Information and messages expressed in a way involving visual elements, such as images, animations, diagrams or other mediums.
Author: Dave Tarrant James Maddison; Publisher: Open Data Institute; Publication Year: 2021. The following tool is for anyone who collects, shares or uses data. It helps identify and manage ethical issues – at the start of a project that uses data, and throughout. It encourages people to ask important questions about projects that use data, and reflect on the responses. It provides a framework to develop ethical guidance that suits any context…
Author: N/A; Publisher: Council of Europe; Publication Year: N/A. The following document was one of the first initiatives in data protection. It was open for signing in January 1981. The most crucial idea of the Convention is that it aimed to guarantee people the right to data protection long before big data became a concern. Another important concept of this document is that it seeks to create a common legal space…
Author: N/A; Publisher: Miro; Publication Year: N/A. The following visualization highlights the impact of bias in several aspects of the machine learning lifecycle. One point discussed frequently is the patterns of bias and discrimination baked into data sets. This image highlights that the real world patterns of discrimination and inequality are the source of the bias in our data sets…
Author: Cat Drew; Publisher: Royal Society Publishing; Publication Year: N/A. Summary: The following visual provides a clear framework and flow chart for data ethics in design practice. This resource has more general data ethics framework applications in white and the design applications in gray. This data ethics visual is also in grayscale which helps for those who are colorblind…
Author: Ben Schmidt; Publisher: Ben Schmidt (Personal Website); Publication Year: 2015. The interactive visualization here allows users to input words to query 14 million Rate My Professor reviews and see the splits in occurrence for gender across different school departments, as well for positive and negative reviews. Negative words generally occur more often for female professors, such as ‘horrible’, ‘awful’…