This article is based on Microsoft's Post 'Open Data for Social Impact Framework'. All credit goes to Microsoft researchers 👏👏👏

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The Open Data for Social Impact Framework, developed by Microsoft, is a roadmap to help businesses use data to gain new insights, make better decisions, and improve efficiency while addressing pressing social issues. “The ability to access data to improve outcomes involves much more than technology tools and the data itself,” the framework builds on foundational learning from the Open Data Campaign. It’s a framework that empowers leaders to use data to solve the problems that matter most to them. Realizing that not all data can be made public, huge benefits can be achieved by promoting more open data, whether in the form of trusted data collaborations or completely open and public data.

It is a platform that leaders can use to use data to solve important social issues such as reducing carbon emissions, closing the broadband gap, improving skills professionals and the expansion of accessibility and inclusiveness. The methodology below aims to provide organizational leaders across all sectors of the data ecosystem – governments, nonprofits, and multilateral organizations – with insights and solutions that can be used to address pressing social concerns.

When trying to use statistics to improve social outcomes, this site identifies five thematic areas for companies to consider: leadership, opportunity, skills, community governance, and technology and data – check that the necessary organizational architecture is in place to understand the issues. want the data to respond, have the required expertise, have established community trust, and have the resources to monitor, activate, and increase your impact. It suggests questions to ask and provides resources to answer them. Examples of real-world open data projects help bring these notions to life. A path to open data is also available for business leaders to use as a starting point.

This framework can be used to help establish the foundations for open data and data collaboration. There are, however, a plethora of wonderful additional resources available to anyone looking to use data for social good. It shares successful projects from the Open Data Campaign, such as Education Open Data Challenge and Electric Vehicle Charging Infrastructure Pilot, and resources from Microsoft partners, such as the Open Data Institute and The GovLab, to help organizations navigate in the roadmap. . The AI ​​Playbook, Data Stewards Academy, Data Landscape Playbook, Data Skills Framework, The Data Assembly, and Data Responsibility Journey are some important resources.

The ability to reveal sensitive data can be a data openness issue. The protection of individual privacy and the protection of confidential or commercially sensitive information may be mandated by law or governed by contract. Additionally, companies must assess the reputational, ethical, and business consequences of sharing sensitive data.

Protecting sensitive data using appropriate legal, technical and organizational means is key to protecting stakeholders in the data sharing ecosystem and building trust in data sharing. However, companies should not be deterred from adopting a successful data strategy because of this requirement. Rather, appropriate governance mechanisms for responsible data sharing can be implemented to achieve the desired level of protection.

Privacy tools, for example, can be used to help keep personal information confidential. Differential privacy, homomorphic encryption, private computing, anonymization and de-identification are technologies and approaches that can be used to protect the privacy of individuals while improving access to data for businesses, researchers and civil society. Although these technologies are not suitable for many situations, they can benefit others.

The Open Data for Social Impact framework builds on the ten lessons learned from the Open Data campaign. The campaign, launched by Microsoft in April 2020, specified organizational goals. To get started, publicize the five principles that define Microsoft’s contribution and commitment to trusted data collaboration: Open, Usable, Empowering, Secure, and Private. Second, by 2022, partner with 20 organizations to learn more about the potential and barriers they face when using data techniques to achieve their goals.

Third, invest in frameworks and capabilities such as Differential Privacy to make data more open without compromising data security, Confidential Computing to isolate sensitive data during processing, Azure Open Datasets to save time on discovery data using publicly available datasets and Azure Data Share to quickly and securely share data with partners for more secure and streamlined data access and sharing.