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Slide 1 of 3. Advancing open data
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Our approach

Microsoft believes everyone can benefit with collaboration around open and available data.

Enable open innovation

We’re working to promote open innovation and data governance approaches that empower data users and providers to collaborate and create value.

Build partnerships for greater impact

We believe success requires partners—industry, government, and civil society around the world. Together, we promote greater access to data to benefit society and bridge the data gap.

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.

Accelerating access to data

Access to data is a big challenge. We partner with industry and open data leaders to advance open data access and private sector data sharing for societal benefit.
Aerial view of people walking on a street.

Industry Data for Society Partnership

Working across industry to make private sector data more open and accessible for societal good.
Line drawing of a neighborhood connected to a cloud with lines.

The open data opportunity

The importance behind data sharing explained.

Microsoft Data for Society catalog

Explore datasets, use cases, and more in our Microsoft Data for Society repository. ​
Colorful banknotes from different countries.

BankNote-Net

Worldwide millions of people have low or no vision. BankNote-Net was created as an open dataset for assistive universal currency recognition to help with daily tasks such as currency recognition.
Map of the United States color coded by broadband usage per county.

United States broadband usage dataset

Broadband internet access is critical to providing communities with education, employment, and telecare. The broadband usage percentages dataset shows broadband access at the US county-level to help address gaps in service availability.
Two young woman speak in sign language.

MS-ASL American Sign Language (ASL) dataset

In the US, over 500,000 people use ASL for communication. This ASL dataset of over 25,000 annotated videos with sign and action recognition can help researchers build machine learning models to advance sign language recognition.
Images of hands in different positions shown on a monitor.

Tagged hands dataset

Development of a rich hand-gesture-based interface is currently a tedious process. This dataset of 3,500 labeled depth frames of various hand poses and 140 gesture clips helps enable easy development of a gesture-based interface.
Collage of drawings developing progressively.

Generative Neural Visual Artist (GeNeVA)

Intelligent systems can generate images and video for a range of applications, from education to accessibility. This dataset has sequences of images, associated instructions and linguistic feedback, and a modified version of the Compositional Language and Elementary Visual Reasoning (CLEVR) dataset.
Collection of colorful pens on a shelf.

Learning from analog pen use to improve digital ink experiences

To help researchers understand the gaps between analog versus digital pens and improve digital experiences, this dataset contains 493 entries of a diary study with 26 participants using analog pens and 178 entries from 30 participants using digital pens.
Collage of colorful question marks on speech bubbles.

Microsoft Machine Reading Comprehension (MS MARCO)

AI and automated assistants need strong machine reading comprehension (MRC) and question answering (QA) capabilities to understand real-world dialog. This dataset contains 1,010,916 questions and 182,669 answers to improve QA and MRC.
Graphic of "Online risks experienced vary by gender: Total, 2016-2021 average".

Digital Civility Gender Equality Dataset

Microsoft recognizes the importance of advocating for and advancing the release of gender disaggregated data to realize gender equality and to close the data divide. This dataset can be leverage by researchers and organizations to advance better gender data policies and solutions.
Field with rows of solar panels.

Solar farms mapping

The solar farms mapping data can help researchers identify factors driving land suitability for solar projects and help public agencies better plan siting of solar energy development in India.
Aerial view of glaciers.

HKH glacier mapping

Glacier mapping is key to ecological monitoring in the Hindu Kush Himalaya (HKH) region, climate change poses a risk to those dependent on the health of glacier ecosystems. The (HKH) glacier mapping dataset includes imagery with locations of glaciers.
Satellite view of a city with color coding to show land cover.

Chesapeake land cover

The Chesapeake Conservancy created a landcover dataset for conservation efforts, this same data containing high-resolution aerial imagery and land cover labels can be used to train ML models to map an even wider area of land cover.
Barn in a field against a blue sky.

Concentrated Animal Feeding Operations (CAFO)

The poultry CAFO GitHub repository contains US-wide datasets of predicted poultry barn locations to help researchers identify CAFOs for conservation groups to address water and air quality issues.
A multicolored aerial view of an urban area.

TorchGeo

TorchGeo is a PyTorch domain library that includes several Geospatial benchmark datasets such as CDL, Landsat7, and Landsat8 to help support research tasks like image classification, semantic segmentation, object detection, instance segmentation, change detection, and more.
World map showing spread analysis by country/region..

Bing COVID-19 data

Bing COVID-19 data includes confirmed, fatal, and recovered cases from all regions, updated daily from multiple reliable sources. This data is reflected in the Bing COVID-19 Tracker.
Scientist holding DNA gel in laboratory.

NCI-PID-PubMed Genomics KB

NCI-PID-PubMed Genomics Knowledge Base Completion Dataset is derived from the National Cancer Institute Pathway Interaction Database, and contains textual mentions extracted from cooccurring pairs of genes in PubMed abstracts, to help support the cancer research community and others interested in cellular pathways.
Athletes working out inside and outside a gym.

Exercise recognition from wearable sensors

Exercise is an important part of maintaining good health. This data set contains accelerometer and gyroscope recordings from over 200 participants performing various gym exercises that can be leveraged by researchers developing exercise devices.
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Two people in a conference room talk in front of a laptop.

Microsoft Nonprofit Innovation Hub

The Nonprofit Innovation Hub is an open-source GitHub repository with lightweight solutions that enable nonprofits to innovate.

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.

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.

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.

Researcher tools

Explore a collection of datasets, code, and models from Microsoft Research for the broader academic community to advance state-of-the-art research across all disciplines.
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