Системы обнаружения информации в библиотеках: новый подход к поиску

A discovery system is a bibliographic search system based on search engine technology. It is part of the concept of Library 2.0 and is intended to supplement or even replace the existing OPAC catalogs. These systems emerged in the late 2000s in response to user desire for a more convenient search option similar to that of internet search engine. The results from searching a discovery system may include books and other print materials from the library's catalog, electronic resources such as e journals or videos, and items stored in other libraries.

As the web became more widespread, library users developed "the expectation of being able to discover the collection in a search engine style". Gradually, discovery interfaces were created to be more forgiving of misspellings and punctuation choices than historical OPACs, and to offer features like suggestion of related search terms and faceted search. They were concerned that library users had to hunt for various types of resources with various tools, an obstacle to users, resulting in underused resources. Librarians sought multidatabase search products that would collapse the silos.

These two features, search engine like interfaces and multidatabase search, began to appear in the same software systems. One author dates the uniting of these features to 2009; this would be the invention of the discovery system. Some libraries maintain both a catalog interface OPAC and a discovery layer interface.

Large search space: A search can search the data from different data sources (the discovery system has a comprehensive central subject index). For example, you can search a journal article or a textbook directly in the discovery system and you do not have to change from a subject database to the library catalog. Intuitive usability, like a search engine. The search is basically only a simple form, an advanced search function is not always provided. Ranking of the results according to relevance: The "best" hit is displayed first, not necessarily the newest one. A good ranking is important because many hits are often found due to the large search space. Search refinement with drill down menus (facets): For example, a search can be restricted to all matches available online. Correction of input errors via a "Did you mean  ?" function. Autocomplete: After input to the search field, a drop down list of suggestions appears. Exploratory search: One finds results of interest that were not specifically requested. For example, links to similar hits, entries in subject databases, or Wikipedia articles are displayed (integration of other web technologies).

Software Developer Year of release Year of latest stable release Written in Main purpose License Wikipedia article w/out issues VuFind Villanova University 2010 2021 PHP Discovery GPL 2.0 only ✔ Blacklight University of Virginia Library, Stanford University Libraries, and Project Blacklight team 2009 2021 Ruby Discovery Apache 2.0 ✔