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The Open Data for Social Impact Framework, developed by Microsoft, is a roadmap to assist companies in using data to get new insights, make better decisions, and enhance efficiency while addressing urgent social concerns. “The ability to access data to enhance outcomes entails much more than technological tools and the data itself,” the framework relies on the fundamental learning from the Open Data Campaign. It is a framework that allows leaders to use data to solve the problems that matter most to them. Finding that not all data can be made available publicly, enormous benefits can be gained 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 may use to use data to address significant social issues like lowering carbon emissions, closing the broadband gap, improving job skills, and expanding accessibility and inclusiveness. The methodology below is intended to bring organizational leaders from all sectors of the data ecosystem — governments, nonprofits, and multilateral organizations – to insights and solutions that can be used to address pressing social concerns.
When attempting to use statistics to improve social outcomes, this site identifies five topic areas that companies should consider: leadership, opportunity, skills, community governance, and technology and data – check that have the necessary organizational architecture in place that can understand the questions one want data to answer, have the requisite expertise, have built community trust, and have the resources to monitor, enable, and increase your impact. It suggests questions to ask and provides resources to answer them. Examples from real-world open data projects help to bring these notions to life. A path to open data is also available for corporate leaders to use as a starting point.
This framework can be used to assist in establishing the foundation for open data and data collaboration. There are, however, a plethora of additional wonderful resources available to anyone looking to use data for social good. It shares successful projects from the Open Data Campaign, such as the Education Open Data Challenge and the Electric Vehicle (EV) Charging Infrastructure Pilot, and resources from Microsoft’s partners, such as the Open Data Institute and The GovLab, to help organizations navigate the roadmap. The AI Playbook, the Data Stewards Academy, the Data Landscape Playbook, the Data Skills Framework, The Data Assembly, and the Data Responsibility Journey are a few significant resources.
The possibility of revealing sensitive data may be a problem with data openness. Individual privacy protection and the protection of confidential or commercially sensitive information may be mandated by law or governed by contract. Furthermore, firms must evaluate the reputational, ethical, and commercial consequences while sharing sensitive data.
Protecting sensitive data using appropriate legal, technical, and organizational means is critical to safeguarding stakeholders in the data-sharing ecosystem and engendering trust in data sharing. However, firms 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-enhancing tools, for example, can be used to assist keep personal information private. Differential privacy, homomorphic encryption, private computing, anonymization, and de-identification are technologies and approaches that can be used to protect individual privacy while improving data access for companies, researchers, and civil society. While these technologies may not be suitable for many situations, they can benefit others.
The Open Data for Social Impact Framework draws on the Open Data Campaign’s ten lessons learned. The campaign, which Microsoft launched in April 2020, specified organizational goals. To begin, make public 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 about the potential and obstacles they encounter when using data techniques to further their goals.
Third, invest in frameworks and capabilities such as differential privacy to make data more open without jeopardizing data security, confidential computing to isolate sensitive data during processing, Azure Open Datasets to save time on data discovery by using publicly available datasets, and Azure Data Share to share data quickly and safely with partners for more secure and streamlined data access and sharing.
Annu is a consulting intern at MarktechPost. She is currently pursuing her B.Tech from the Indian Institute of Technology(IIT), Kanpur. She is a coding enthusiast and has a keen interest in the scope of application of mathematics in various fields. She is passionate about exploring the new advancements in technologies and their real-life application.