Our approach

We believe everyone can benefit from opening, sharing, and collaborating around data to make better decisions, improve efficiency, and help tackle some of the world’s most pressing societal challenges.

Set data collaboration principles

When we launched the Open Data Campaign, we adopted five principles to guide our participation in data collaborations: open; usable; empowering; secure; and private. These principles underpin our participation, and we hope other organizations can build on them to share their data responsibly.

Learn about our principles

Engage partnerships and explore projects

We believe success will depend on building deep collaborations with others from industry, government, and civil society around the world. This includes work with leading organizations in the open data movement, such as the Open Data Institute and The GovLab at New York University.

Make data sharing easier

We're committed to investing in the essential assets that will make data sharing easier, including the necessary tools; frameworks; and templates. This is especially important when it comes to opening and collaborating around data to solve important societal issues.


Closing the data divide

Access to data is a big challenge. The benefits for organizations of all sizes and the broader community are significant if we can work together to make progress on open data.

Collage of four aerial photos.

Year one in review

Sharing 10 lessons learned from the first year of the campaign to help other organizations of all sizes unlock the power of data.

Line drawing of a neighborhood connected to a cloud with lines.

The open data opportunity

The importance behind data sharing explained

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Open data stories

Stories of open data and data sharing driving change


20 data collaborations by 2022

Explore projects in the areas of sustainability; health; and equity and inclusion using open data and data sharing models that we've helped to launch against our commitment of 20 data collaborations by 2022.

Sustainability Health Equity and inclusion


Legal frameworks

Data sharing agreements can take months to draw up, oftentimes deterring organizations from sharing data at all. As a first step toward building better processes and tools, we're sharing a set of data agreements to govern the sharing of data, particularly in the context of training AI models.

CDLA Permissive 2.0

The Community Data License Agreement (CDLA) Permissive 2.0 is an open data agreement designed to make it easier to share and collaborate with open data.

C-UDA 1.0

The Computational Use of Data Agreement (C-UDA) 1.0 is intended for use with datasets that may include material not owned by the data provider, but where it may have been assembled lawfully from publicly accessible sources.

DUA-OAI

The Data Use Agreement for Open AI Model Development (DUA-OAI) provides terms to govern the sharing of data by an organization with another for the purpose of allowing that second organization to use the data to train an AI model, where the trained model is open sourced.

DUA-DC

The Data Use Agreement for Data Commons (DUA-DC) can be used by multiple parties who want to share data through a common, Application Programming Interface (API)-enabled database.


Capabilities

Learn more about the tools and practices we employ to enable more secure and streamlined access to data.

Differential privacy

Differential privacy introduces statistical noise–slight alterations–to mask datasets and protect the privacy of individuals.

Learn about differential privacy

Azure confidential computing

Confidential computing helps to protect sensitive data in the cloud by offering security through data-in-use encryption–additional protection for your data while it's being processed.

Read about Azure confidential computing

Azure Open Datasets

A curated collection of publicly available datasets that are ready to use in machine learning workflows and easy to access from Azure services.

Review the Azure Open Datasets

Microsoft Research Open Data

A collection of free datasets from Microsoft Research to advance state-of-the-art research in areas such as natural language processing, computer vision, and domain specific sciences.

Explore Microsoft Research Open Data