Developing a tool for information retrieval and research purposes utilizing BookSampo data

Research output: ThesisMaster's thesis

Abstract

The goal of this thesis was to develop a new tool for information retrieval and research purposes based on the BookSampo data set. The current BookSampo portal uses Linked Data but offers limited search capabilities to the user that do not fully utilize the possibilities of Linked Data. The goal of the new portal was to offer the users both ways to visualize the data as well as a facet-based search, where the user could search and filter the result data set using different facets.

The portal was developed using the Sampo Model based Sampo-UI framework that makes it possible to build new semantic portals without requiring a lot of actual programming work. Developing new semantic portals using the Sampo-UI framework is based on editing configuration files that define the wanted components as well as the data location using a SPARQL endpoint. The data used in the portal was the BookSampo dataset, the quality of which was also assessed during the development process.

The final product is a Sampo-UI based semantic portal that uses unmodified BookSampo data, which was assessed to be of good quality considering the sheer volume of the data set. The portal offers the user five different perspectives that can be used for looking at and searching for data. The perspectives have their own visualizations developed for them based on the annotation coverage of the data that can be used for viewing the data in different formats, e.g., as a chart or on a map.

Sampo-UI framework fit the purpose well and makes it possible to develop the portal easily further in the future. The BookSampo data has and will be receiving the needed fixes, after which it could be published to public use and then improved based on the feedback received from users.

Original languageEnglish
QualificationMaster's degree
Awarding Institution
  • School of Science
Supervisors/Advisors
  • Hyvönen, Eero, Supervising Professor
  • Rantala, Heikki, Thesis Advisor
Award date20 Mar 2023
Publisher
Publication statusPublished - 20 Mar 2023
MoE publication typeG2 Master's thesis, polytechnic Master's thesis

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