This guide will help you get started with the basics, such as using dashboards, uploading data and creating relationships
Get started with the basic functionality of KgBase.
In this lesson we'll learn how to create your first KgBase project and import data with 500 best music albums from CSV file.
In this lesson, you'll learn how to convert a flat file into graph by extracting relationships. You will also become familiar with the Graph interface of KgBase.
So far we've imported our music albums file, and converted the "Genre" column into a relationship. Before we move on to graph functionality, let's learn how to do basic analysis of a flat file.
In this lesson, you will learn how to see different aspects of your graph with our features.
Complex queries enable you to have fine grained control over the subgraph that gets visualized.
Draw your graph from scratch by creating nodes and building relationships with our "Edit Mode" feature.
In this tutorial, you'll learn how to do basic multiple linear regression with tables in your KgBase project. This feature lets you specify one or multiple input variables (predictor variables) and a single output variable (outcome variable.)
In this tutorial, you'll learn how to compute statistics such as PageRank and Network Diameter for your KgBase graph.
When you first log in, you get access to a series of dashboards. Public dashboards are knowledge graphs that are created by other users that you can access. You can also access your own projects that you have saved previously.
Click on the “Data” tab to take you to the table section. In order to create your table, import a CSV file of your data by clicking on the “gear button” on the top right corner of the dashboard.
Before getting to the graph view, you must first choose what you want to view on the graph. For example, if you want to see the relationship between two columns, convert one column into its own table by clicking the top three dots on the column.
If you're creating a knowledge graph with many tables, you may want to add descriptions to tables, to make sure users understand what is included in each table. The descriptions will show up in the sidebar of Graph tab:
To visualize your data on the knowledge graph, you need to choose what data you’d like to convert to tables first by creating the relationships. Once this is done, click the graph tab. This will load the whole graph with each node and relationship.
You can import and analyze Facebook data using KgBase Facebook integration feature.
To load Apache TinkerPop Gremlin data using the CSV format, you must specify the vertices and the edges in separate files.
KgBase markup language is a user-friendly way to create graphs just by writing text.
You can get started with KgBase API by installing the official Python package:
In this tutorial, you'll learn how to use the data of your KgBase project in Gephi. First part is exporting your data from KgBase, second part is importing the generated file into Gephi.
You can upgrade your subscription to KgBase via the upgrade button on the upper right corner.