<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">K. Jacobson</style></author><author><style face="normal" font="default" size="100%">M. Sandler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Interacting With Linked Data About Music</style></title><secondary-title><style face="normal" font="default" size="100%">Web Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">17/03/2009</style></date></pub-dates></dates><edition><style face="normal" font="default" size="100%">1</style></edition><publisher><style face="normal" font="default" size="100%">WSRI</style></publisher><pub-location><style face="normal" font="default" size="100%">Athens, Greece</style></pub-location><volume><style face="normal" font="default" size="100%">1</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">{In an effort to move towards intuitive visual interfaces for faceted browsing of structured data about music, we develop a visualization technique called k-pie}. Derived from a network visualization technique know as $k$-cores decomposition, k-pie layout accounts for the semantic labels or `colors' associated with each vertex. Vertices of a graph are arranged in a 2 dimensional circle where `slices' in the circle correspond to a specific vertex label and the most connected vertices are found in the center of the visualization. We describe the k-pie algorithm and demonstrate how it can be useful in the context of Semantic Web technologies.</style></abstract></record></records></xml>