LOD-GF: An Integral Linked Open Data Generation Framework

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Abstract

Linked Open Data (LOD) generation is a common activity within organizations due to its advantages for sharing and reusing information. Since these technologies require specialized knowledge, the development of technological and methodological tools that allows its implementation is limited. Most of the current solutions are built on top of specific tools which require considerable effort to consolidate into an integral solution. Moreover, those tools work on specific domains, or they do not support some of the phases required for LOD life cycle (e.g., data cleaning, data exploitation). In this paper, we present a framework for LOD management which follows methodological principles presented in the state of the art in scientific literature and provides an unified software tool for publishing LOD for multiple domains and technologies. Our platform leverages a modular ETL processor, allowing a transparent and flexible integration, providing an integral environment for LOD. This framework was tested, successfully, using data sources from different domains, e.g., digital repositories, libraries.

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Saquicela, V., Segarra, J., Ortiz, J., Tello, A., Espinoza, M., Lupercio, L., & Villazón-Terrazas, B. (2019). LOD-GF: An Integral Linked Open Data Generation Framework. In Advances in Intelligent Systems and Computing (Vol. 884, pp. 283–300). Springer Verlag. https://doi.org/10.1007/978-3-030-02828-2_21

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