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.

Modelling and linking company data in the EubusinessGraph platform / A. Maurino, S. Mauricio, A. Rula, B. Elvesaeter, B.M. Von Zernichow, D. Roman - In: DSMM'19: Proceedings[s.l] : ACM, 2019. - ISBN 978-1-4503-6823-0. - pp. 1-6 (( Intervento presentato al 5. convegno DSMM tenutosi a Amsterdam nel 2019 [10.1145/3336499.3338012].

Modelling and linking company data in the EubusinessGraph platform

S. Mauricio;
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.
Company data; Entity Matching; RDF; Record Linkage
Settore INFO-01/A - Informatica
2019
ACM Special Interest Group on Management of Data (SIGMOD)
Book Part (author)
File in questo prodotto:
File Dimensione Formato  
a12-final.pdf

accesso riservato

Tipologia: Publisher's version/PDF
Dimensione 1.18 MB
Formato Adobe PDF
1.18 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1121820
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 1
  • OpenAlex ND
social impact