## 4 Discussion
### Fusepool in Practice
#### 4.1.1 Content Lookup and Discovery Engine by the Libraries of Free University of Berlin  
The Free University Berlin is one of Germany's top-ranked universities and hosts many of the nation's research excellence centers. The libraries of the Free University Berlin comprise the University Library (UB) and around forty departmental libraries with total holdings of around eight million printed items, 38,000 e-journals, 400,000 e-books and 1,300 databases. A library representative participated in the hackathon of the Data Hack Award 2014 in Berlin (DHA14) and developed a winning proposal that was implemented in less than a month and presented at the Fusepool showcase event in Brussels. The library system offers their own state-of-the art online search system. However, many of the external works are only full-text indexed, but not labeled with controlled keywords, which results in imprecise search results. As a consequence, users divert to other search tools that benefit from massive global amounts of data and are therefore more likely to retrieve relevant results just from full-text indices. For many years, printed materials (local holdings) where indexed by librarians using keywords from well-elaborated subject terminologies (such as GND, Integrated Authority File). Using subject terminologies enables grouping related materials and browsing them via semantic relations of concept identifiers (broader, narrower, related). However, manually indexing the vast amount of external material is not feasible. Resources from external providers do not share the same \"language\" (terminologies) with the local holdings, which makes it harder to deliver coherent search results beyond the local holdings. End users have to compensate for this semantic gap by guessing about synonyms that may appear in their desired results. Given this context, the main goals are two-fold:  
1. tools supporting library staff in the time consuming task of manual subject indexing;
2. new services that improve results and attract usage of library online search systems. The Fusepool SMA component (string matching algorithm) compares each word of a plain text input with strings provided in a dictionary in order to identify a match. Hence, the main question was how to use SMA to support librarians in subject indexing. For the proof of concept, the library used a set of controlled subject headings as a dictionary (a subset of GND published by the German National Library). Each identifier (GND Number) is dereferenceable following linked data principles. For example, the keyword \"linked data\" is represented using the unique identifier [[http://d-nb.info/gnd/7863462-3](http://d-nb.info/gnd/7863462-3)]([http://d-nb.info/gnd/7863462-3](http://d-nb.info/gnd/7863462-3)). However, the SMA requires the actual string \"linked data\" for computing the match. This did not pose a problem, because the GND authority data is represented as a thesaurus, which also includes alternative labels for most of the GND concepts. As a result, it is possible to automatically assign the correct identifier, 7863462-3, even when a text contains a synonym, e.g., \"linked open data\". The following usage scenarios are foreseen, depending on the perspective of the stakeholder:  
* Library staff: support in the time-consuming task of manual indexing the acquired materials. It should be possible to suggest identifiers based on the text input of book reviews, table of contents, abstracts and full texts;
* Researchers: suggestions of related content for their research topics. It should be possible to start research at any location in the WWW (not only library catalogue). Users want to collect significant text phrases and get suggestions of related content available in their library;* Publishers/authors: improve the findability of their content by adding controlled keywords (_i.e._, concept identifiers) easily. Their contents should be scanned automatically for phrases that can be represented with unique identifiers.