Knowledge Graph

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Virginia Tech


The knowledge graph project is a two-component project: the first component is concerned with the back end Grakn.AI while the second component deals with the front end service registration. The goal of the project is to build a knowledge graph that represents how user information goals are connected to one another. The knowledge graph is connected to a workflow management system that allows developers to register their services and add them to the knowledge graph.

A knowledge graph is a directed graph data model that stores interlinked entities. Storing data into the knowledge graph allows you to see how this data is connected with other entities in the graph as well as how they are connected. Through this we see the power of a fully fleshed-out knowledge graph. A user may wish to complete a task but has no knowledge about how to complete this task or the tools needed to do so. They can use the knowledge graph and query for this task and thus retrieve the workflow necessary to perform this task including the input files, output files, libraries, functions, and environments.

During this project, research was conducted on both the back end and the front end. On the back end, our team researched how to search through the knowledge graph with Grakn. The front end searched for a suitable method to visualize the knowledge graph. As a result, the Grakn database is able to query the knowledge graph and a Python API is connected to Grakn to allow the front end to display an update to date version of the knowledge graph.



Knowledge graph, Visualization, Grakn.AI, Grakn, Workflow