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Architecture of Linked Data Applications
(CRC Press (Taylor & Francis), 2014)
In this chapter, we first perform an empirical survey of RDF-based applications over most of the past decade, from 2003 to 2009. As the Linked Data principles where introduced in 2006, this allows us to describe the current ...
Linked Biomedical Dataspace: Lessons Learned integrating Data for Drug Discovery
The increase in the volume and heterogeneity of biomedical data sources has motivated researchers to embrace Linked Data (LD) technologies to solve the ensuing integration challenges and enhance information discovery. As ...
GenomeSnip: Fragmenting the Genomic Wheel to augment discovery in cancer research
Cancer genomics researchers have greatly benefited from high-throughput technologies for the characterization of genomic alterations in patients. These voluminous genomics datasets when supplemented with the appropriate ...
A Roadmap for navigating the Life Sciences Linked Open Data Cloud
Multiple datasets that add high value to biomedical research have been exposed on the web as a part of the Life Sciences Linked Open Data (LSLOD) Cloud. The ability to easily navigate through these datasets is crucial for ...
SemStim at the Linked Open Data-enabled Recommender Systems 2014 challenge
SemStim is a graph-based recommendation algorithm which is based on Spreading Activation and adds targeted activation and duration constraints. SemStim is not affected by data sparsity, the cold-start problem or data quality ...