1. Introduction: Multiple platforms that provide
searchable resources to a target user base participated in a federation. A user
makes a single query request in the federation, which is distributed to the all
the platform participating in the federation in real time with the appropriate
syntax for that resource. The federated search then aggregates the results that
are received from the platform for presentation to the user with minimal
duplication. One application of federated searching is the Meta search engine;
however, Meta search engine unable to index many documents called deep Web, or
invisible Web.
2. Definition: Peter Jasco defines federated
search as, “Transforming a query and broadcasting it to a group of disparate
databases with the appropriate syntax, merging the results collected from the
databases, presenting them in a succinct and unified format with minimal
duplication, and allowing the library patron to sort the merged result set by
various criteria”. The definition of federated search generally includes the
following aspects.
a) Search Scope: The federated search inspects
multiple resources simultaneously for relevant resources.
b) Software: Federated search engine is the software that use a
protocol standard such as Z39.50.
c) Presentation: The results are presented in a
uniform interface that of the federated search engine. Depending on the
particular program‘s capabilities, the results can be ranked and de-duped.
In simple,
federated search is an information retrieval technology that allows the
simultaneous search of multiple searchable resources in real time and presents
the resultant list in a unified way. Federated searches are inherently as
current as the individual information sources, as they are searched in real
time.
3. Approaches to Federated Search: Federated
search work by the following ways-
a) Search-Time Merging: A query federator intercepts
the query, and passes it to multiple platform or databases. The federator then
waits to hear replies from the platforms, and when received, merges the results
into a results list. This model relies on data repositories to provide a search
function.
The
primary advantage of this approach is ease of implementation, because no
additional indexing of content is necessary. The query federation system simply
taps into existing systems and extracts results, which are then merged.
The
merging of search results into a sensible hit list is difficult if based on
relevancy, as each search engine called will score relevancy in a different
way. Again, performance issues can occur if the federator waits for the slowest
remote search engine to respond.
b) Index-Time Merging: This approach requires content to
be acquired into a central index, and it is typical of traditional enterprise
search systems.
Through
acquiring all data into a central index, sophisticated query enhancement and
relevancy algorithms the user can be provided with excellent search results.
The effort
needed to acquire the content from the various repositories can be substantial.
The indexing process must read each item, and re-read it every time a change
occurs in the databases. In some cases,
for example where private content behind paywall is involved, this is not
possible.
c) Hybrid Federated Search: In hybrid approach the content
is indexed centrally. Repositories for which are not cost effective (or simply
not possible) are federated to at query time.
4. Federated Search Interfaces: A few
federated search interfaces provided by commercial vendors to the libraries are
mentioned below-
a) SEARCHit: SEARCHit
(https://www.auto-graphics.com/researchit-a-robust-federated-search-application/)
is a federated search tool from Auto-Graphics, Inc. that saves time by enabling
users to simultaneously search across multiple content resources and view a
combined results set.
b) Encore Discovery Solution: Encore Discovery Solution (https://www.iii.com/resources/product-overview-encore-discovery-solution) is a product from Innovative Interfaces Inc that fully integrates the
discovery process and gives users the types of self-service capabilities they
have come to expect through the web, by placing library and its unique
offerings at the forefront.
c) Primo®: Primo (https://www.exlibrisgroup.com/products/primo-discovery-service), a product from Ex Libris is a one-stop solution for the discovery and
delivery of local and remote resources, such as books, journal articles, and
digital objects.
d) MasterKey Connect (MKC): MasterKey Connect
(https://software.indexdata.com/mkc/mkc-profile.html), a product from Index
Data is a service which provides a simple network Application Programming
Interface (API) to thousands of online databases, journals, library catalogues,
and other resources. The service allows you to use a simple, XML-based API to
access practically any searchable site, whether open access or
subscription-based. It consists of open source software based on international
standards and communication protocols such as Z39.50, but also supports
non-Z39.50 searching.
5. Examples of Federated Search Engines: In the following,
a few examples of Meta search engines are given-
a) WorldWideScience (http://www.worldwidescience.org): WorldWideScience is hosted by the U.S. Department of Energy’s Office of
Scientific and Technical Information. WorldWideScience.org is a global
federated science search engine designed to accelerate scientific discovery and
progress by accelerating the sharing of scientific knowledge. Through a
multilateral partnership, WorldWideScience.org enables anyone with internet
access to launch a single-query search of national scientific databases and
portals in more than 70 countries, covering all of the world’s inhabited
continents and over three-quarters of the world’s population. From a user’s
perspective, WorldWideScience.org makes the databases act as if they were a
unified whole.
b) Science.gov (http://www.science.gov): Science.gov is
a federated search engine that serves as a gateway to information sources
representing most of the R&D output of the United States government
scientific and technical information and research. Science.gov searches over 60
databases and over 2200 selected websites from 15 federal agencies, offering
200 million pages of authoritative U.S. government science information
including research and development results.
6. Usefulness of Federated Search: The basic idea
of federated search is to improve the accuracy and relevance of individual
searches as well as reduce the amount of time required to search for resources.
The following are the usefulness of federated search-
a) Time Saving: Federated search allows a user to search
multiple databases at once in real time, arrange the results from the various
databases into a useful form and then present the results to the user. So, the
user is reluctant to go to all the databases individually.
b) Single Searching Platform for Multiple Resources: Federated search helps user to put his/her query into a single platform
and search multiple disparate content sources.
c) Familiar Interface: Searching for information using
electronic databases can be tedious and time-consuming as all databases use
different interfaces and query language to which user are not familiar with.
Federated search is the options here that provide only a single interface to
the user.
7. Problems with Federated Search Engines: A challenge
faced in the implementation of federated search engines is scalability, in
other words, the performance of the site decreases as the number of information
sources comprising the federated search engine increases.
a) Problem in Indexing of Subscription Databases: Not all federated search engines can search all databases, although most
can search Z39.50 and free databases. Most vendors that claim to offer
federated search engines cannot currently search all licensed databases due to
the problem with authentication for subscription databases. Before buying a
federated platform for your library, ask vendors to demonstrate that they can
search all of your library’s databases using your library’s own authentication,
both locally and remotely.
b) Duplication cannot be Avoided: To completely
de-dupe search results, it’s necessary to download all results from all
databases, but practically it is impossible. So, for federated search engines,
true de-duplication is virtually impossible. Vendors that claim to do true
de-duping usually are just de-duping the first results set returned by the
search.
c) Relevancy is Questionable: The abstract and full-text data, as well as
the indexing that content providers use to relevancy-rank their content, are
unavailable to federated search engines. The content providers have the full
article and indexing to work with, but not the federated search engines. They
have only the citation to search on, so the relevancy is a questionable thing
in federated search engine.
d) Native is Better than Federated: You can’t get
better results with a federated search engine than you can with the native
database search. In case of federated search platform, the same content is
being searched which are already taken care of by the native search engine at
the same time the federated engine does not enhance the native database's
search interface. All federated search does is translate a search into
something the native database’s engine can understand. But it’s restricted to
the capabilities of the native database’s search function. Federated searching
cannot improve on the native databases search capabilities. It can only use
them.
e) Time Taking: In a federated search interface
user needs to wait sometime to get all the result. Again, after getting the
result the user need to click on the resources relevant to them in the
federated retrieval list that will lead them to the individual databases. So,
ultimately the user needs to deal with both the federated search platform as
well as the native interface which again is a time consuming job. In case of general purpose search interfaces,
the results are generally arrived instantly.
8. Conclusion: Federated searching and
information retrieval service collect descriptive metadata from multiple,
diverse target resources, including but not limited to commercial or licensed
electronic resources, databases, Web pages, and library catalogues and present
a single interface to the user. The users can search all the databases from
that single interface itself and thus reluctant in remembering all the web
resource the library has access to. It should be noted; however, that the user
may have to deal with the native interface (e.g., Sage, Emerald, Elsevier) once
he or she clicks an item in the federated search results list, so using the
search results may ultimately require dealing with multiple interfaces.
How to Cite this
Article?
APA Citation, 7th Ed.: Barman, B. (2020). A comprehensive book on Library and Information Science. New
Publications.
Chicago 16th Ed.: Barman, Badan. A Comprehensive Book on Library and Information Science. Guwahati:
New Publications, 2020.
MLA Citation 8th Ed: Barman, Badan. A Comprehensive Book on Library and Information Science. New
Publications, 2020.

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