1. “What Everyone Calls It”
Mapping Users’ Words and Terminologies
Stephanie W. Haas
School of Information and Library Science
University of North Carolina at Chapel Hill

2. BLS and FedStats Hert & Marchionini, 1998
User information needs & statistical information
Types of users and their tasks
Search strategies and tools
How do skilled intermediaries search?
How do domain experts search?
How do domain novices search?
How can user strategies be improved?

3. Interface design for website to support user tasks
Knowledge representation, metadata, and terminology
foundation for information sharing, both inside and outside the system
coordinate possibly contradictory concepts, terms, etc.

4. Searching isn’t easy
Borgman, 1996, “Why Are Online Catalogs Still Hard to Use?”
Query systems generally designed for skilled users
“Query matching is effective only when the search is specific, the searcher knows precisely what he or she wants, and the request can be expressed adequately in the language of the system” (p. 494)

5. The Mapping Problem Search Data Element(s) Term(s) User’s Term(s)
Information
Need

6. Inside the System Crisp operational definitions
Expert understanding and usage
Data
Element(s)
Term(s)

7. Outside the System Choice of terms may depend on:
user’s domain knowledge
user’s search knowledge
user’s notion of what is available
luck?
User’s
Term(s)
User’s
Information
Need

8. Miss, Meeting, or Collision?
Term(s)
User’s
Term(s)
Not necessarily the same as mapping between terminologies.
What are the possible relationships between system terms and user terms?

9. Possible Mappings Same word(s), same meaning
Same word(s), different meaning
Same word(s), some relationship between meanings (e.g., BT, NT, part-of, domain specific)
Same word(s), some overlap in meaning

10. Possible Mappings (cont.)
Different word(s), same meaning
Different word(s), different meaning
Different word(s), some relationship between meanings (e.g., BT, NT, part-of, domain specific)
Different word(s), some overlap in meanings

11. Search Terms from FedStats Web Page
Carol Hert & John Fieber
11/98, 28,248 unique queries
concept of pay
income
compensation
earnings
wage
salary

12. Users’ Search Terms “income”; 948 unique queries, 2025 instances
combined with:
statistical concepts, e.g., mean
temporal concepts, e.g., current, 1990
geographical concepts, e.g., national, Boston

13. combined with (cont.): demographic concepts gender, e.g.,women, male
age, e.g., elderly
race, e.g., race, african american
marital status, e.g., divorced
education, e.g., education level, college graduate
occupation, e.g., occupation, correction officer

14. BLS/CPS Terms Total combined income Compensation
“includes money from jobs, net income from business, farm or rent, pensions, dividends, interest, social security payments and any other money income received” (CPS)
Compensation
“sometimes used to encompass the entire range of wages and benefits” (BLS Glossary of Compensation Terms)

15. BLS/CPS Terms (cont.) Usual weekly earnings Hourly earnings
“include any overtime pay, commissions, or tips usually received” (CPS concepts)
Hourly earnings
“hourly rate as stated by the employer…does not include tips, commissions, or any other non-hourly wages.” (CPS interviewer manual)

16. What does this user want? correction officer, income
Money income received - including that unrelated to job
Compensation, including benefits - total job package
Usual weekly earnings - including regular overtime
Hourly earnings - excluding overtime

17. Open Issues
Can a system recognize the user’s intention and/or information need?
need for user studies
identifying user expertise
user education in terminology, domain, e.g., statistics (Dippo, 1998)
recognizing changes in system and user terms, possible mappings

18. Open Issues (cont.) Where does terminology mapping information belong?
concept/terminology representation
special-purpose thesaurus
user interface
query formulation and clarification tools
explanation of provided information