The current scientific context is characterized by intensive digitization of the research outcomes and by the creation of data infrastructures for the systematic publication of datasets and data services. Several relationships can exist among these outcomes. Some of them are explicit, e.g. the relationships of spatial or temporal similarity, whereas others are hidden, e.g. the relationship of causality. By materializing these hidden relationships through a linking mechanism, several patterns can be established. These knowledge patterns may lead to the discovery of information previously unknown. A new approach to knowledge production can emerge by following these patterns. This new approach is exploratory because by following these patterns, a researcher can get new insights into a research problem. In the paper, we report our effort to depict this new exploratory approach using Linked Data and Semantic Web technologies (RDF, OWL). As a use case, we apply our approach to the archaeological domain.
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Thanos, C., Meghini, C., Bartalesi, V. et al. An exploratory approach to archaeological knowledge production. Int J Digit Libr 23, 231–239 (2022). https://doi.org/10.1007/s00799-022-00324-3
- Knowledge bases
- Knowledge discovery
- Linked data
- Semantic web
- Archaeological knowledge