Large-scale, algorithmic access to LOD Cloud data has been hampered by the absence of queryable endpoints for many datasets, a plethora of serialization formats, and an abundance of idiosyncrasies such as syntax errors. As of late, very large-scale — hundreds of thousands of document, tens of billions of triples — access to RDF data has become possible thanks to the LOD Laundromat Web Service. In this paper we showcase Frank, a command-line interface to a very large collection of standards-compliant, real-world RDF data that can be used to run Semantic Web experiments and stress-test Linked Data applications
In this position paper, we argue that the Linked Open Data (LoD) Cloud, in its current form, is only...
Numerous digital humanities projects maintain their data collections in the form of text, images, an...
Many data scientists make use of Linked Open Data (LOD) as a huge interconnected knowledge base repr...
Large-scale, algorithmic access to LOD Cloud data has been hampered by the absence of queryable endp...
Ad-hoc querying is crucial to access information from Linked Data, yet publishing queryable RDF data...
Ad-hoc querying is crucial to access information from Linked Data, yet publishing queryable RDF data...
LOD-a-lot democratizes access to the Linked Open Data (LOD) Cloud by serving more than 28 billion un...
Abstract. Linking Open Data (LOD) facilitates the emergence of a web of linked data by publishing an...
The LOD Laundromat provides access to a large subset of Linked Open Data (LOD) that is published in ...
LOD-a-lot democratizes access to the Linked Open Data (LOD) Cloud by serving more than 28 billion un...
The Linked Open Data (LOD) Cloud has more than tripled its sources in just three years (from 295 sou...
This paper introduces the LOD Laundromat meta-dataset, a continuously updated RDF meta-dataset that ...
LOD Laundromat poses a centralized solution for today's Semantic Web problems. This approach adheres...
The Linked Open Data (LOD) cloud has been around since 2007. Throughout the years, this prominent de...
Contemporary Semantic Web research is in the business of optimizing algorithms for only a handful of...
In this position paper, we argue that the Linked Open Data (LoD) Cloud, in its current form, is only...
Numerous digital humanities projects maintain their data collections in the form of text, images, an...
Many data scientists make use of Linked Open Data (LOD) as a huge interconnected knowledge base repr...
Large-scale, algorithmic access to LOD Cloud data has been hampered by the absence of queryable endp...
Ad-hoc querying is crucial to access information from Linked Data, yet publishing queryable RDF data...
Ad-hoc querying is crucial to access information from Linked Data, yet publishing queryable RDF data...
LOD-a-lot democratizes access to the Linked Open Data (LOD) Cloud by serving more than 28 billion un...
Abstract. Linking Open Data (LOD) facilitates the emergence of a web of linked data by publishing an...
The LOD Laundromat provides access to a large subset of Linked Open Data (LOD) that is published in ...
LOD-a-lot democratizes access to the Linked Open Data (LOD) Cloud by serving more than 28 billion un...
The Linked Open Data (LOD) Cloud has more than tripled its sources in just three years (from 295 sou...
This paper introduces the LOD Laundromat meta-dataset, a continuously updated RDF meta-dataset that ...
LOD Laundromat poses a centralized solution for today's Semantic Web problems. This approach adheres...
The Linked Open Data (LOD) cloud has been around since 2007. Throughout the years, this prominent de...
Contemporary Semantic Web research is in the business of optimizing algorithms for only a handful of...
In this position paper, we argue that the Linked Open Data (LoD) Cloud, in its current form, is only...
Numerous digital humanities projects maintain their data collections in the form of text, images, an...
Many data scientists make use of Linked Open Data (LOD) as a huge interconnected knowledge base repr...