![]() ![]() There’s model mapping capabilities, essentially it allows you to map your Neo4j graph to an existing public vocabulary and expose your data according to that vocabulary. These are the two main points – import and export. Essentially, Neo4j says that you’re free to use the storage that you like and RDF is this layer on top that simplifies and enables interoperability between applications through the standard format. It’s a model for data exchange and that’s how we use it. I’d like to emphasize the idea that we see Neo4j as the mechanism to publish and import data, as defined by the W3C. These are the two main capabilities of the NSMNTX extension and it’s where it all started. That’s what I mean by a lossless import/export of data. We store that graph in a way that it is able to be regenerated back again as RDF without loss of any single triple. In a little bit, we will see how that happens because that’s what Neo4j is. We store the RDF data as a property graph. It’s important that we do so in a lossless manner. Any kind of RDF data is able to be imported with NSMNTX into Neo4j. You are able to import RDF data, this RDF data could come from services that expose the results as RDF, it could be datasets that exist that are published as RDF or it could be your own files. They’re graphs, so they should be straightforward. ![]() One of the things that we’ll be able to do with RDF through NSMNTX is be able to import RDF data into Neo4j. What’s interesting is that RDF, being a different model, has the same underlying abstraction of the world. Effectively, when you combine triples, you’re forming a graph. RDF uses the notion of triples and that’s how it represents the world.Ī triple is a subject connected to an object through a predicate. What’s interesting is that RDF represents models of the world in terms of connected entities. RDF offers a number of serialization formats that we’ll be looking at. RDF is a standard model for data exchange on the web. I’ll be talking about this extension plugin for Neo4j that will help you work with RDF data, linked data and do some quite interesting things. I’m going to be presenting Neosemantics, NSMNTX. Finally, users can clone subgraphs from one Neo4j instance to another. It also includes inferencing which is being able to define as data explicit descriptions or explicit behaviors that you want a general purpose engine to run. importOntology which will take the ontology from wherever it lives and it will import it. Other features include ontology management and publishing ontologies within your graph. NSMNTX is not just about importing and exporting data. Additionally, users can also run Cypher on the database. We run a series of commands, produce a serialization and export the graph as RDF. The import and export process for RDF data into and out of Neo4j is exactly the same. Because they are both graphs the transition is straightforward. With NSMNTX, users will be able to import RDF data into Neo4j. As such, RDF offers a number of serialization formats.Įven though RDF is a different model it still has the same underlying abstraction of the world, and sees the world as a graph. RDF is a standard defined by W3C and is a standard model for data exchange on the web. Starting off, Barrasa discusses different types of data. NSMNTX is an extension plugin for Neo4j built to help users work with RDF and linked data. Jesús Barrasa, Neo4j Sales Engineering Director, presents Neosemantics, NSMNTX. Please note that this talk covers the previous version of neosemantics, the current version has a lot of new features and capabilities, please check out the documentation and videos on the neosemantics Neo4j Labs page. Editor’s Note: This presentation was given by Jesús Barrasa at NODES 2019. ![]()
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