scholarly journals Using the Semantic Web in digital humanities: Shift from data publishing to data-analysis and serendipitous knowledge discovery

Semantic Web ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 187-193 ◽  
Author(s):  
Eero Hyvönen
2018 ◽  
Vol 2 (1) ◽  
pp. 15-26 ◽  
Author(s):  
Xia Cuijuan ◽  
Liu Wei ◽  
Zhang Lei

Abstract Linked data is becoming a mature technology as a lightweight realization of the Semantic Web, as well as a way of facilitating knowledge reorganization and discovery. As a use case and start point, based on linked data technology, a genealogy knowledge service platform was implemented by the Shanghai Library for providing knowledge discovery and open data services. This article explains the design and development of the Genealogy Knowledge Service Platform, describes the method and process of the implementation, and introduces four examples of how the platform helps users to discover questions, raise questions, and solve questions for their research, to explain how Linked Data can be used in Digital Humanities.


Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 367 ◽  
Author(s):  
Martín López-Nores ◽  
Omar Bravo-Quezada ◽  
Maddalena Bassani ◽  
Angeliki Antoniou ◽  
Ioanna Lykourentzou ◽  
...  

Recent advances in semantic web and deep learning technologies enable new means for the computational analysis of vast amounts of information from the field of digital humanities. We discuss how some of the techniques can be used to identify historical and cultural symmetries between different characters, locations, events or venues, and how these can be harnessed to develop new strategies to promote intercultural and cross-border aspects that support the teaching and learning of history and heritage. The strategies have been put to the test in the context of the European project CrossCult, revealing enormous potential to encourage curiosity to discover new information and increase retention of learned information.


2010 ◽  
Vol 1 (1) ◽  
pp. 1757-1764 ◽  
Author(s):  
Oliver Rübel ◽  
Sean Ahern ◽  
E. Wes Bethel ◽  
Mark D. Biggin ◽  
Hank Childs ◽  
...  

2008 ◽  
pp. 2734-2748
Author(s):  
Henry Dillon ◽  
Beverley Hope

Knowledge discovery in databases (KDD) is a field of research that studies the development and use of various data analysis tools and techniques. KDD research has produced an array of models, theories, functions and methodologies for producing knowledge from data. However, despite these advances, nearly two thirds of information technology (IT) managers say that data mining products are too difficult to use in a business context. This chapter discusses how advances in data mining translate into the business context. It highlights the art of business implementation rather than the science of KDD.


2009 ◽  
Vol 10 (2) ◽  
pp. 153-163 ◽  
Author(s):  
M. Dumontier ◽  
N. Villanueva-Rosales

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