This form provides a template for a form allowing third party use of the data under conditions governing responsible, respectful and ethical research. It is a useful example of a form that any third party requesting to use data collected during a project should complete, including specific conditions for which individual identifiers should be removed before publishing. […]
These resources will help you organize, understand and visualize your data appropriately. They also identify ways to share data responsibly inside or outside your organization and guard against data misuse.
Interested in how to publish data without passing on people’s personal information? Try the Open Data Institute’s walkthrough guide, developed from a session at the Open Knowledge Festival last year.
This is a guide to planning the various stages of a project involving data, with sections for people starting out on a project or those already halfway through an initiative. In particular, check out the sections on closing a project successfully, including designing projects with a finite lifespan and enforcing a definitive ‘hands-off’ date (p.8). Where this […]
This guide gives practical guidance for protecting personal data in the context of migrant assistance.
It seems like there has been a lot of questions amongst the members of the Responsible Data listserv on issues related to de-identification, including when we should do it and what the potential risks and harms may be. Therefore, we are coordinating an online discussion on De-identifying data: an introduction for advocacy organisations on Friday, June […]
This report identifies privacy legal challenges to sharing information about missing persons in the context of disaster relief work.
As part of Brookings’ Issues in Technology Innovation series, Cameron F Kerry, Yves-Alexandre de Montjoye and Jake Kendall published a paper arguing for a more nuanced approach in protecting privacy related to mobile data, and building a case for special exceptions where data may be used for significant public good or to avoid serious harm to people.
Guidance on different types of collaborative software, factoring in responsible data principles.
A list of questions and considerations when designing your data visualizations to help you recognize and avoid bias and misrepresentation.
This book, organized around the data lifecycle, highlights responsible data concerns, recommendations, and real-world examples in the context of international development programming.