Using Multinet

This chapter is all about how to make use of a running Multinet system. Along the way, you will also learn how Multinet structures data into tables and networks, collected in different workspaces, and how Multinet thinks of multivariate data and multivariate networks.

Getting Started

To begin, you will need access to a running Multinet instance (either the official instance hosted at, or a local instance you have built and run; see Quick Start for help). We will follow some steps to illustrate the basic mode of using the system.

1. Create a Workspace

Multinet structures all the data it hosts into workspaces. A workspace can hold several tables of data, as well as several networks assembled from those tables. Think of a workspace as a dedicated area for related data to be stored.

In this tutorial sequence we will be recreating the Paul Revere dataset as a social network connecting the various Revolutionary War figures to the social clubs they belonged to.

The first step for any session where you’re modifying data, is to log in using Google OAuth. Click the person icon next to the multinet logo and then click ‘Sign in with Google’. Follow the prompts until you’re back on the multinet site. Authenticating allows you to create workspaces and upload data to them.

To create a workspace to hold the materials for this dataset, use the NEW WORKSPACE button appearing near the top of the left sidebar. A dialog box will appear asking for the name of the new workspace. Fill this in with boston and click on the CREATE WORKSPACE button. This will create the workspace and activate it.

In the main panel, you should see two empty columns, headed by Networks and Tables respectively. These columns will track all of the data that comes to live in this workspace.

2. Upload Node Tables

Multinet largely thinks of attribute data in tabular terms. That is, Multinet can ingest data formatted as (among other things) CSV files, storing it as a table of rows, each row containing the same types of attributes in the same order. Every node table must have a column of keys, which contains a unique value for every row within the table it is part of. By default, the Multinet uploader assumes that this is in a column called _key, but you may specify a different column in the uploader options.

We will begin by uploading separate tables to account for the people and clubs represented in this dataset. First, download members.csv; this file contains the names of several historical figures important during the American Revolution, along with some attributes. Next, click on the plus icon to the right of the Tables column to upload a file and create a table. Specify the members.csv file, note that the system autofills in the name of the table to create, and then click the CREATE button.

This network contains two node types—one to encode the people, and another for the clubs they belong to. Multinet recognizes nodes encoded in different tables as being of different node types, so download clubs.csv and upload it to a clubs table, using the same procedure as above.

You should now see both a members and a clubs table listed. You can click on each of these to see the rows of each table. Return to the workspace view by clicking on boston in the top bar.

3. Upload an Edge Table

Next we want to specify the topology of this network—that is, the relationship between clubs and members as specified by membership. We need a special table that encodes these memberships, using special attributes _from and _to. These attributes will always refer to rows from other tables in the workspace, using a node ID, which is formed by joining the name of the table and the key of the row with a slash. For instance, the John Adams row has a key value of 7; its node ID is therefore members/7.

You can think of the rows of such a table as a directed links connecting two of the nodes from somewhere in the workspace. To see this in action, download membership.csv, and upload it as a table. Because this table has properly formatted _from and _to attributes, Multinet recognizes it as an edge table. If you click on the newly uploaded table, you can explore what the rows look like. Note that while edge tables can also have other attributes, this one does not.

4. Create a Network

Creating a network in Multinet is a matter of specifying an edge table that defines that network’s topology and implicitly (via the _from and _to values of its edge table rows, the nodes involved as) its nodes as well. To create the Paul Revere network, click on the plus icon to the right of the Networks column. When the dialog box appears, click on the CREATE tab at the top, then select the membership table from the dropdown. Note that Multinet already knows which tables are edge tables, due to the presence of _from and _to attributes. Fill in the name of the network with boston, and then click on the CREATE NETWORK button. You should see the new network appear in the Networks column.

If you click on the new network, you will be taken to the network view, which aggregates various pieces of information about this network, and provides links to visualization applications. Note that the main panel displays some characteristic information such as the number of nodes and edges, and the drawer at the bottom displays information about the node types comprising this network, the edge table that provides the connectivity, and a paged view of the nodes themselves, identified by their node IDs. Clicking on these items will bring you to dedicated views providing specific information; you can return to the network view using the browser back button.

5. Visualize the Network

Now that the Paul Revere network is known to Multinet, its component data is now available via the Multinet API to be consumed by different analysis and visualization applications. To demonstrate, we will launch an interactive node-link diagram to see what this particular network looks like.

In the network view, note that the right-hand sidebar contains a list of external applications it can open. Click on Nodelink to open the node-link diagram in a new tab. This application works by sending REST requests for the specified network to the Multinet API server (which is the same server that provides the file-browser-like view of the data that we have been learning about in the Multinet client). As data about the nodes and links arrives in this application, it can construct an interactive visual model of the network as a collection of physical nodes connected by physically springlike links. Play with the network in this application and explore the various options available in the control panel.