Dockerizing Linked Data: Knowledge Base Shipping to the Linked Open Data Cloud

Popular knowledge bases that provide SPARQL endpoints for the web are usually experiencing a high number of requests, which often results in low availability of their interfaces. A common approach to counter the availability issue is to run a local mirror of the knowledge base. Running a SPARQL endpoint is currently a complex task which requires a lot of effort and technical support for domain experts who just want to use the SPARQL interface. With our approach of containerised knowledge base shipping we are introducing a simple to setup methodology for running a local mirror of an RDF knowledge base and SPARQL endpoint with interchangeable exploration components. The flexibility of the presented approach further helps maintaining the publication infrastructure for dataset projects. Popular knowledge bases that provide SPARQL endpoints for the web are usually experiencing a high number of requests, which often results in low availability of their interfaces. A common approach to counter the availability issue is to run a local mirror of the knowledge base. Running a SPARQL endpoint is currently a complex task which requires a lot of effort and technical support for domain experts who just want to use the SPARQL interface. With our approach of containerised knowledge base shipping we are introducing a simple to setup methodology for running a local mirror of an RDF knowledge base and SPARQL endpoint with interchangeable exploration components. The flexibility of the presented approach further helps maintaining the publication infrastructure for dataset projects.

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SML-Bench 0.2 Released ( 2017-05-11T13:01:45+02:00 by Patrick Westphal)

2017-05-11T13:01:45+02:00 by Patrick Westphal

Dear all, we are happy to announce the 0.2 release of SML-Bench, our Structured Machine Learning benchmark framework. SML-Bench provides full benchmarking scenarios for inductive supervised machine learning covering different knowledge representation languages like OWL and Prolog. Read more about "SML-Bench 0.2 Released"

AKSW Colloquium, 08.05.2017, Scalable RDF Graph Pattern Matching ( 2017-05-08T09:42:49+02:00 by Lorenz Bühmann)

2017-05-08T09:42:49+02:00 by Lorenz Bühmann

At the AKSW Colloquium, on Monday 8th of May 2017, 3 PM, Lorenz Bühmann will discuss a paper titled “Type-based Semantic Optimization for Scalable RDF Graph Pattern Matching” of Kim et al. Read more about "AKSW Colloquium, 08.05.2017, Scalable RDF Graph Pattern Matching"

ESWC 2017 accepted two Demo Papers by AKSW members ( 2017-04-19T10:19:43+02:00 Christopher Schulz)

2017-04-19T10:19:43+02:00 Christopher Schulz

Hello Community! The 14th ESWC, which takes place from May 28th to June 1st 2017 in Portoroz, Slovenia, accepted two demos to be presented at the conference. Read more about them in the following:                                                                         1. Read more about "ESWC 2017 accepted two Demo Papers by AKSW members"

AKSW Colloquium, 10.04.2017, GeoSPARQL on geospatial databases ( 2017-04-07T10:43:55+02:00 by Dr. Matthias Wauer)

2017-04-07T10:43:55+02:00 by Dr. Matthias Wauer

At the AKSW Colloquium, on Monday 10th of April 2017, 3 PM, Matthias Wauer will discuss a paper titled “Ontop of Geospatial Databases“. Read more about "AKSW Colloquium, 10.04.2017, GeoSPARQL on geospatial databases"

AKSW Colloquium, 03.04.2017, RDF Rule Mining ( 2017-03-31T13:39:28+02:00 TommasoSoru)

2017-03-31T13:39:28+02:00 TommasoSoru

At the AKSW Colloquium, on Monday 3rd of April 2017, 3 PM, Tommaso Soru will present the state of his ongoing research titled “Efficient Rule Mining on RDF Data”, where he will introduce Horn Concerto, a novel scalable SPARQL-based approach … Continue reading → Read more about "AKSW Colloquium, 03.04.2017, RDF Rule Mining"