Post on 23-Feb-2016
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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.
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
“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?
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
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
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
Classifications, Taxonomies, and Classifications, Taxonomies, and Ontologies -Ontologies - ClassificationsClassifications 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
Classifications, Taxonomies, and Classifications, Taxonomies, and Ontologies -Ontologies - TaxonomiesTaxonomies
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
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
Taxonomic Hieracrhy
Clothes Fasteners
Belts Zippers Buttons
Classifications, Taxonomies, and Classifications, Taxonomies, and Ontologies -Ontologies - OntologiesOntologies 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 Can include many sub-class taxonomies
connected togetherconnected together
Classifications, Taxonomies, and Classifications, Taxonomies, and OntologiesOntologies 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
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
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
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
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
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
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)
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
ReferencesAdams, K. (2000). Immersed in structure: the meaning and function of
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Stefik, M. (1995). Introduction to knowledge systems. San Francisco: Morgan Kaufmann.
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