A decade of Semantic Web research through the lenses of a mixed methods approach

Tracking #: 1850-3063

This paper is currently under review
Sabrina Kirrane
Marta Sabou
Javier D. Fernandez
Francesco Osborne
Cécile Robin
Paul Buitelaar 1
Enrico Motta
Axel Polleres

Responsible editor: 
Christoph Schlieder

Submission type: 
Full Paper
The identification of research topics and trends is an important scientometric activity. In the Semantic Web area, initially topic and trend detection was primarily performed through qualitative, top-down style approaches, that rely on expert knowledge. More recently, data-driven, bottom-up approaches have been proposed which can offer a quantitative analysis of the research field’s evolution. In this paper, we aim to provide a broader and more complete picture of Semantic Web topics and trends by adopting a mixed methods methodology, which allows a combined use of both qualitative and quantitative approaches. Concretely, we build on a qualitative analysis of the main seminal papers, which have adopted a top-down approach, and on quantitative results derived with three bottom-up data-driven approaches (Rexplore, Saffron, PoolParty) on a corpus of Semantic Web papers published in the last decade. In this process, we both use the latter for “fact-checking” on the former and also derive key findings in relation to the strengths and weaknesses of top-down and bottom-up approaches to research topic identification. Overall, we provide a reflectional study on the past decade of SemanticWeb research, however the findings and the methodology are relevant not only for our community but beyond the area of the Semantic Web to other research fields as well.
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