<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Benjamin Adams</style></author><author><style face="normal" font="default" size="100%">Dave Kolas</style></author><author><style face="normal" font="default" size="100%">Charles Vardeman</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Five stars of Linked Data vocabulary use</style></title><secondary-title><style face="normal" font="default" size="100%">Semantic Web</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.3233/SW-140135</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">173–176</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In 2010 Tim Berners-Lee introduced a 5 star rating to his Linked Data design issues page to encourage data publishers along the road to good Linked Data. What makes the star rating so effective is its simplicity, clarity, and a pinch of psychology – is your data 5 star? While there is an abundance of 5 star Linked Data available today, finding, querying, and integrating/interlinking these data is, to say the least, difficult. While the literature has largely focused on describing datasets, e.g., by adding provenance information, or interlinking them, e.g., by co-reference resolution tools, we would like to take Berners-Lee’s original proposal to the next level by introducing a 5 star rating for Linked Data vocabulary use.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yingjie Hu</style></author><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Simon Scheider</style></author><author><style face="normal" font="default" size="100%">Werner Kuhn</style></author><author><style face="normal" font="default" size="100%">Gary Berg-Cross</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Mike Dean</style></author><author><style face="normal" font="default" size="100%">Dave Kolas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Geo-ontology Design Pattern for Semantic Trajectories</style></title><secondary-title><style face="normal" font="default" size="100%">Spatial Information Theory - 11th International Conference, COSIT 2013, Scarborough, UK, September 2-6, 2013. Proceedings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Ontology Design Pattern</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Trajectory</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-01790-7_24</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">438–456</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Trajectory data have been used in a variety of studies, including human behavior analysis, transportation management, and wildlife tracking. While each study area introduces a different perspective, they share the need to integrate positioning data with domain-specific information. Semantic annotations are necessary to improve discovery, reuse, and integration of trajectory data from different sources. Consequently, it would be beneficial if the common structure encountered in trajectory data could be annotated based on a shared vocabulary, abstracting from domain-specific aspects. Ontology design patterns are an increasingly popular approach to define such flexible and self-contained building blocks of annotations. They appear more suitable for the annotation of interdisciplinary, multi-thematic, and multi-perspective data than the use of foundational and domain ontologies alone. In this paper, we introduce such an ontology design pattern for semantic trajectories. It was developed as a community effort across multiple disciplines and in a data-driven fashion. We discuss the formalization of the pattern using the Web Ontology Language (OWL) and apply the pattern to two different scenarios, personal travel and wildlife monitoring.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gary Berg-Cross</style></author><author><style face="normal" font="default" size="100%">Isabel Cruz</style></author><author><style face="normal" font="default" size="100%">Mike Dean</style></author><author><style face="normal" font="default" size="100%">Tim Finin</style></author><author><style face="normal" font="default" size="100%">Mark Gahegan</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Hook Hua</style></author><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author><author><style face="normal" font="default" size="100%">Naicong Li</style></author><author><style face="normal" font="default" size="100%">Philip Murphy</style></author><author><style face="normal" font="default" size="100%">Bryce Nordgren</style></author><author><style face="normal" font="default" size="100%">Leo Obrst</style></author><author><style face="normal" font="default" size="100%">Mark Schildhauer</style></author><author><style face="normal" font="default" size="100%">Amit Sheth</style></author><author><style face="normal" font="default" size="100%">Krishna Sinha</style></author><author><style face="normal" font="default" size="100%">Anne Thessen</style></author><author><style face="normal" font="default" size="100%">Nancy Wiegand</style></author><author><style face="normal" font="default" size="100%">Ilya Zaslavsky</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author><author><style face="normal" font="default" size="100%">C. Kessler</style></author><author><style face="normal" font="default" size="100%">T. Kauppinen</style></author><author><style face="normal" font="default" size="100%">Dave Kolas</style></author><author><style face="normal" font="default" size="100%">Simon Scheider</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Semantics and Ontologies for EarthCube</style></title><secondary-title><style face="normal" font="default" size="100%">Workshop on GIScience in the Big Data Age, In conjunction with the seventh International Conference on Geographic Information Science 2012 (GIScience 2012)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><pub-location><style face="normal" font="default" size="100%">Columbus, Ohio, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Semantic technologies and ontologies play an increasing role in scientific workflow systems and knowledge infrastructures. While ontologies are mostly used for the semantic annotation of metadata, semantic technologies enable searching metadata catalogs beyond simple keywords, with some early evidence of semantics used for data translation. However, the next generation of distributed and interdisciplinary knowledge infrastructures will require capabilities beyond simple subsumption reasoning over subclass relations. In this work, we report from the EarthCube Semantics Community by highlighting which role semantics and ontologies should play in the EarthCube knowledge infrastructure. We target the interested domain scientist and, thus, introduce the value proposition of semantic technologies in a non-technical language. Finally, we commit ourselves to some guiding principles for the successful implementation and application of semantic technologies and ontologies within EarthCube.&lt;/p&gt;
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