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Tag Archives: SPARQL

Knowledge Graphs and Natural Language Processing. The Year of the Graph Newsletter, July/August 2019

Pinterest gets with the knowledge graph program. Facebook releases a new dataset for conversational Reasoning over Knowledge Graphs. Connected Data London announces its own program, rich in leaders and innovators. And as always, new knowledge graph and graph database releases, research, use cases, and definitions. A double bill summertime newsletter edition, making your knowledge graph […]

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Knowledge graphs, AI, and interoperability. The Year of the Graph Newsletter: February 2019

Knowledge graphs are spreading everywhere: from Airbnb and eBay to Alexa, and from using JSON-LD on the web for better SEO to leveraging taxonomy to define AI. Combining knowledge graphs and machine learning, benchmarking graph databases, and W3C initiative for interoperability shaping up. January 2019 has been a lively month in the graph landscape. A […]

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In Between Years. The Year of the Graph Newsletter: January 2019

In between years, or zwischen den Jahren, is a German expression for the period between Christmas and New Year. This is traditionally a time of year when not much happens, and this playful expression lingers itself in between the literal and the metaphoric. As the first edition of the Year of the Graph newsletter for […]

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The Year of the Graph Newsletter: September 2018

Knowledge graphs in Gartner’s hype cycle, machine learning extensions and visual tools for graph databases, Ethereum analytics with RDF, Using Gremlin with R, SPARQL, and Spring, graph database research wins best paper award in VLDB, and benchmarking AWS Neptune. Not bad for a typical summer vacation month such as August. This edition of the Year […]

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The Year of the Graph Newsletter: May 2018

  New releases, algorithms, and visualization. April has been an interesting month in the graph database world. We saw 2 minor and one major graph database versions come out, namely GraphDB 8.5, Neo4j 3.4 and DSE Graph 6.0. Each of these brings interesting new features and reshapes the landscape a little bit. We saw more […]

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RDF on Hadoop and Schema on Read vs. Schema on Write

One of the challenges for any Big Data solution is dealing with scale, and RDF stores are no exception: going for billions of RDF triples (the equivalent of rows in the SQL world) is not trivial. Hadoop on the other hand is great at scaling out on commodity hardware, which is a feature every MPP […]

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SPARQL City and Benchmarks

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We have written in the past about SPARQL, Hadoop and benchmarks. In this post, we take a look at a company that combines all of these subjects, SPARQL City, on the occasion of the results they released after subjecting their product, SPARQLVerse, to the SP2 benchmark. This year’s NoSQLNow conference was colocated with SemTechBiz, providing […]

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On APIs, JSON, Linked Data, attitude and opportunities

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I’ve been meaning to revisit some of the things i’ve been writing about and getting feedback on lately – APIs, the JSON vs. XML “non” debate and Linked Data. My focus was going to be on JSON-LD as the low-hanging fruit of Linked Data, and this week some news came out that gave me the […]

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Data modeling for APIs. Part 4: Linked Data and SPARQL

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Part 1: Seting the stage | Part 2: REST and JSON | Part 3: SOAP and XML | Part 4: Linked Data and SPARQL | Part 5: Modeling vs. Meta-Modeling In the 4th part of this series of posts we look at a different way of data modeling for APIs, one that is based on […]

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