Step 1:
Complete the following table of concepts by identifying a definition for
each concept:
Aboutness
The topic dimension of a resource
Exhaustivity
The level of detail included in
index/description
Specificity
The level of detail about a specific
concept/topic
Conceptual analysis
Determining the ‘aboutness’ of a resource
Translation
The process of abstracting and mapping
concepts to a vocabulary
Controlled
A structured set of terms that define a
Vocabulary
concept within specified boundaries
(synonyms, homographs (disambiguation),
linking
Question 1. What questions does Lancaster recommend asking about a
resource during the indexing process?
What is the book about, what audience is it for, has it been added to our collection?
Question 2. What role does Lancaster indicate that the “community” plays in
helping create good indexes?
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A community focus is important in indexing , understanding community needs and
as it shifts over time is important!
Question 3. What are the three types of controlled vocabularies that
Lancaster mentions?
Bibliographic classification schemes, lists of subject headings, thesauri
Question 4. How are subject heading and thesauri lists related? How are
they different?
Different: SH lists are not necessarily hierarchical or complete, thesauri show
relationships between terms
Similar: they are all lists of the labels that we apply (p17), the application of them is
“conceptually identical processes”
Table 1: Map of classification types
Classification type
Hierarchies
Trees
Paradigms
Faceted
Classifications
Folksonomies (not
in article)
Common uses
Limitations
Examples
Question 5. Where would Kwasnik place the LC Classification?
I suppose Kwasnik would call LC hierarchical although her concept of hierarchy is
different from Chowdhury’s
Table 2 Features of Classification systems
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Classification type
System feature
Subjects and classes are listed in a pre-defined
Enumerative
notation
System is - “Strictly hierarchical”, “pre-defined”
Enumerative
Rules for classification have no pre-defined
Faceted
classes but define an approach to classification
Classification process focuses on identifying
Faceted
unrelated aspects of a document (personality,
matter, energy, space, time)
Mixes pre-defined hierarchy and refining facet
Analytico-synthetic
features
Uses classification schedules to build a
Analytico-synthetic
classification number
Question 6. What is your top level heading?
a. G3. Probability and Statistics
Question 7. What is the full classification?
a. G3. Probability and Statistics Statistical Computing
Question 8. What Headings did you select?
1. Heading 1: Statistical hypothesis testing--Computer
programs
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2. Heading 2: Mathematical statistics--Computer
programs
3. Heading 3: Python (Computer program language)
4. Heading 4: Computer Science Texts
Question 9. What is the Authorized heading for our author? How could you
tell?
a.
Downey, Allen
b. Because the authority record has references to other books
he wrote (we expect that there are not multiple people called
Allen Downey writing in Computer Science right now)
Question 10.
What are some potential classification numbers for our
resource?
5. Potential heading 1: QA 276.45
6. Potential heading 2: QA 276.4
7. Potential heading 3: QA 76.73
Question 11.
What is the best classification Number for this resource?
a. QA 276.45 .P9
Question 12.
What is your final Call number (including cutter):
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a. QA 276.45 .P9 D68 2011
Question 13.
What call number did you create for this record?
QA 276.45 .P9 D68 2011
QA = Mathematics
276 = Mathematical statistics
.45 Data processing—Special programs or languages, A-Z
.P9 = Python (using the cutter handout to get the 9)
D68 = Downey
2011
Question 14.
What subject headings did you assign?
1. Heading 1: Statistical hypothesis testing--Computer
programs
2. Heading 2: Mathematical statistics--Computer
programs
3. Heading 3: Python (Computer program language)
4. Heading 4: Computer Science Texts
Question 15.
What Dublin Core vocabulary scheme did you select for
the library of congress classification?
Dcterms:LCSH
Table 3 Tags for Think Stats
http://www.libraryth
2012-0205 21st century 3100SS 3300WK analysis analytics computer
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ing.com
programming computer
computingdata data analysis data
science development digital ebook etext mathematics pr
science computers
ogramming python Python (Computer program language) selfteaching software
statistics technology
http://goodreads.com
1 person 1 person
to-read-eventually
1 person
textbook
1 person
my-books
1 person
read_in_2012
1 person
z
1 person
partial
1 person
maths
1 person
informatics
1 person
2012
1 person
computer-science
1 person
software
1 person
digital
1 person
wishlist
1 person
ebook
1 person
it
1 person
later
1 person
data-mining
1 person
safari-books
1 person
ml-ai
1 person
statistical-analysis
1 person
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technical
1 person
data-processing
1 person
computers-technical
1 person
science
1 person
nook
1 person
math
1 person
math-stats
1 person
computer
1 person
http://www.shelfari.c1.
2.
om/
digital,
development,
3.
4.
programming,
5.
statistics,
6.
technology
software",
Also had subjects
Books › Computers & Internet › Computer Science › Modeling & Simulation
Question 16.
What were the most representative tags from the
folksonomies? How did their content compare to the other classification
systems?
Personal opinion
Question 17.
Rank each classification system with regards to how
specific the classification is. Re-rank the systems in terms of ‘exhaustivity.’
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Which system is most exhaustive and how does that compare to the
system that is most specific?
Personal opinion
Question 18.
Do ebooks have call numbers? How exhaustive or
specific are the subject headings?
Personal opinion
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