Markov Logic Networks (MLNs) is a powerful framework that combines statistical and logical reasoning; they have been applied to many data intensive problems including information extraction, entity resolution, text mining, and natural language processing. Based on principled data management techniques, Tuffy is an MLN inference engine that achieves scalability and orders of magnitude speedup compared to prior art implementations. It is written in Java and relies on PostgreSQL. For a brief introduction to MLNs and the technical details of Tuffy, please see our technical report.
Tupelo is a data and metadata management system based on semantic web technologies. Tupelo provides a variety of generic utilities for managing data and metadata using both best-of-breed semantic database implementations such as Jena and Sesame, as well as ordinary storage technologies such as flat files. Tupelo makes data and metadata portable across a variety of Contexts and deployment scenarios, including desktop applications, web-based applications, and more complex distributed architectures. Its use of global identification and explicit semantics means that metadata created and managed with Tupelo can be easily exported and used by a wide variety of RDF-aware tools and technologies.
The Fresnel Vocabulary for RDF provides a way to write down a set of instructions for transforming RDF statements into HTML for display. For some time, the ORDF library has included two implementations of Fresnel, one in JavaScript and one in Python. Recently added is a command line tool, simply called fresnel, for rendering HTML documents given a lens and an RDF graph.
Developed by the Lawrence Livermore National Laboratory, VisIt contains a rich set of visualization methods—such as contour plots, pseudocolor plots, volume plots, vector plots, and boundary plots—for visualizing scientific data. VisIt allows the ability to provide quantitative as well as qualitative information from a scientific data set.
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