Historical Quantitative Reasoning on the Web

A. Meroño-Peñuela, A. Ashkpour

Research output: Contribution to conferencePaperScientificpeer-review

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The Semantic Web is an extension of the Web through standards
by the World Wide Web Consortium (W3C) [4]. These standards
promote common data formats and exchange protocols on the Web,
most fundamentally the Resource Description Framework (RDF). Its
ultimate goal is to make the Web a suitable data space for humans (using
the paradigm of Linked Documents) as well as for machines (using the
paradigm of Linked Data). The latter has experimented an enormous
growth in the last years, mostly due to the adoption of Linked Data
publishing practices by institutions, governments and users, giving birth
to the Linked Open Data cloud: a Web-graph of 100 billion interconnected
facts and schemas (also called ontologies) [3]. Many domains have
published their datasets as Linked Open Data, including History [6,12],
converting them to RDF and linking them to related historical datasets
and concepts on the Web. One of the fundamental problems of historical
research are so-called gaps in historical evidence: the non-existence of
relevant historical data for a particular matter. The very exercise of historical
research has a primary focus on filling these gaps, generating the
missing knowledge (to a level of certainty) using diverse methods. When
raw historical datasets are published on the Semantic Web as Linked
Data, these gaps still exist [2]. In this paper, we investigate whether
existing Semantic Web technology is useful to fill these gaps of historical
knowledge. We study the way in which social historians derive new
knowledge from historical quantitative sources to fill missing gaps [2,13],
and we mimic their behavior in a Semantic Web setting, by adapting
existing technologies to, first, identify these gaps [14] and, second, to fill
them [17] We explore whether these mechanisms can be generalized to
be applied to other domains [18].
Original languageEnglish
Publication statusPublished - 30 Mar 2016


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