In this feature on our blog, we answer questions from our GraphDB users. Today’s question is about GraphDB security.
Making Sense of Text and Data
Provide consistent unified access to data across different systems by using the flexible and semantically precise structure of the knowledge graph model
Interlink your organization’s data and content by using knowledge graph powered natural language processing with our Content Management solutions.
Implement a Connected Inventory of enterprise data assets, based on a knowledge graph, to get business insights about the current status and trends, risk and opportunities, based on a holistic interrelated view of all enterprise assets.
Quick and easy discovery in clinical trials, medical coding of patients’ records, advanced drug safety analytics, knowledge graph powered drug discovery, regulatory intelligence and many more
Make better sense of enterprise data and assets for competitive investment market intelligence, efficient connected inventory management, enhanced regulatory compliance and more
Connect and model industry systems and processes for deeper data-driven insights in:
Improve engagement, discoverability and personalized recommendations for Financial and Business Media, Market Intelligence and Investment Information Agencies, Science, Technology and Medicine Publishers, etc.
Unlock the potential for new intelligent public services and applications for Government, Defence Intelligence, etc.
Connect and improve the insights from your customer, product, delivery, and location data. Gain a deeper understanding of the relationships between products and your consumers’ intent.
Link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.
Organize your information and documents into enterprise knowledge graphs and make your data management and analytics work in synergy.
Integrate and evaluate any text analysis service on the market against your own ground truth data in a user friendly way.
Turn strings to things with Ontotext’s free application for automating the conversion of messy string data into a knowledge graph.
GraphDB Q&As
TESTED ON: GraphDB 9.9
Unless you are already running an “empty” ruleset repository, that’s the consequence of inference. The short explanation is that there are two types of inference – forward and backward chaining. Forward chaining starts at the data and infers all possible statements you can get. Backward chaining starts at the query and infers only the statements you can get given a particular query. Forward chaining happens at load time. Backward chaining happens at query time. This means that forward chaining has slower loads and faster queries, plus it is easier to manipulate the materialized triples. Backward chaining leads to fast loads and slower queries.
GraphDB is a forward chaining database. This means that all your statements are materialized during load time. The more statements there are, the harder it is to infer new data. This is why imports get slower over time.
If you want your import to go faster, you can always try to fine-tune the inference:
Remember that there’s always a trade off in inference. Sure, the data import may be going slower than expected but, in return, queries are consistently fast and you can easily access these inferred triples programmatically.
Did this help you solve your issue? Your opinion is important not only to us but also to your peers.
In this feature on our blog, we answer questions from our GraphDB users. Today’s question is about GraphDB security.
In this feature, we answer questions from our GraphDB users. Today's question is about the number of repos in GraphDB and accessing the data.
Learn how to choose the GraphDB edition most suited for your smart data prototypes.
In this feature on our blog, we answer questions from our GraphDB users. Today’s question is about GraphDB security.
In this feature, we answer questions from our GraphDB users. Today's question is about the number of repos in GraphDB and accessing the data.
Learn how to choose the GraphDB edition most suited for your smart data prototypes.
Ontotext answers questions from our GraphDB users. You can also check out the frequently asked questions on general topics about GraphDB. Or you can get quick answers on technical questions from the community as well as Ontotext experts using the graphdb tag on stack overflow.
In this blog, we answer questions from our GraphDB users. This question is about where can one deploy GraphDB and what are some best practices
In this blog, we answer questions from our GraphDB users. This question is about the the isolation levels GraphDB supports..
In this blog, we answer questions from our GraphDB users. This question is about the most important hardware attribute for optimizing GraphDB performance.
In this blog, we answer questions from our GraphDB users. This question is about the best way to store the triples’ history in the database
In this blog, we answer questions from our GraphDB users. This question is about using nested repositories to introduce logical separation to GraphDB
In this blog, we answer questions from our GraphDB users. This question is about fine-tuning securing on a GraphDB endpoint.
In this blog, we answer questions from our GraphDB users. This question is about the different ways to deploy GraphDB.
In this blog, we answer questions from our GraphDB users. This question is about the best ways to integrate JSON data in GraphDB.
In this feature, we answer questions from our GraphDB users. This question is about how about GraphDB security workds, especially for Automated APIs
In this feature, we answer questions from our GraphDB users. This question is about if Kafka is used only for exporting or importing data or we can use for both
In this feature, we answer questions from our GraphDB users. Today’s question is about how to change the configuration of connector if you’ve made a mistake when creating it
In this feature, we answer questions from our GraphDB users. Today’s question is about whether there are administration differences to operating a cluster in GraphDB 10
In this feature, we answer questions from our GraphDB users. Today’s question is if one can scale GraphDB.
In this feature, we answer questions from our GraphDB users. Today’s question is if one can change inference at runtime.
In this feature, we answer questions from our GraphDB users. Today’s question is about how to mark statements in a query as explicit or implicit.
In this feature, we answer questions from our GraphDB users. Today’s question is if one can use the standard Onotp configurations.
In this feature, we answer questions from our GraphDB users. Today’s question us whether to use a SPARQL Repository or a HTTP Repository.
In this feature, we answer questions from our GraphDB users. Today’s question is about the Log4j vulnerability for different versions of GraphDB.
In this feature, we answer questions from our GraphDB users. Today, we answer 12 very short question from GraphDB users.
In this feature, we answer questions from our GraphDB users. Today’s question is about GraphDB logs and how to monitor for problems.
In this feature, we answer questions from our GraphDB users. Today’s question is about how users can optimize their queries.
In this feature, we answer questions from our GraphDB users. Today’s question is about the difference between SPARQL and FedX federation.
In this feature, we answer questions from our GraphDB users. Today’s question is about what the “Insufficient Free Heap memory” error means.
In this feature, we answer questions from our GraphDB users. Today’s question is about how to optimize inference.
In this feature, we answer questions from our GraphDB users. Today’s question is about whether RDF-star is the best choice for reification.
In this feature, we answer questions from our GraphDB users. Today’s question is about if GraphDB’s inference works with virtualized repositories.
In this feature, we answer questions from our GraphDB users. Today’s question is about how SHACL works on GraphDB.
In this feature, we answer questions from our GraphDB users. Today’s question is about if GraphDB supports ABAC.
In this feature, we answer questions from our GraphDB users. Today’s question is about getting errors about GraphDB being “unable to find valid certification path to requested target”.
In this feature on our blog, we answer questions from our GraphDB users. Today’s question is about GraphDB security and access control.
In this feature on our blog, we answer questions from our GraphDB users. Today’s question is about GraphDB import speed.
In this feature on our blog, we answer questions from our GraphDB users. Today’s question is about GraphDB security.
In this feature, we answer questions from our GraphDB users. Today’s question is about the number of repos in GraphDB and accessing the data.