Guillermo Palma

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Linked Open Data has made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms (CV terms) from ontologies. These semantic annotations encode scientific knowledge which is captured in annotation datasets. One can mine these datasets to discover relationships and patterns(More)
We present GRAPHIUM a tool to visualize trends and patterns in the performance of existing graph and RDF engines. We will demonstrate GRAPHIUM and attendees will be able to observe and analyze the performance exhibited by Neo4j, DEX, HypergraphDB and RDF-3x when core graph-based and mining tasks are run against a variety of benchmarks of graphs of diverse(More)
The optical absorption coefficient, particulate matter with an aerodynamic diameter <2.5 microm, and elemental carbon (EC) have been measured simultaneously during winter and spring of 2000 in the western part of Santiago, Chile (Pudahuel district). The optical measurements were carried out with a low-cost instrument recently developed at the University of(More)
The ability to integrate a wealth of human-curated knowledge from scientific datasets and ontologies can benefit drug-target interaction prediction. The hypothesis is that similar drugs interact with the same targets, and similar targets interact with the same drugs. The similarities between drugs reflect a chemical semantic space, while similarities(More)
Annotation graph datasets are a natural representation of scientific knowledge. They are common in the life sciences where concepts such as genes and proteins are annotated with controlled vocabulary terms from ontologies. Scientists are interested in analyzing or mining these annotations, in synergy with the literature, to discover patterns. Further,(More)
Linked data can be represented as graphs, and core graph-based tasks are required not only for consuming linked data, but also for mining associations and patterns among data and links. To facilitate these tasks, efficient algorithms have been defined; additionally, graph database engines that manage, store and query large graphs have been implemented.(More)