Abstract
In this paper, we introduce Sheet2RDF, a platform for the acquisition and transformation of spreadsheets into RDF datasets. Based on Apache UIMA and CODA, two wider-scoped frameworks respectively aimed at knowledge acquisition from unstructured information and RDF triplification, Sheet2RDF narrows down their capabilities in order to restrict the domain of acquisition to spreadsheets, thus taking into consideration their peculiarities and providing informed solutions facilitating the transformation process, while still exploiting their full potentialities. Sheet2RDF comes also bundled in the form of a plugin for two RDF management platforms: Semantic Turkey and VocBench. The integration with such platforms enhances the level of automatism in the process, thanks to a human-computer interface that can exploit suggestions by users and translate them into proper transformation rules. In addition, it strengthens this interaction by direct contact with the data/vocabularies edited in the platform.
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Fiorelli, M., Lorenzetti, T., Pazienza, M.T., Stellato, A., Turbati, A. (2015). Sheet2RDF: a Flexible and Dynamic Spreadsheet Import&Lifting Framework for RDF. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_13
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DOI: https://doi.org/10.1007/978-3-319-19066-2_13
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