1. IL Step 3: Using Bibliographic Databases
Information Literacy

2. Bibliographic DB: Overview
Collection of bibliographic records
references to scientific publications
Journals, proceedings (books, etc.)
in specific disciplines
e.g., Biological Abstracts
in multiple disciplines
e.g., Web of Science, Scopus
Digital Library
Bibliographic DBs
contain rich information
Keywords, abstracts, (full-text, citation data)
are mostly proprietary
Charge usage fees
use English as primary language
Non-English titles translated to English
may have different record format
e.g., title vs. original title, author vs. primary author
may offer different search interfaces & options
Citation Database
Information Literacy

3. Bibliographic DB: Coverage
It is important to consider DB coverage before using.
Document Type
Journals, magazines, books, book chapters, dissertations, etc.
Publication Type
Scholarly, Popular, Trade, etc.
Discipline/Subject Area
Math & Physics, Computer Science, Social Science, etc.
Time Period
, 1990-present, etc.
Update frequency: annually, monthly, weekly, daily, etc.
Content
Brief description (abstract & references) vs. full-text
Citation metadata
For quality assessment
Enhanced search capability (e.g., following the thread)
Information Literacy

4. DB Coverage: Examples Web of Science -Tutorial - Scopus -Tutorial -
90M records (1900-present)
50,000 books, 12,000 journals & 160,000 conference proceedings
Multi-disciplinary, high impact scholarly publications
Owned by Clarivate Analytics - Sold by Thompson Reuters (started by Institute for Scientific Information)
Scopus Tutorial -
66M records
20M with references (1996-present) & 20M without references ( )
22,000 multi-disciplinary titles from 5,000 international publishers
20,000 peer-reviewed journals & 3.6M conference papers
Owned by Elsevier (a major publisher of international scientific journals)
JSTOR (Journal Storage) -Tutorial -
2000 academic journals from 900 publishers
Full-text publications in humanities, social sciences, & sciences
Operated by JSTOR, non-profit organization
Google Scholar
160M records (88% of English scholarly documents on the Web)
Multi-disciplinary titles in 30+ document types (varying quality)
Information Literacy

5. DB Searching: Records & Fields
DB Record
Describes information source
e.g., journal article
DB Field
Contains metadata about the information source
e.g., author, title, subject, publisher, publication date, etc.
DB Searches
Keyword Search – match in any field
Emphasis on finding as much information as possible
Field Search – search in specific fields
Focus on finding only desired information
General Strategy
Begin with keyword search
to find everything about a topic
to discover subtopics
Use field search
To find precise information about specific topics
on recalling as much information as possible
Field Search
red + blue + green
(Tie=red) + (Shirt=blue) + (Hat=green)
Information Literacy

6. DB Searching: Options & Tools
Wildcards
To group words with various spellings and forms
e.g., secret* → secret, secrets, secretary, etc secret? → secret, secrets
Quotation Marks
Around exact phrases (i.e., exact match)
e.g., “longevity secret?”, “longevity factor?”
Boolean Operators
Connecting words to broaden or narrow a search
e.g., secret? AND longevity, (secret? OR factor?) AND longevity
Proximity Operators
Connecting words that should appear near one another
e.g., (secret? OR factor?) NEAR longevity
to prevent happenstance occurrence of words “Secret of happiness is love. Longevity has noting to do with it.”
Information Literacy

7. DB Searching: Options & Tools
Searchable indexes
List of searchable terms (words that appear in DB)
e.g., author index, journal index
Thesaurus
Standardized list of keywords
Typically have a hierarchical structure
Each term can have
Broader term (BT)
Narrower terms (NT)
Related terms (RT)
Equivalent terms (ET)
Related Articles
Tool for finding “more like this” articles.
Offered by some DBs
Web of Science → articles that cite at least one document cited by current article
Scopus → articles that share same reference, keywords, or authors
PubMed → articles that share same words in title, abstract, MeSH terms (keywords)
Information Literacy

8. DB Searching: Search Refinement
Too much information
Examine non-relevant results
Why were they retrieved?
Modify the query to filter out non-relevant results
Add terms that exclude bad results
Use more specific terms
e.g. longevity AND secrets → longevity AND secrets NOT myths
Search in specific fields
e.g., subject, title
Too little information
Eliminate long phrases (i.e., exact match)
e.g., “longevity secrets” → longevity AND secrets
Use alternative terms
e.g., “longevity secrets” → longevity AND factors, longevity AND research
Try broader terms
e.g., “longevity secrets” → “long life”
e.g., “recombinant DNA” → genetic engineering
Information Literacy