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Semantic Web
Article . 2015 . 2014 . Peer-reviewed
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Semantic Web
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Semantic technologies for historical research: A survey

Authors: Meroño-Peñuela, A.; Ashkpour, Ashkan; van Erp, Marieke; Mandemakers, Kees; Breure, L.; Scharnhorst, A.M.; Schlobach, Stefan; +1 Authors

Semantic technologies for historical research: A survey

Abstract

During the nineties of the last century, historians and computer scientists created together a research agenda around the life cycle of historical information. It comprised the tasks of creation, design, enrichment, editing, retrieval, analysis and presentation of historical information with help of information technology. They also identified a number of problems and challenges in this field, some of them closely related to semantics and meaning. In this survey paper we study the joint work of historians and computer scientists in the use of Semantic Web methods and technologies in historical research. We analyse to what extent these contributions help in solving the open problems in the agenda of historians, and we describe open challenges and possible lines of research pushing further a still young, but promising, historical Semantic Web.

Country
Netherlands
Subjects by Vocabulary

Microsoft Academic Graph classification: Computer science media_common.quotation_subject Semantics Presentation Semantic Web media_common business.industry Information technology Data science Quantitative history Comparative historical research Semantic technology business Meaning (linguistics)

Keywords

Computer Networks and Communications, Digital Humanities, ESHCC HIS, Semantic Web, Computer Science Applications, historical research, Information Systems

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    Top 10%
    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    62
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
62
Top 10%
Top 10%
Top 10%
hybrid