2. Brief origins of the organization of information Large amounts of information became difficult to store and retrieve. Although the classes used vary wildly across cultures, grouping based on the class level is nearly universal. Organizational structures provide the context in which humans transform information into knowledge. It’s not just handy, it’s essential.

3. Humans classify “with a pronouncedly mental scalpel that helps us carve discrete mental slices out of reality” because “reality is not made up of insular chunks unambiguously separated from one another by sharp divides, but, rather, of vague, blurred-edge essences that often spill over into one another.” - Eviatar Zerubavel (1991)from The fine line: Making distinctions in everyday life

4. “Cognitive scientists have noticed that much of our mental commerce with an environment deals with classes of things rather than with unique events and objects.” - Mark Stefik (1995) from Introduction to knowledge systems For example, the people seen below could probably all be placed in both the class “Cognitive Scientists” and the class “Nerds”. Can you think of other possible classes? Possible relationships? Clinical vs. academic cognitive scientists? Beards and nerds?

5. Why consider classification and taxonomy together? Both are methods for grouping objects or ideas sharing useful, although sometimes superficial, similarities Both group to make retrieval easier Both are very basic and pervasive elements of information architecture It is often difficult to tell them apart It is often unnecessary to tell them apart

6. Why tell them apart then? To become knowledgeable about the different limitations and possibilities in their interaction Differential demand on and payoff for users It is important to understand the specific qualities by which each can achieve organizational objectives

7. Specific qualities presented as keywords and key-dichotomies Organization Retrieval Controlled vocabulary/thesauri Ambiguous vs. Exact Searching vs. Browsing Content-based vs. User-based Descriptive vs. Navigational Precision vs. Recall Structures vs. Applications Concise vs. Broad

8. Relationships expressed are not essential, but are based on arbitrary, external attributes (color, genre, format, geography, subject, alphabetical order) Created broadly from the top-down, based on conceptual frameworks Created by subject experts Usually don’t change significantly after their creation Generally applicable to specific domains

9. Relationships expressed are usually essential, based on internal properties of the related pieces of information Created concisely from the bottom-up from actual content Created by multidisciplinary teams Are process-oriented, and so are updated frequently Oftentimes can be used and reused in different situations and environments Relationships commonly represented hierarchically Can be include many classifications connected together

10. Example of internal properties of taxonomic relationship All zippers are clothes fasteners Not all clothes fasteners are zippers Because of the essential nature of their relationship, zippers is a sub-class of clothes fasteners, and clothes fasteners is a superordinate class of zippers

11. Taxonomic Hieracrhy Clothes Fasteners BeltsZippersButtons

12. Like taxonomies, relationships expressed are also essential Scope is more overarching due to inclusion of supplemental information Descriptions and definitions of concepts and their corresponding relationships Can include many sub-class taxonomies connected together Can include many sub-class taxonomies connected together

13. Classifications, Taxonomies, and Ontologies Classifications guide users to a body of information Taxonomies guide users through a body of information Ontologies guide users in becoming proficient in the retrieval of and understanding of a particular body of information

14. Classification To classify something is to identify it as a member of a known class On the Web, information architects organize classification schemes into either exact or ambiguous schemes Classification problems begin with data and identify predetermined classes as solutions

15. Exact classification schemes Items are categorized mutually exclusively Useful to users who know exactly what they are looking for By definition, are easier to create and maintain than ambiguous schemes Alphabetical, chronological, geographical

16. Alphabetical schemes Directories and lists User must have a good idea of what they are searching for and be able to spell it On the Web, usually utilized deeper in the scheme inside of sub-sites

17. Chronological schemes Have an intuitive advantage for users because they are organized in the same linear scheme in which humans experience the dimension of time Yearbooks, historical sites, and news headline sites Ebay offers results organized by a few different types of chronologies

18. Geographical schemes Have intuitive appeal to rich spatial faculties and needs of users in their experience of reality Geographical divisions coincide with governing bodies which restrict and encourage behaviors through law and language Requires knowledge of geographical divisions and map reading on the part of the user

19. Ambiguous classification schemes Items are categorized into intellectually meaningful groups Useful to users who don’t know quite what information they are searching for Facilitate iterative, serendipitous learning Audience-based, Subject-based, Task-based Each should be based on scheme specific research and development processes (e.g. user and task analyses)

20. Audience-based classification schemes Makes sense if the informational domain caters to clearly delineated audiences Homepage becomes a filter that leads to sub-sites organized some other scheme Suggests customization/personalization Recommendations are sometimes powerful, sometimes failures

21. IA research for audience-based classification schemes Map services and applications to their appropriate group Discern what types of technology-use are associated with specific populations Find points of overlap between audience categories User research sessions, usage statistics, search log analysis, focus groups, critical incident reports

22. Subject-based classification schemes Most immediately recognized are the library classification schemes (DDC, LC) When used in IA, they generally work best when hybridized with other types of schemes Are challenging to implement because different words, symbols, and idioms mean different things to different people Breadth of subjects included should be decided early on because these parameters will affect much of the rest of the IA and content work for the Web site

23. IA research for subject-based classification schemes Solicit development team to write down each content item that will be part of site IA’s perform card sorting exercise to establish initial subject categories Take it to the user Further card sorting Survey with questions about navigation Continually refine

24. Task-based classification schemes Useful for action and transaction related Web sites Rarely drive a Web site on their own, but are typically embedded deeper as part of a hybrid scheme Desire of businesses to remove labor costs will likely increase their ubiquity

25. IA research for task-based classification schemes The field of usability arose from the need to research the success and value of tools and their applications Traditional usability tests are a good fit Analyses of video-taped sessions, navigation logs, heuristic reviews, surveys, critical incident reports

26. Taxonomies Information architects have two major types to utilize: descriptive and navigational They contrast well and each excels for different organizational and user needs Central ideas include creating hierarchies, controlled vocabularies, and variant/preferred term and synonym relationships Build on classifications by supporting applications and many different types of content, including images, email, search engines, process funnels, and site registration

27. Descriptive taxonomies Operate outside of a user’s immediate awareness Supplement information retrieval during keyword searching IA’s create controlled vocabularies and synonym rings which they use to maintain consistency across applications and departments By analyzing emerging content and search logs, IA’s maintain currency and map alternative terminology used by searchers back to the preferred form

28. Controlled vocabularies in descriptive taxonomies Done by attaching tags to content with metadata derived from controlled vocabulary usage logs The resulting thesaurus with related and variant terms makes a descriptive taxonomy more robust

29. Using the controlled vocabulary to increase recall or precision A user’s search can be expanded to increase recall by mapping the search term to its variants Or a user’s search can be narrowed to increase precision by mapping a user’s term to the preferred term in the controlled vocabulary

30. More about descriptive taxonomies Created from the bottom-up Are called descriptive because they are derived directly from the content that is being used Data management vocabularies allow workers in disparate domains to report information using the same terminology Makes it easier for management to mine information from this data in the future

31. Navigational taxonomies Have a lot of overlap with exact and ambiguous classification schemes In contrast to descriptive taxonomies, navigational taxonomies command the user’s conscious awareness Allow the user to guide the seeking process themselves by browsing instead of searching

32. Navigational taxonomies cont’d Created from the top-down based on mental models of users Hierarchical structures visually imply sequences of events and relationships These relationships provide context similar to words in a sentence Works best when users are unsure of what they are seeking

33. Breadth vs. Depth Breadth is how many categories are contained in each level Depth refers to how many levels are contained in the hierarchy Too broad and shallow causes user too many choices and not enough content Too narrow and deep causes user to click more than they will stand for It is best to err on the side of broad and shallow to allow for add-ons and to avoid restructuring the home page

34. Summary Distinction is more pronounced in theory than in practice because both are essentially controlled vocabularies structured by logical relationships Generally, as one moves from classifications to taxonomies to ontologies, the structures, relationships, and supplemental descriptions become more complex

35. Summary cont’d Since humans seem to perform all three of these innately, it matters less what they are called than how their elements can be tailored to specific scenarios to improve retrieval of information, consistency of communication, and creation of knowledge

36. References Adams, K. (2000). Immersed in structure: the meaning and function of taxonomies.Internetworking, 3.2. Retrieved October 25, 2004 from: http://www.internettg.org/newsletter/aug00/article_structure.html http://www.internettg.org/newsletter/aug00/article_structure.html Brown, J., & Duguid, P. (2002). The social life of information. Boston: Harvard Business School Press. Conway, S., & Sligar, C. (2002). Unlocking knowledge assets. Redmond, Washington: Microsoft Press. Edols, L. (2001).Taxonomies are what? FreePint, 97, 9-11. Retrieved October 25, 2004 from the FreePint Web site: http://www.freepint.com/issues/041001.pdfhttp://www.freepint.com/issues/041001.pdf Goodall, G. (2003). Business taxonomies and bibliographic objective: Facetation. Retrieved October 25, 2004 from: http://www.deregulo.com/facetation/pdfs/businessTaxomies_goodall.pdf http://www.deregulo.com/facetation/pdfs/businessTaxomies_goodall.pdf Nielsen, J. (2001). Designing web usability. Indianapolis, IA: New Riders Publishing. Rosenfeld, L., & Morville, P. (2002). Information architecture for the World Wide Web.Cambridge ; Sebastopol, CA: O'Reilly.

37. References cont’d Shank, P. (2004). Get organized or get lost. OnlineLearningMag. Retrieved October 25, 2004 from: http://www.onlinelearningmag.com/onlinelearning/magazine/article_display.jsp? vnu_content_id=1108349 http://www.onlinelearningmag.com/onlinelearning/magazine/article_display.jsp? vnu_content_id=1108349 Stefik, M. (1995). Introduction to knowledge systems. San Francisco: Morgan Kaufmann. Svenonius, E. (2001). The intellectual foundation of information organization. Cambridge, MA: The MIT Press. Taylor, Arlene G. (1999). The organization of information. Englewood, CO: Libraries Unlimited. van Duyne, D. K., Landay, J. A., & Hong, J. I. (2003). The design of sites. Cambridge: Addison-Wesley. van Rees, R. (2003). Clarity in the usage of the terms ontology, taxonomy and classification. CIB73 2003 Conference Paper. Retrieved October 25, 2004 from http://vanrees.org/research/papers/cib2003.pdf http://vanrees.org/research/papers/cib2003.pdf Zerubavel, E. (1991). The fine line: Making distinctions in everyday life. New York: FreePress.