Redivis

Redivis#

Redivis is a cloud-based data platform that lets researchers discover, query, and analyze datasets directly in their browser — without downloading files. Northwestern’s Redivis Data Library is a collaboration between Kellogg Research Support and Northwestern University Libraries. It hosts a curated collection of research datasets that can be explored interactively, linked into analysis workflows, or accessed programmatically via API from the Kellogg Linux Cluster (KLC).

Gaining Access#

  1. Visit the Northwestern Redivis Data Library .

  2. Click Create account in the upper right corner.

    Northwestern Redivis Data Library page with the Create account button highlighted

  3. Choose Authenticate with your institution and select Northwestern University. Sign in with your Northwestern NetID credentials.

    Sign in to Redivis with your Northwestern University account

  4. After signing in, you will be taken to the Northwestern organization page. Click Join organization and complete the short request form.

    Northwestern Redivis organization page showing the Join organization button

  5. Once your request is approved, you will have access to the datasets hosted in the Northwestern Data Library. Some datasets additionally require you to Apply for access on the individual dataset page.

For a walkthrough, see the Redivis discover and access data guide .

Exploring Datasets#

Visit the Northwestern datasets page to browse all datasets hosted in the Northwestern Data Library.

When you open a dataset you will find three main tabs:

  • Overview — General description, citation information, and access terms for the dataset.

  • Tables — All tables included in the dataset. Click any table to open an exploration panel with three sub-tabs:

    • Variables — Full data dictionary listing every variable and its type.

    • Cells — A scrollable preview of the data. Select a column to see summary statistics in the right pane.

    • Query — An ad-hoc SQL interface for quick, transient queries. Results are shown inline but cannot be saved.

Working with Data in Workflows#

For deeper analysis, click Analyze in workflow (upper right of any dataset page) to open the dataset in a Redivis workflow. Inside the workflow canvas:

  1. Click the circular dataset node to expand it, then hover over it to reveal two options: Transform and Notebook.

  2. Transform — A graphical interface for building multi-step data pipelines:

    • From New step, select SQL query to write a SQL transformation.

    • From New step, choose other built-in operations (filter, aggregate, join, etc.) as needed.

    • Click Run in the upper right to execute the pipeline.

    • Click the output node, then use Export table in the right pane to download results.

  3. Notebook — Opens a Jupyter notebook with a Python or R kernel pre-connected to your dataset:

For a walkthrough, see the Redivis analyze data in a workflow guide .

Accessing Redivis Data from KLC#

You can query Redivis datasets programmatically from the Kellogg Linux Cluster using the Redivis Python client library.

Step 1 — Generate an API token#

  1. Log in to Redivis and go to Settings → API tokens .

  2. Click Generate new token.

  3. Enable the Data and Workflow permissions, then click Generate token.

  4. Copy the token text.

Step 2 — Save the token on KLC#

cd $HOME
mkdir -p keys
nano keys/redivis_api.txt
# Paste your token, then press Ctrl+X and save

Step 3 — Run a query#

Sample scripts are available on KLC at /kellogg/software/redivis_scripts. Copy them to your working directory and run:

cp /kellogg/software/redivis_scripts/sample_sql.py .
cp /kellogg/software/redivis_scripts/nu_author_openalex.sql .

module load mamba/24.3.0
source /hpc/software/mamba/24.3.0/etc/profile.d/conda.sh
conda activate /kellogg/software/envs/redivis_env
python sample_sql.py

Datasets on Redivis#

The dataset pages below document a selected subset of datasets available on the Redivis platform with documentation on this site.

Note

The datasets listed below are a selected subset with documentation on this site, not an exhaustive catalog. For an exhaustive list of datasets available to Kellogg researchers, see the Kellogg Research Support Datasets page .

Dataset

Brief Description

L2 VM2 Uniform

National voter file from all 50 states, enhanced with consumer and demographic data, standardized into a single schema

Numerator

Consumer panel data on purchases, promotions, and shopping behavior

OpenAlex

Open catalog of scholarly works, authors, institutions, sources, topics, and funders, and their connections

ProxyCurl

Snapshot of ~170 million public LinkedIn profiles with professional attributes