Cross-language Semantic Matching for Discovering Links to e-gov Services in the LOD Cloud

The large diffusion of e-gov initiatives is increasing the attention of public administrations towards the Open Data initiative. The adoption of open data in the e-gov domain produces different advantages in terms of more transparent government, development of better public services, economic growth and social value. However, the process of data opening should adopt standards and open formats. Only in this way it is possible to share experiences with other service providers, to exploit best practices from other cities or countries, and to be easily connected to the Linked Open Data (LOD) cloud. In this paper we present CroSeR (Cross-language Service Retriever), a tool able to match and retrieve cross-language e-gov services stored in the LOD cloud. The main goal of this work is to help public administrations to connect their e-gov services to services, provided by other administrations, already connected to the LOD cloud. We adopted a Wikipedia-based semantic representation in order to overcome the problems related to match really short textual descriptions associated to the services. A preliminary evaluation on an open catalog of e-gov services showed that the adopted techniques are promising and are more effective than techniques based only on keyword representation.