Using the Past to Explain the Present: Interlinking Current Affairs with Archives via the Semantic Web

The BBC has a very large archive of programmes, covering a wide range of topics. This archive holds a significant part of the BBC's institutional memory and is an important part of the cultural history of the United Kingdom and the rest of the world. These programmes, or parts of them, can help provide valuable context and background for current news events. However the BBC's archive catalogue is not a complete record of everything that was ever broadcast. For example, it excludes the BBC World Service, which has been broadcasting since 1932. This makes the discovery of content within these parts of the archive very difficult. In this paper we describe a system based on Semantic Web technologies which helps us to quickly locate content related to current news events within those parts of the BBC's archive with little or no pre-existing metadata. This system is driven by automated interlinking of archive content with the Semantic Web, user validations of the resulting data and topic extraction from live BBC News subtitles. The resulting interlinks between live news subtitles and the BBC's archive are used in a dynamic visualisation enabling users to quickly locate relevant content. This content can then be used by journalists and editors to provide historical context, background information and supporting content around current affairs.