Fagi: A framework for fusing geospatial RDF data

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Abstract

In this paper, we present FAGI, a framework for fusing geospatial RDF data. Starting from two interlinked datasets, FAGI handles all the steps of the fusion process, producing an integrated, richer dataset that combines entities and attributes from both initial ones. In contrast to existing approaches and tools, which deal either with RDF fusion or with spatial conflation, FAGI specifically addresses the fusion of geospatial RDF data. We describe the main components of the framework and their functionalities, which include aligning dataset vocabularies, processing geospatial features, applying -manually or automatically- fusion strategies, and recommending link creation or rejection between RDF entities, with emphasis on their geospatial properties.

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Giannopoulos, G., Skoutas, D., Maroulis, T., Karagiannakis, N., & Athanasiou, S. (2014). Fagi: A framework for fusing geospatial RDF data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8841, pp. 553–561). Springer Verlag. https://doi.org/10.1007/978-3-662-45563-0_33

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