triplestore | Nifty library to manage , query and store RDF triples | Parser library

I'm trying to load some basic json-ld content as a string, but I'm not able to see the namespace prefixes that should be included.

Given the following json-ld:

When I import the dump "PathwayCommons12.All.BIOPAX.owl.gz" (linked from this page) of this Virtuoso triplestore, I've noticed that there are "#"s inserted after the prefix of various URIs.

In particular, the following query runs on the original endpoint:

I'm coming from the RDF world where named graphs are persistent and can be used like a collection of triples. Moreover you can query against one single named graph or over the whole triplestore. I'm looking for the same features (or a workaround to achive them) in Neo4j.

Neo4j's Graph Catalog is well documented. As I understood, named graphs in Neo4j are stored entirely in-memory (so lost after a restart) with a subset of nodes you define for analytic purpose.

Is there a way to create persistents named graphs in Neo4j? A graph that is stored in the disk with the data and that permits to fast access to a subset of nodes (nodes can be added or removed from the named graph).

I am cloning a large public triplestore for local development of a client app.

The data is too large to fit on the ssd partition where /data lives. How can I create a new repository at a different location to host this data?

I'm trying to use SPARQL to query literals that have regexes with balanced parentheses. So "( (1) ((2)) (((3))) 4)" should be returned, but "( (1) ((2)) (((3)) 4)", where I removed a closing parenthesis after the "3", should not be returned.

I've previously looked here for a suitable regex: Regular expression to match balanced parentheses

And have been trying to implement regex suggested by rogal111, which is as follows:

I am new to using Blazegraph and am have been developing with it locally as part of a project over the past few months. I am currently trying to host an instance of my triple store online and have got to the point where I am lost going around in circles.

My application uses a spring-boot API to manage any interactions with the triplestore. I originally used docker-compose to host both on my local machine and was able to query and update the triplestore with no problem. This is the docker-compose.yml file I used:

I have the following RDF data in my Fuseki triplestore.

Despite the number of questions/answers on the subject, I'm stil having trouble to configure Apache Jena Fuseki...

I'm trying to configure an Apache Jena Fuseki instance with TDB and OWL reasoner activated, for testing my application. I need to create a dataset, execute my tests, and delete the dataset programatically.

I use stain/jena-fuseki docker image to run Apache Jena Fuseki.

I run Jena Fuseki in version 3.10.0.

I am trying to use Dgraph as my primary database. I have a simple system that has two domain entities viz. User and Product. They both have certain properties represented as edges/attributes in Dgraph. They both have a common property name which is a string. If I use the same predicate name for both the nodes then it creates a problem when I am using a has function to find all the users with a name edge. The has function also returns Product nodes with name edge. This is not desirable.

In this situation, what is the right approach or recommendation when modeling the domain entities? I can think of two approaches:

1. Have a common edge type for all the nodes to uniquely identify similar nodes. Here the value of type would be User or Product. This is approximately similar to a traditional table/column analogy where type represents the table and edges as columns with a context localized to type property.
2. Have a separate predicate for each node type. So, instead of having name, prefer two predicates like user_name and product_name.

I believe this problem only exists for RDF/Triplestore databases like Dgraph and not for property graphs like Neo4j since each node contains its own properties.