Understanding LISA Database Field Codes

The question asks about a specific field nomenclature, 'NOFT', used within the LISA database. LISA stands for Library and Information Science Abstracts, which is a major abstracting and indexing database covering library and information science topics. When searching databases like LISA, users often have the ability to specify which parts of a record they want to search in, such as the title, author, abstract, subject terms, or full text.

These specific searchable parts of a database record are often referred to as fields. Databases use specific codes or labels to represent these fields in search queries. The term 'NOFT' is a common field code used in many abstracting and indexing databases, including those that might host LISA content, to specify that a search term should appear in any searchable field *except* the full text of the document.

Analyzing the 'NOFT' Nomenclature in LISA

Let's break down the meaning of 'NOFT' in the context of database searching:

• 'NO' typically signifies 'Not' or 'Excluding'.
• 'FT' typically signifies 'Full Text'.

Combining these, 'NOFT' logically translates to 'Not Full Text' or 'Excluding Full Text'. This means a search using 'NOFT' will look for your search terms in fields like the title, abstract, subject headings, author, etc., but will deliberately ignore the complete body or full text of the document.

This is useful when you want to find documents where your search term is a primary subject or mentioned in a significant part of the record (like the abstract or title) rather than just incidentally appearing somewhere within a lengthy full text document. Searching 'Anywhere' often implies searching across all fields, including full text if available, whereas 'NOFT' provides a more targeted search.

Evaluating the Options

Based on the understanding of database field codes and the likely meaning of 'NOFT', let's look at the options provided for the LISA database nomenclature:

1. Nowhere
2. Anywhere
3. Anywhere except full text
4. Nowhere full text

Option 1, 'Nowhere', is incorrect as 'NOFT' specifies a location for the search, not the absence of one.

Option 2, 'Anywhere', is too broad. 'Anywhere' usually includes the full text, which 'NOFT' specifically excludes.

Option 4, 'Nowhere full text', is grammatically awkward and doesn't accurately reflect the exclusion of full text from an 'anywhere' search.

Option 3, 'Anywhere except full text', perfectly matches the likely meaning of 'NOFT' as 'Not Full Text', indicating a search across all typical searchable fields *except* the full text content. This allows searching in key areas like titles, abstracts, and subject terms.

Conclusion

In the context of the LISA database and standard database searching practices, the nomenclature 'NOFT' is used to specify searching in fields anywhere within the record *except* the full text. Therefore, the correct label is 'Anywhere except full text'.

This table illustrates which common fields would typically be included or excluded when using a 'NOFT' search, reinforcing that it covers 'Anywhere' *except* the 'Full Text'.

Revision Table: LISA Database Searching

Additional Information: Database Searching Concepts

Understanding field codes like 'NOFT' is crucial for effective database searching. Here are some related concepts:

• Boolean Operators: Terms like AND, OR, NOT used to combine or exclude search terms. For example, "library AND technology" finds results containing both terms.
• Proximity Operators: Operators used to specify how close search terms must be to each other (e.g., NEAR, ADJ).
• Truncation and Wildcards: Symbols (like *, ?, #) used to search for variations of a word (e.g., librar* finds library, libraries, librarian).
• Controlled Vocabulary: Predefined subject terms or descriptors used by the database to index content, providing a standardized way to search for concepts (e.g., using "Information Retrieval" instead of searching for all its synonyms).

Knowing how to use field codes, combined with these other techniques, allows for much more precise and relevant results when searching databases like LISA.