In the business environment, knowledge of company data is essential for a variety of tasks. The European funded project euBusinessGraph enables the establishment of a company data platform where data providers and consumers can publish and access company data. The core of the platform is the semantic data model that is the conceptual representation of company data in a common way so that it is easier to share and interlink company data. In this paper we show how the unified model and Grafterizer, a tool for manipulating and transforming raw data into Linked Data, support the linking challenge proposed in FEIII 2019. Results show that geographical enrichment of RDF data supports the interlinking process between company entities in different datasets.
Maurino, A., Gomez, M., Rula, A., Elvesaeter, B., Von Zernichow, B., Roman, D. (2019). Modelling and linking company data in the EubusinessGraph platform. In Proceedings of the 5th International Workshop on Data Science for Macro-Modeling, DSMM 2019, in conjunction with the ACM SIGMOD/PODS Conference (pp.1-6). Association for Computing Machinery, Inc [10.1145/3336499.3338012].
Modelling and linking company data in the EubusinessGraph platform
Maurino, A;Rula, A;
2019
Abstract
In the business environment, knowledge of company data is essential for a variety of tasks. The European funded project euBusinessGraph enables the establishment of a company data platform where data providers and consumers can publish and access company data. The core of the platform is the semantic data model that is the conceptual representation of company data in a common way so that it is easier to share and interlink company data. In this paper we show how the unified model and Grafterizer, a tool for manipulating and transforming raw data into Linked Data, support the linking challenge proposed in FEIII 2019. Results show that geographical enrichment of RDF data supports the interlinking process between company entities in different datasets.
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