Introduction
The Dataverse Software APIs allow users to accomplish many tasks such as…
creating datasets
uploading files
publishing datasets
and much, much more
… all without using the Dataverse installation’s web interface.
APIs open the door for integrations between the Dataverse Software and other software. For a list, see the Integrations section of the Admin Guide.
What is an API?
API stands for “Application Programming Interface” and an example is the Dataverse Software’s “file upload” API. In the diagram below, we can see that while users can click a button within Dataverse installation’s web interface to upload a file, there are many other ways to get files into a Dataverse installation, all using an API that allows for uploading of files.
The components above that use the “file” upload API are:
DvUploader is terminal-based application for uploading files that is described in the Dataset + File Management section of the User Guide.
OJS, OSF, and RSpace are all web applications that can integrate with a Dataverse installation and are described in “Getting Data In” in the Integrations section of the Admin Guide.
The script in the diagram can be as simple as a single line of code that is run in a terminal. You can copy and paste “one-liners” like this from the guide. See the Getting Started with APIs section for examples using a tool called “curl”.
The diagram above shows only a few examples of software using a specific API but many more APIs are available.
Types of Dataverse Software API Users
This guide is intended to serve multiple audiences but pointers various sections of the guide are provided below based on the type of API user you are.
API Users Within a Single Dataverse Installation
Each Dataverse installation will have its own groups of people interested in APIs.
Users of Integrations and Apps
Integrations and apps can take many forms but two examples are:
Using Open Science Framework (OSF), a web application, to deposit and publish data into a Dataverse installation.
Using DVUploader, a terminal-based desktop application, to upload files into a Dataverse installation.
In both examples, users need to obtain an API Token to authenticate with a Dataverse installation.
Starting point A good starting point is “API Tokens” in the Account Creation + Management section of the User Guide. DvUploader is documented in the Dataset + File Management section of the User Guide. The integrations that are enabled depend on your Dataverse installation. You can find a list in the Integrations section of the Admin Guide.
Power Users
Power users may be researchers or curators who are comfortable with automating parts of their workflow by writing Python code or similar.
Starting point The recommended starting point for power users is the Getting Started with APIs section.
Support Teams and Superusers
Support teams that answer questions about their Dataverse installation should familiarize themselves with the Getting Started with APIs section to get a sense of common tasks that researchers and curators might be trying to accomplish by using Dataverse Software APIs.
Superusers of a Dataverse installation have access a superuser dashboard described in the Dashboard section of the Admin Guide but some operations can only be done via API.
Starting point A good starting point for both groups is the Getting Started with APIs section of this guide followed by the Troubleshooting section of the Admin Guide.
Sysadmins
Sysadmins often write scripts to automate tasks and Dataverse Software APIs make this possible. Sysadmins have control over the server that the Dataverse installation is running on and may be called upon to execute API commands that are limited to “localhost” (the server itself) for security reasons.
Starting point A good starting point for sysadmins is “Blocking API Endpoints” in the Configuration section of the Installation Guide, followed by the Getting Started with APIs section of this guide, followed by the Troubleshooting section of the Admin Guide.
In House Developers
Some organizations that run a Dataverse installation employ developers who are tasked with using the Dataverse installation’s APIs to accomplish specific tasks such as building custom integrations with in house systems or creating reports specific to the organization’s needs.
Starting point A good starting point for in house developers is the Getting Started with APIs section.
API Users Across the Dataverse Project
The Dataverse Project loves contributors! Depending on your interests and skills, you might fall into one or more of the groups below.
Developers of Integrations, External Tools, and Apps
One of the primary purposes for Dataverse Software APIs in the first place is to enable integrations with third party software. Integrations are listed in the following places:
The Integrations section of the Admin Guide.
The Building External Tools section this guide.
The Apps section of this guide.
Starting point Good starting points are the three sections above to get a sense of third-party software that already integrates with the Dataverse Software, followed by the Getting Started with APIs section.
Developers of Dataverse Software API Client Libraries
A client library helps developers using a specific programming language such as Python, Javascript, R, or Java interact with Dataverse Software APIs in a manner that is idiomatic for their language. For example, a Python programmer may want to
Starting point A good starting point is the Client Libraries section, followed by the Getting Started with APIs section.
Developers of The Dataverse Software Itself
Developers working on the Dataverse Software itself use the APIs when adding features, fixing bugs, and testing those features and bug fixes.
Starting point A good starting point is the Testing section of the Developer Guide.
How This Guide is Organized
Getting Started
API Tokens and Authentication
Lists of Dataverse APIs
Search API: For searching dataverse collections, datasets, and files.
Data Access API: For downloading and subsetting data.
Native API: For performing most tasks that are possible in the GUI. See Getting Started with APIs for the most common commands which operate on endpoints with names like:
Dataverses
Datasets
Files
etc.
Dataset Semantic Metadata API: For creating, reading, editing, and deleting dataset metadata using JSON-LD.
Dataset Migration API: For migrating datasets from other repositories while retaining the original persistent identifiers and publication date.
Direct DataFile Upload/Replace API: For the transfer of larger files/larger numbers of files directly to an S3 bucket managed by Dataverse.
Globus Transfer API: For the Globus transfer of larger files/larger numbers of files directly via Globus endpoints managed by Dataverse or referencing files in remote endpoints.
Metrics API: For query statistics about usage of a Dataverse installation.
SWORD API: For depositing data using a standards-based approach rather than the Native API.
Please note that some APIs are only documented in other guides that are more suited to their audience:
Admin Guide
Installation Guide
Developer Guide
Client Libraries
See Client Libraries for how to use Dataverse Software APIs from Python, R, Java, and Javascript.
Examples
Apps links to example open source code you can study. Getting Started with APIs also has many examples.
Frequently Asked Questions
Getting Help
Dataverse Software API questions are on topic in all the usual places:
The dataverse-community Google Group: https://groups.google.com/forum/#!forum/dataverse-community
The Dataverse Project community calls: https://dataverse.org/community-calls
The Dataverse Project chat room: https://chat.dataverse.org
The Dataverse Project ticketing system: support@dataverse.org
After your question has been answered, you are welcome to help improve the Frequently Asked Questions section of this guide.