In this module, three questions were posed:
What is the difference between structural queries and query protocols?
Baeza-Yates and Ribeiro-Neto define a “structural query” as one that leverages organizational elements like parts of or divisions within in a document . These types of queries allow the user to create more specific, directive queries that deliver more precise results, as retrieved documents must not only satisfy the query within basic text but also do so within the required constraints. An example of a “structural query” would be a “fixed structure” that allows for use of certain fields. For example, in Lexis Academic one can search the news databases in fields like headline, written by, or publication name.
A “structural query” is a type of query that an end user would enter. A “query protocol,” in contrast, is one that is not meant to be used by humans. In fact, Baeza-Yates and Ribeiro-Neto use the term “protocol” specifically, in contrast to “language,” to emphasize that point. Z39.50, which is offered as an example, is a query protocol that the NISO’s primer describes as “a common language that all Z39.50 systems can understand” and “enables two computer systems on a network to communicate for the purpose of information retrieval.” (See http://www.niso.org/publications/press/Z3950_primer.pdf ). In other words, it provides a common way that two systems can talk to each other and understand each other, rather than an end user and a system.
What type of query do you use most often?
The type of query I use most, often depends upon the type of research I am doing. If I am doing legal research and I have already carefully thought through my query and what types of documents might best satisfy it, I will employ Boolean search logic within a structured query. For example, on Lexis Advance, if I were to search for caselaw in the state of Florida involving a party named “Smith” and heard by a judge named “Jones,” my query might look something like name(smith) AND judge(jones) AND court(florida). This would enable me to retrieve all of the documents that I want and definitely exclude those that do not meet my information need.
If I am searching for general information on Google though, and I’m not sure what document might satisfy my information need – or what my information need is to begin with – I might just start with a single term search. Akin to “berry picking,” I will find myself following a hypertext link trail, collecting alternate terms, and meandering around the web rather than taking a methodical approach. In fact, sometimes I will start my legal research this way, and once I am comfortable with the terminology, switch over to a legal database to perform a structured search.
Why we are still facing so many problems finding the right documents, images, video while we are searching?
I believe the answer here is that researchers are not patient and not willing to take the time to think about the following things:
(1) What they are looking for,
(2) What types of resources would be the most appropriate places to find that information,
(3) Once they figure out those resources, how to construct a valid query within them, and with what terms, and
(4) Take the time to understand how the system they are researching processed that query and retrieved the documents that it did, in the order that it did.
I think people too often just jump right in and start searching, which leads to “garbage in, garbage out.”