improve?

User research

Interface design: search entry interface, search results

Retrieval algorithm modification

Navigation design

Metadata development

Content development

Best Bet search results: Big answers for Big Questions

Manually-assigned recommended links

Ensure useful results for top search queries

Useful resources for each popular query are manually determined (guided by documented logic)

Useful resources manually linked to popular queries; automatically displayed in result page

Best Bets example: NCI

Best Bets also improve navigation

Comprehensive A-Z site index automatically generated from best bet keywords

Guides: Bigger answers to Big Questions

Guides are single pages that contain

A selective set (5-10) of important links related to a Big Question

Narrative text that explains the topic and what’s available to help with that topic

Generally linked from the main page, but also used in more specific contexts

Subsite main pages

Search results

Vanguard links to guides on main page

Vanguard’s guide to its tax information

Guides are painless and efficient

Low impact on IT (single HTML page)

Cut across departmental silos

Gap fillers; complement comprehensive methods of navigation and search

Can be timely (e.g., news-oriented guides, seasonal guides)

Minimize political headaches by creating new real estate

Can grow into fuller subsites

Sample Design Approach: Contextual Navigation

Contextual navigation: Focusing on where users are

Contextual navigation supports users deep in site

Where am I?

Where can I go from here?

Critical in a Web 2.0 world

Top layers of information systems are increasingly bypassed

Search engines

Syndication (RSS, Atom)

Banner advertising

Deep content becomes starting point

A common content model

Contextual navigation is powered by content models

“Data modeling for semi-structured content”

Content modeling process helps narrow down both content and metadata choices

Content models consist of

Content objects

Links between objects

Metadata

Use sparingly to support high-value contextual navigation

Hewlett-Packard content model for product information

HP’s content model for products includes overview, supplies, support, drivers…

Content model is exposed as part of search results to enhance navigation

BBC content model for music artist descriptions album reviews album pages artist bios discography concert calendar TV listings

Content modeling use metadata to connect content objects artist description artist description artist description artist bio, discography, concert calendar, TV listing album review, artist description album page album review, discography, artist … link to other Content Objects… Artist Name , Channel, Date, Time… Artist Name , Tour, Venue, Date, Time… Artist Name , Individual Artist Name… Artist Name , Desc Author, Desc Date… Artist Name , Album Name , Release Date… Album Name , Artist Name , Review Author, Source, Pub Date… Album Name , Artist Name , Label, Release Date… … by leveraging common Metadata Attributes TV listing concert calendar artist bio artist description discography album review album page Content Objects…

At last: A little bit of inspiration

The past and future of IA… in logos time External IAs Internal IAs Senior information architect Director of User Experience Chief Experience Officer Chief Information Officer … CEO?

What I’ve covered