Holistic Benchmarking of Big Linked Data
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HOBBIT aims at abolishing the barriers in the adoption and deployment of Big Linked Data by European companies, by means of open benchmarking reports that allow them to assess the fitness of existing solutions for their purposes. These benchmarks are based on data that reflects reality and measures industry-relevant Key Performance Indicators (KPIs) with comparable results using standardized hardware.
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linked data
benchmarking
projecthobbit
semantic web
h2020 project
big data
benchmark
rdf
hobbit
link discovery
blink
iswc2016
challenge
eswc2016
sparql
graph-ta
h2020
enchmarking
memory management
large-scale link discovery
tutorial
query processing
eswc 2016
instance matching
benchmarks
question answering
streaming systems
scalable link discovery
spatial link discovery
ontology matching
ekaw
ecai2016
edf2016
algorithms
allen relations
data responsibility
diversity
discrimination
fairness
owl
query optimization
archiving
versioning
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