Cultural Heritage Information Retrieval: Data Modelling and Applications

Tracking #: 2250-3463

This paper is currently under review
Authors: 
Babak Ranjgar
Abolghasem Sadeghi-Niaraki
Maryam Shakeri

Responsible editor: 
Special Issue Cultural Heritage 2019

Submission type: 
Survey Article
Abstract: 
Knowledge organization and development of better information retrieval techniques were of great importance from very an early time period in human history. The need has grown high for such systems with the advent of digitization and the web era. Computer systems and web have offered easier retrieval of information in almost no time. However, as the amount of data increased, these systems were not able to work well in terms of accuracy and precision of retrieval. Semantic Web concept was introduced to overcome the issue by converting the web of documents to a web of data. Semantic Web technologies make data machine-understandable so that information retrieval can be more precise and accurate. The Cultural Heritage community is one of the first domains to adopt Semantic Web recommendations and technologies, which can provide interoperability between various organizations by creating a shared understanding in the community. The data in the CH domain differs widely with types and formats. Also, a lot of organizations and experts from various fields interact through different processes within this community. Due to the mentioned needs, the CH employed Semantic Web technologies step by step along its evolution process for better knowledge management and a uniform understanding among the community. In this paper, we presented this process from its initial steps to the latest developments in the CH information retrieval. By making data machine-readable, the Semantic Web ena-bles a wide set of opportunities to develop smart applications based on rich CH information besides better information retrieval. In this paper, we also reviewed intelligent applications and services developed in the CH domain after establishing semantic data models and Knowledge Organization Systems.
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