Introduction¶

Intended Audience¶

This guide is intended primarily for developers who want to work on the main Dataverse code base at https://github.com/IQSS/dataverse but see “Related Projects” below for other code you can work on!

To get started, you’ll want to set up your Development Environment and make sure you understand the branching strategy described in the Version Control section and how to make a pull request. Testing is expected. Opinions about Coding Style are welcome!

Getting Help¶

If you have any questions at all, please reach out to other developers via the channels listed in https://github.com/IQSS/dataverse/blob/develop/CONTRIBUTING.md such as http://chat.dataverse.org (#dataverse on freenode), the dataverse-dev mailing list, community calls, or support@dataverse.org.

Core Technologies¶

Dataverse is a Java EE application that is compiled into a war file and deployed to an application server (Glassfish) which is configured to work with a relational database (PostgreSQL) and a search engine (Solr).

We make use of a variety of Java EE technologies such as JPA, JAX-RS, JMS, and JSF. The front end is built using PrimeFaces and Bootstrap.

Roadmap¶

For the Dataverse development roadmap, please see https://dataverse.org/goals-roadmap-and-releases

Kanban Board¶

You can get a sense of what’s currently in flight (in dev, in QA, etc.) by looking at https://github.com/orgs/IQSS/projects/2

Issue Tracker¶

We use GitHub Issues as our issue tracker: https://github.com/IQSS/dataverse/issues

Related Guides¶

If you are a developer who wants to make use of Dataverse APIs, please see the API Guide. If you have front-end UI questions, please see the Style Guide.

If you are a sysadmin who likes to code, you may be interested in hacking on installation scripts mentioned in the Installation Guide. We validate the installation scripts with Tools such as Vagrant and Docker (see the Docker, Kubernetes, and OpenShift section).

Related Projects¶

As a developer, you also may be interested in these projects related to Dataverse:

• External Tools - add additional features to Dataverse: See the External Tools section of the Installation Guide.
• Dataverse API client libraries - use Dataverse APIs from various languages: Client Libraries
• DVUploader - a stand-alone command-line Java application that uses the Dataverse API to support upload of files from local disk to a Dataset: https://github.com/IQSS/dataverse-uploader
• dataverse-sample-data - populate your Dataverse installation with sample data: https://github.com/IQSS/dataverse-sample-data
• dataverse-metrics - aggregate and visualize metrics for installations of Dataverse around the world: https://github.com/IQSS/dataverse-metrics
• Configuration management scripts - Ansible, Puppet, etc.: See “Advanced Installation” in the Preparation section of the Installation Guide.
• Universal Numerical Fingerprint (UNF) (Java) - a Universal Numerical Fingerprint: https://github.com/IQSS/UNF
• GeoConnect (Python) - create a map by uploading files to Dataverse: https://github.com/IQSS/geoconnect
• DataTags (Java and Scala) - tag datasets with privacy levels: https://github.com/IQSS/DataTags
• TwoRavens (Javascript) - a d3.js interface for exploring data and running Zelig models: https://github.com/IQSS/TwoRavens
• Zelig (R) - run statistical models on files uploaded to Dataverse: https://github.com/IQSS/Zelig
• Matrix - a visualization showing the connectedness and collaboration between authors and their affiliations.
• Third party apps - make use of Dataverse APIs: Apps
• chat.dataverse.org - chat interface for Dataverse users and developers: https://github.com/IQSS/chat.dataverse.org
• [Your project here] :)

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