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Assignment 2: Keyword Wiki Entry

Search Interfaces

Search interfaces are access links or gateways by which library clienteles can search library contents or repositories. There are many search interfaces, such as

A. Discovery Layer,

B. Document Surrogate; and

C. Faceted Search.

Discovery Layer

The Discovery layer is also known as web-scale discovery, a construct used for unified web software that allows library users to query numerous library database on a single searchable interface. The Discovery layer is the search system for finding, viewing, and relating to the library's information content. It offers a solitary access point to the complete library resources, including digitized, licensed and subscribed collections. A unified search box is provided together with a range of other navigation features [1]. It links users to desired results based on the keywords used, easy searching and algorithm-ranked results [2]. The searchable contents from discovery comprise but not limited to print resources, electronic information resources like e-books, e-journals, audio-visual and all forms of information resources domiciled in other libraries and databases.

The discovery layers are considered as the extension of the third-generation library catalogues [3]. Ever since Discovery layers have been introduced in 2009 to libraries, academic libraries have extensively adopted it to improve ease of access to the variety of scholarly library collections or resources. Discovery layer comes in proprietary and open-source modes [4].

The major attributes of discovery layers are:

  • end-user features and accounts;
  • facets, category, and other tools for refining and using the results;
  • links to full-text through straight connections and OpenURL;
  • quick response time; relevant-ranked results list; and
  • solitary search across the central index [5].

University of British Colombia Discovery Layer interface

Figure 1: University of British Colombia Discovery Layer, (credit UBC Library)


Categorisation of library resources

The discovery layer has not been able to categorize types of materials, i.e. differentiate either the materials are books or research articles.  

Technical Knowledge

The discovery layer is complex and requires a high level of technical ICT skills, such as customization or API knowledge. The discovery technologies keep on changes and need ICT librarians to adapt to the changes; the electronic resources librarian fights to keep up with link resolvers, proxy servers, and many others [6].

Document Surrogate

Surrogate derives from the Latin word surrogate, which connotes “to substitute” or “to put in another’s place,” The word document means a “written or printed paper that provides evidence or proof” also “whatever bearing readable lettering or inscription.” Document surrogates in an information system are referred to as catalogue records that give valuable insights and brief information about library information resources such as physical books, e-books, manuscripts, journals, periodicals, maps, audio-visual etc. When library users query the library databases, they are usually presented with results that summarize each of the items retrieved. These summaries are recognized as document surrogates, which are brief displays that denote the real document [7]. Following the user’s query, the systems present the retrieved records’ surrogates, i.e., full bibliographic details about the item such as author name, title, source, author, pages, ISBN, call number, and some contain abstract, etcetera. By default, some systems display more information about the retrieved document, while most require the user to request the document’s full text [7]. Typical examples of document surrogates provided by the University of British Colombia are shown in figure 1,2, 3 & 4.

The retrieved resources display in a surrogate form containing author, title, keywords, abstract and summaries, etc. It facilitates selections of resources that will meet users' information needs, eases literature searches, and saves users' time [7].

UBC Library listing parts of result (metadata) document surrogate (image 2)

Figure 3: UBC Library interface displaying document surrogate with an abstract and little bibliographic information of the resource

Figure 4: UBC Library interface displaying document surrogates with detailed bibliographic information of the resource [8]

Document Surrogate Disadvantages

Mismatch or vocabulary problem

User queries are generally processed with ontologies and indexes, user must know exact search terms to use to query the system (such as name, title or subject) before they can access document surrogates [7].

Faceted search

Faceted search, otherwise known as faceted browsing or faceted navigation, is a practice used by libraries to support users to assess and filter sets of information resources (results). Faceted search is a leading technique for searching library resources, and where users can narrow down the query results by applying filters, called facets. Faceted search help user to narrow down their search results and find the relatively perfect information resources [9]. Faceted search is a navigation approach which allows users to explore anticipated information in an interactive style. The faceted search system displays users an outline of the existing search results in form of facets [10]. For example, in the University of British Colombia site shown in figure 1.

Faceted search helps users to lessen the amount of search results quickly and get the anticipated information timely. The all displayed narrow options support users to better recognize how data are organized and possibly use that information to formulate better search queries in the future (Vora, 2009). It uses more innovative search technologies than the earlier search interfaces and enhance user interaction with the information system [11].

Figure 5: UBC Library Faceted Search Feature


Basic data model and restrictive information 

In faceted search the basic data model where resources are linked with sets of values across numerous autonomous facet hierarchies is too limiting to model some real-life data [12].


  1. Dempsey, L. (2010). "Discovery layers-Top Tech Trends 2. Lorcan Dempsey blog". Retrieved 2021-02-02.
  2. Evelhoch, Z (2018). "Where users' find the answer: discovery layers versus databases". Journal of Electronic Resources Librarianship. 30(4): 205-215.
  3. Sonawane, C.S. (2017). "Library Discovery System: An integrated approach to resource discovery". Informatics Studies. 4(3): 27–38.
  4. Karadia, A.; Pati, S (2015). "Discovery Tools and Services for Academic Libraries". Retrieved 2021-02-02.
  5. Hoeppner, A (2012). "The ins and outs of evaluating web-scale discovery services". Computers in libraries. 32(3).
  6. Minkin, R. M.; Tobias, C (2017). "Bridging the (unit) divide: applying user experience to a discovery layer. Satellite Meeting - Reference and Information Services & Information Technology Sections: Evaluating and Implementing Discovery Systems" (PDF). IFLA. Retrieved 2021-02-02.
  7. 7.0 7.1 7.2 7.3 Azad, H. K.; Deepak, A (2019). "Query expansion techniques for information retrieval: a survey. 5". Information Processing & Management. 56(5): 1698–173.
  8. University of British Colombia Library (20201). "Summon serials solutions". UBC. Retrieved 2021-02-24. Check date values in: |date= (help)
  9. Arenas, M; Grau, B.C.; Kharlamov, E.; Marciuška, S.; Zheleznyakov, D (2016). "Faceted search over RDF-based knowledge graphs". Journal of Web Semantics. 37: 55–74.
  10. Komamizu, T; Amagasa,, T; Kitagawa, H (2015). "Facet-value extraction scheme from textual contents in XML data". International Journal of Web Information Systems. 11(3): 270–290.CS1 maint: extra punctuation (link)
  11. Niu, X (2014). "Faceted Search in Library Catalogs: New Directions in Information Organization". Library and Information Science. 7: 173–208.
  12. Ben-Yitzhak, O; Golbandi, N; Har'El, N; Lempel, R; Neumann, A; Ofek-Koifman, S; Yogev, S (2008). "Beyond basic faceted search". Proceedings of International Conference on Web Search and Data mining: 33–44.