%0 Journal Article %J Semantic Web %D 2014 %T Five stars of Linked Data vocabulary use %A Krzysztof Janowicz %A Pascal Hitzler %A Benjamin Adams %A Dave Kolas %A Charles Vardeman %X 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. %B Semantic Web %V 5 %P 173–176 %G eng %U http://dx.doi.org/10.3233/SW-140135 %R 10.3233/SW-140135 %0 Conference Paper %B Spatial Information Theory - 11th International Conference, COSIT 2013, Scarborough, UK, September 2-6, 2013. Proceedings %D 2013 %T A Geo-ontology Design Pattern for Semantic Trajectories %A Yingjie Hu %A Krzysztof Janowicz %A David Carral %A Simon Scheider %A Werner Kuhn %A Gary Berg-Cross %A Pascal Hitzler %A Mike Dean %A Dave Kolas %K Ontology Design Pattern %K OWL %K Trajectory %X

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.

%B Spatial Information Theory - 11th International Conference, COSIT 2013, Scarborough, UK, September 2-6, 2013. Proceedings %P 438–456 %G eng %U http://dx.doi.org/10.1007/978-3-319-01790-7_24 %R 10.1007/978-3-319-01790-7_24 %0 Conference Paper %B Workshop on GIScience in the Big Data Age, In conjunction with the seventh International Conference on Geographic Information Science 2012 (GIScience 2012) %D 2012 %T Semantics and Ontologies for EarthCube %A Gary Berg-Cross %A Isabel Cruz %A Mike Dean %A Tim Finin %A Mark Gahegan %A Pascal Hitzler %A Hook Hua %A Krzysztof Janowicz %A Naicong Li %A Philip Murphy %A Bryce Nordgren %A Leo Obrst %A Mark Schildhauer %A Amit Sheth %A Krishna Sinha %A Anne Thessen %A Nancy Wiegand %A Ilya Zaslavsky %E Krzysztof Janowicz %E C. Kessler %E T. Kauppinen %E Dave Kolas %E Simon Scheider %X

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.

%B Workshop on GIScience in the Big Data Age, In conjunction with the seventh International Conference on Geographic Information Science 2012 (GIScience 2012) %C Columbus, Ohio, USA %G eng