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Classification and Taxonomy

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Title: Classification and Taxonomy


1
Classification and Taxonomy
Greg Argo
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.
  • Its not just handy, its 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
Classifications, Taxonomies, and Ontologies -
Classifications
  • 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 dont change significantly after their
    creation
  • Generally applicable to specific domains

9
Classifications, Taxonomies, and Ontologies -
Taxonomies
  • 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

12
Classifications, Taxonomies, and Ontologies -
Ontologies
  • 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

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 dont 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
  • IAs 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 users immediate awareness
  • Supplement information retrieval during keyword
    searching
  • IAs create controlled vocabularies and synonym
    rings which they use to maintain consistency
    across applications and departments
  • By analyzing emerging content and search logs,
    IAs 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 users search can be expanded to increase
    recall by mapping the search term to its variants
  • Or a users search can be narrowed to increase
    precision by mapping a users 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 users
    conscious awareness
  • Allow the user to guide the seeking process
    themselves by browsing instead of searching

32
Navigational taxonomies contd
  • 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 contd
  • 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/a
    rticle_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.pdf
  • Goodall, G. (2003). Business taxonomies and
    bibliographic objective Facetation. Retrieved
    October 25, 2004 from http//www.deregulo.com/fac
    etation/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 contd
  • Shank, P. (2004). Get organized or get lost.
    OnlineLearningMag. Retrieved October 25, 2004
    from http//www.onlinelearningmag.com/onlinelearn
    ing/magazine/article_display.jsp?vnu_content_id11
    08349
  • 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/c
    ib2003.pdf
  • Zerubavel, E. (1991). The fine line Making
    distinctions in everyday life. New York
    Free Press.
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