Getting started

The dataverse project describes itself as:

Dataverse is an open source web application to share, preserve, cite, explore,
and analyze research data. It facilitates making data available to others, and
allows you to replicate others’ work more easily. Researchers, journals, data
authors, publishers, data distributors, and affiliated institutions all receive
academic credit and web visibility.

Introduction: what’s this all about?

This project aims at offering a new way to deploy, run and maintain a Dataverse installation for any purpose on any kind of Kubernetes-based cloud infrastructure.

You can use this on your laptop, in your on-prem datacentre or public cloud. With the power of Kubernetes, many scenarios are possible.


Quick’n’dirty demo persona on naked cluster [1]:
kubectl apply -k

Wait. Regularly check logs and pods. Login with dataverseAdmin:admin1.

[1]Your mileage may vary due to storage classes. You really should look at the demos below.

Prerequisites: First things first.

Before you start deploying, make sure to look at the following checklist:

1. Think first

If you never touched a commandline, never thought about why using cloud infrastructure might be a good idea: maybe you should stick with the old, but paved and solid ways of installing complex applications like Dataverse.

Keen to learn new technology? Be part of the future? Want to streamline CI/CD and your application? Continue.

2. Install tools

You will at least need:

  • kubectl, at least version 1.14
  • git (or another VCS)

Depending on your use-case and targeted environment that might be just it. If something else is necessary, it’ll be documented in its respective documentation part.

3. Grasp some knowledge

If you never used Kubernetes, but want to deploy to production, you definitely should be reading some docs first. Some starting points:

4. Grab a cluster

You’ll need a running and fully configured Kubernetes cluster.

5. Choose persistent identifiers

When you want to register datasets and/or files in your deployment to DataCite, EZID or similar, you will need active accounts. Be sure to have access credentials around. As an alternative, you might want to use the FAKE provider.

Use Cases: What installation persona are you?

1. Demo time!

Demos provide showcases what Dataverse can do for you. Currently pre-packaged:

2. Developing is my thing

There is an entire section in this guide dealing with how to use this project for developing Dataverse, run development snapshots for tech demos, etc.

Please go to development docs here.

3. Gimme the production stuff


This needs yet to be refactored.

You should make yourself familiar with a series of documentation articles, linked below:

Please be aware that this project currently only offers images and support for basic usage. Integrations are not yet part of this, but may be added as needed. See also relevant docs within Dataverse guides and upstream projects.

4. Integrate yourself!

One of the true superpowers of Dataverse is its ability to integrate with external tools. Previewers, data analysis, data capturing and many more await you.


Currently, none of these are supported or maintained by this project, although this is a mid-term goal. If you feel a need, raise an issue. You are most welcome to contribute.