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An ontology-driven knowledge graph for tourism information management
Abstract
Background Lao Tzu, the ancient Chinese philosopher, had famously said, “a journey of a thousand miles begins with a single step”. The modern ecosystem of tourism is extremely multi-faceted and multi-context dependent, so much so that tourists, planning on an excursion, have an entire range of queries from as basic as “Where to eat?” to as complex as “List all the eating establishments which are suitable for groups and also provide children menu”. Such a list becomes even more complicated due to the intermixing of different perceptions, languages, cultures and economies in which tourists are enmeshed in. Accordingly, such increasing complexity in questions from tourists necessitate the need to provide specialized and fine-grained data and information services which are beyond the Information and communications technology (ICT) infrastructures in vogue in tourism today. Methods In this paper, we propose and advocate the use of, via a theoretically and implementationally well-founded methodology, the Artificial Intelligence (AI) backed technology of ontology-driven Knowledge Graphs, to provide fine-grained information services to tourists at any scale and at any level of complexity. Results and Conclusions The methodology is validated by developing a fully populated tourism-specific ontology-driven knowledge graph having 4264 RDF statements and ready for reuse, extension and exploitation as a part of any of the current ICT infrastructure in tourism sector.
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The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.18 · Cited by 18,423 · cited 1×
“…a socio-technical perspective, the methodology can provide the starting basis on which an all-encompassing FAIR information organization ecosystem 16,17 can be built which can subsequently be exploited by all players in tourism - tourists, businesses, governments, human and artificial agents,…”
Al-Hassan, M., Lu, H., & Lu, J. (2015) · Decision Support Systems · doi:10.1016/j.dss.2015.02.001 · Cited by 136
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Metadata
- Authors
- DAS, S., & Bagchi, M.
- Venue
- Open Research Europe
- Publisher
- CERN
- Published
- 2025-07-23
- ISSN
- 2732-5121
- Cited by
- 1
- References
- 2
- Funders
- European Commission (101034371)
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