The document serves as a practical introduction to information architecture (IA), emphasizing its role in usability and accessibility on the web. It discusses the methodologies and disciplines within IA, including user orientation, content orientation, and context orientation, as well as how to identify audiences and their information needs. Furthermore, it highlights the importance of regular assessment of user information needs and provides insights on improving website navigation and search functionalities.

1. 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

2. My path and biases

3. The “Polar Bear” book

4. 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

5. Introduction: IA in six slides

6. 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

7. 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

8. 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

9. Where we’re from/what we do: Context-orientation Stakeholder interviews Project planning Specifications development Management Systems engineering Organizational psychology Methods Disciplines

10. 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

11. 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

12. Before we continue: A question Aren’t usability and information architecture really just the same thing?

13. CiteSeer: Strong on findability, weak on usability

14. UseIt: Strong on usability, weak on findability

15. IA for novices and veterans: Start with Two Big Questions

16. 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?

17. Q1: Who are your site’s major audiences?

18. 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

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

20. 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?

21. 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

22. 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

23. Big Answers for Big Questions

24. 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

25. Sample Method: Search Analytics

26. 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/

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

28. What users want and when: Sorting and clustering queries

29. 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

30. 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

31. Best Bets example: NCI

32. Best Bets also improve navigation Comprehensive A-Z site index automatically generated from best bet keywords

33. 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

34. Vanguard links to guides on main page

35. Vanguard’s guide to its tax information

36. 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

37. Sample Design Approach: Contextual Navigation

38. 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

39. A common content model

40. 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

41. 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

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

43. 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…

44. At last: A little bit of inspiration

45. 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?

46. What I’ve covered Introduction to information architecture How to think like an information architect Some practical advice on methods and design approaches Where the field is going Now, about those questions…

47. How to reach me Louis Rosenfeld 705 Carroll Street, #2L Brooklyn, NY 11215 USA +1.718.306.9396 voice +1.734.661.1655 fax [email_address] www.louisrosenfeld.com www.rosenfeldmedia.com