ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.
ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.
Designing and refining ontologies becomes a tedious task, once the boundary to real-world-size knowledge bases has been crossed. Hence semi-automatic methods supporting those tasks will determine the future success of ontologies in practice. Our research therefore aims at the conceptual development and implementation of tools for semi-automatic ontology engineering. By combining Ontology Learning and Relational Exploration we hope to overcome the knowledge acquisition bottleneck, especially with respect to expressive axiomatizations (see our seminal paper at ICCS'2007). The RELExO framework supporting the refinement and evaluation of OWL DL ontologies is open source and publicly available under the LGPL license.
Let's explore how the lower cognitive cost of tagging makes it popular...From my first encounter with tagging (on systems such as del.icio.us & flickr), I could feel how easy it was to tag. But it took me a while to understand the cognitive processes at w
Let's explore how the lower cognitive cost of tagging makes it popular...From my first encounter with tagging (on systems such as del.icio.us & flickr), I could feel how easy it was to tag. But it took me a while to understand the cognitive processes at w
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