Ehret Snyder,
C. (2013, Dec 20). Data-driven deselection: multiple point data using a
decision support tool in an academic library. Collection Management, 39, 11-31. https://doi.org/10.1080/01462679.2013.866607
Weeding is a time-consuming and sensitive task for
librarians. It is necessary to make space for new material, keep information current
and updated, and remove items in poor condition. Librarians have to determine what
kind of data is necessary to review in order to justify removing an item from
the library’s shelves. Tools exist to help librarians gather multiple points of
data to make the process more efficient. The librarians at Olin Library, part
of Rollins College in Florida, utilized such a tool (Sustainable Collections
Services) to help them update their collection and present the findings in this
paper.
Summary:
Librarians are short on time and weeding is one of the
most time-consuming tasks they can take on. Criteria is necessary to make
decisions and librarians must find the information, analyze, and track it to
make informed decisions. Some information, like circulation history, copies,
donor information, and publication dates are available via the catalog. Decision
support tools can help librarians identify data points, select the measurable
information, and compile it into a useable format.
One example of a data point that can be identified and
defined is the obsolescence rate. That is the degree to which the demand for an
item decrease over a year, which varies by subject. Computer science texts will
decrease rapidly, while history texts would decline more slowly. That
information would be helpful to set cutoff years; librarians could say that science
texts are available for deaccession after a period of 10 years since information
is likely to have changed greatly and old texts may be inaccurate.
The Olin Library weeding task force had planned a weeding
project using only one point of data-- date of last use. They were contacted by
Sustainable Collections Services to test out a new tool in development. The
librarians agreed and provided SCS their holding data as well as choosing additional
criteria from a suggested list, justification for the criteria, and limits for
each point. They ended up with six
points of criteria and an item must meet each criterion to be a candidate for
withdrawal. SCS provided additional information for those items like donation
and gift notes for reference. The librarians then added physical flags to each
book on the shelves and advertised that the books were up for review and that
students and faculty could remove the flags if they felt like the items should
stay. After a defined period of time, they then removed any flagged books that
were left and donated them.
The task force found that the tool helped the process
immensely. It asked the librarians to better determine withdrawal criteria,
gave more information based on that criteria, and boosted the librarian’s
confidence in their decisions to withdraw because the item was available
elsewhere. It helped the librarians identify rare books that should qualify for
preservation and note that information for future weeding cycles. The tool also
facilitated the plan to utilize faculty review; most faculty noted that the
withdrawal criteria was sound.
The library’s test agreement with SCS ended, but they
decided to purchase a service to move the weeding project forward. They found
that the service greatly improved their collection management by thoughtfully
reviewing items, but in a timely and efficient manner.
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