Learning from visualizing and Interacting with the Semantic Web Dog Food

Abstract

International audienceSemantic Web conferences such as WWW and ISWC fos- tered a collaborative e ort for the leveraging of Linked Data about con- ferences people, papers and talks. This e ort gave birth to the Semantic Web Conference Corpus, a.k.a. the Semantic Web Dog Food Corpus. Many other conferences and journals contributed afterwards to this cor- pus, so that it is today a representative semantic data archive about our research community activities and progression. These metadata are con- sistent with Linked Data principles and therefore can be semantically processed by the machine. Although it is a matchless source of scienti c knowledge for our community, it is di cult for the researcher, as a hu- man, to browse this corpus that contains more than 180k unique triples. This paper presents our e ort to bring a user-friendly Web application based on the Semantic Web Dog Food corpus that show the topics trends in Semantic Web research. The application was made freely available to the researcher as an end user. In this work we identify speci c issues and barriers encountered when building the system, discuss how these were approached in this software, and how the lessons learnt can drive future implementations fostering the Web of Data