PoolParty GraphEditorKnowledge Graph Management for DATA SCIENTISTS & Subject Matter Experts
Why PoolParty GraphEditor?
The PoolParty GraphEditor allows data scientists and domain experts build and manage data graphs. It seamlessly integrates into the PoolParty interface on a project level. This way you can easily connect and manage data from several graph databases like Stardog, MarkLogic and RDF4J. The PoolParty GraphEditor’s collaborative and flexible interface allows you to edit specific parts of a knowledge graph with ease. A visual query editor also allows for knowledge graph exploration based on customisable views.
Examples of GraphEditor Uses
Large pharmaceutical companies draw upon GraphEditor for tracking down data inconsistencies and fix it manually.
Major financial institutions integrate and explore their data with assisted SPARQL queries supported by PoolParty GraphEditor.
Video game companies model their data in RDF based on industry ontologies thank GraphEditor.
Consulting companies make use of a variety of existing vocabularies since GraphEditor especially supports heterogeneous graph data landscapes.
Main Features of PoolParty GraphEditor
Knowledge Graph Management along the entire Linked Data Lifecycle
Create and edit data based on any ontology. GraphEditor is an entirely new addition to PoolParty, and complements its taxonomy and ontology management capabilities. A state-of-the-art editor that supports knowledge engineering capabilities along the entire linked data lifecycle.
Virtual Assistant for Creating GraphEditors
PoolParty GraphEditor offers a user-friendly virtual assistant that facilitates the creation of new GraphEditors. Specify basic metadata, URI generation patterns, ontologies and the graph database you want to use with a couple of clicks.
Combining Data from Multiple Graph Databases on a large scale
Connect and manage data from several graph databases. A remote storage architecture allows you to store all data created in PoolParty in various graph databases. This functionality offers the ability to work on large data lakes in a highly structured manner. By that, it also provides support for high availability and scalability scenarios.
Bulk and Inline Editing
Use GraphEditor inline editing feature to work on RDF Graphs in-place and see results immediately. Also, you can edit multiple data points at once, such as adding or removing data or deleting the selected resources.