Dynamic Linked Open Data

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Team: Pablo N. Mendes, Pavan Kapanipathi, Delroy Cameron

In this work we approach relationships on the Linked Open Data Web as key facilitators of information exploration. Linked Open Data (LOD) principles contribute to a shift in paradigm for information representation and access, enhancing the ability of users and computers to connect, browse and query data on the Web through standard languages and protocols.

Linked Open Data principles are an important advancement towards a global space of associated data, leading users from one piece of relevant information to the next. There is a need, however, for relationships representing more dynamic information that may change with topic, time, location and social context.

In this project we discuss the real time processing of microblog posts for the extraction of associative relationships for on demand enrichment of the LOD cloud, increasing connectivity with contextually relevant, trending information. We present two applications, demonstrating the usefulness of trending socially contextual relationships for browsing relational databases and performing exploratory search tasks on the Web.

See also our paper at WebSci2010: <a href=http://journal.webscience.org/398/>Dynamic Associative Relationships on the Linked Open Data Web</a>


  • Slides:


For project members: Dynamic LOD Project Page