Content Analysis of Academic Departmental Homepages=20
As a science reference librarian and bibliographer =5BYes, I do have a =
real job, (and a wife, three kids, mortgage, etc. =5B:->=5D, I seek to =
maintain an understanding of the information needs of my clientele as well =
as the research interests of the faculty and staff I serve in the =
selection of materials that will best support their research interests.=20
Last year, in an effort to gain a better understanding of such =
interests, I identified and reviewed the Web pages of my liaison department=
s as well as the official individual homepages of each member of a =
department, e.g. Aeronautical Engineering. My immersion and digestion of =
this formal information, has been of greay benefit in identifying and =
selecting materials for purchase for our library collection =5BThis =
knowledge has been most useful in decisions realating to the purchase of =
more expensive engineering monographs and proceedings=5D.=20
At one point, I considered tabulating the interests of my departmental =
faculty into a spread- sheet as a formal aid for assisting in the decision =
process for retrospective purchases as well as future considerations. =
However, in a recent revisit to my project on the use of Intelligent =
Software Agents for library applications, it occurred to me that an ideal =
application of Agent Technology for collection development for libraries =
would be one in which Agents analyze the contents of departmental =
homepages and generate a group user profile department based upon a =
synthesis of the expressed (and possibly implicit or latent) collective =
research interests.=20
With such a collective user profile, one could now consider using it =
as a Mega Search Statement that another agent would use to search the =
Web, local (or remote) licensed index and abstract databases, other OPACs, =
etc. to identify relevant resources for subsequent consideration for =
selection and purchase and/or incorporation within the local =27collection=
=27. Of course, we would want the ability to instruct the Content Agent =
so that we would be able to be selective in a choice of a department an/or =
to specify the type of electronic database for a subsequent search by the =
Search Agent.=20
One would of course wish to manage that agents such that one could =
massage the results of each agent such that results could be organized =
according to professional judgment.=20
It would be hope that the results could in turn be used to identify =
the deficiencies of the local =27collection=27. For example, to identify =
those e-journals that best =27suit=27 the interests of a department, or to =
identify key Web resources that would serve the interests of a department =
or a rsearch group within a department. =20
One could also imagine providing an alerting service to which a faculty =
member could subscribe that would provide them with a Mega Current =
Awareness Service of newly discovered items. =5BOne could indeed consider =
using another agent, a Feedback Agent, that in turn could provide a Real =
Time update to each and every faculty members interests based upon their =
selection and use of selected resources=5D=20
In planning for the formal establishment of my clearinghouse devoted =
to the use of Agents for collection development, reference as well as =
technical services, called _Library Agents(sm)_ =7B:->=5D, I would be =
interested in learning about any efforts envisioned, as well as those =
related to it. BTW: The address for Library Agents(sm) is:=20
http://www.public.iastate.edu/=7ECYBERSTACKS/Agents.htm=20
Currently, this site has a fuller description of the Larger Project, =
as well as links to key Agent clearinghouses.=20
=5BI am aware of the various e-mail alerting services offered by =
publishers (e.g., Elsevier, IOP) and information services (e.,g EBSCO, =
ISI) and would appreciate learning about any compendium of such Agent-based=
services as basic background for Library Agents(sm).=5D=20
As Always, Any and All citations, sources, contributions, critiques, =
questions, concerns, comments, or queries are Most Welcome=21 =20
Joy=21 =20
Gerry McKiernan Curator, CyberStacks(sm) Iowa State University Ames IA =
50011 =20
gerrymck=40iastate.edu http://www.public.iastate.edu/=7ECYBERSTACKS/ =20
=22The Best Way to Predict the Future is To Invent It=22 =
Attributed to Peter Drucker =20
=20
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