It's often said that a book is the project of many hands. This saying is certainly true for this book. A debt of gratitude is owed to Patsy Baudoin, who first wrote to put the two of us in touch. Without her email message, this project would not exist. This project also would not exist without all the activists, journalists, artists, designers, engineers, scientists, scholars, and teachers whose work we describe in this book, as well as the numerous additional projects that we discussed during the writing process, but ultimately did not have the space to include. Your work is an inspiration.

Breastfeeding is not only a public health issue, but also a matter of economic and social justice. This paper presents an iteration of a participatory design process to create spaces for re-imagining products, services, systems, and policies that support breastfeeding in the United States. Our work contributes to a growing literature around making hackathons more inclusive and accessible, designing participatory processes that center marginalized voices, and incorporating systems-and relationship-based approaches to problem solving. By presenting an honest assessment of the successes and shortcomings of the first iteration of a hackathon, we explain how we restructured the second Make the Breast Pump Not Suck hackathon in service of equity and systems design. Key to our re-imagining of conventional innovation structures is a focus on experience design, where joy and play serve as key strategies to help people and institutions build relationships across lines of difference. We conclude with a discussion of design principles applicable not only to designers of events, but to social movement researchers and HCI scholars trying to address oppression through the design of technologies and socio-technical systems.

Working with data is an increasingly powerful way of making knowledge claims about the world. There is, however, a growing gap between those who can work effectively with data and those who cannot. Because it is state and corporate actors who possess the resources to collect, store and analyze data, individuals (e.g., citizens, community members, professionals) are more likely to be the subjects of data than to use data for civic purposes. There is a strong case to be made for cultivating data literacy for people in non-technical fields as one way of bridging this gap. Literacy, following the model of popular education proposed by Paulo Freire, requires not only the acquisition of technical skills but also the emancipation achieved through the literacy process. This article proposes the term creative data literacy to refer to the fact that non-technical learners may need pathways towards data which do not come from technical fields. Here I offer five tactics to cultivate creative data literacy for empowerment. They are grounded in my experience as a data literacy researcher, educator and software developer. Each tactic is explained and introduced with examples. I assert that working towards creative data literacy is not only the work of educators but also of data creators, data publishers, tool developers, tool and visualization designers, tutorial authors, government, community organizers and artists.

Current efforts to build data literacy focus on technology-centered approaches, overlooking creative non-digital opportunities. This case study is an example of how to implement a Popular Education-inspired approach to building participatory and impactful data literacy using a set of visual arts activities with students at an alternative school in Belo Horizonte, Brazil.  As a result of the project data literacy among participants increased, and the project initiated a sustained interest within the school community in using data to tell stories and create social change.

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From global search engines to local smart cities, from public health monitoring to personal self-tracking technologies, digital technologies continuously capture, process, and archive social, material, and affective information in the form of big data. Although the use of big data emerged from the human desire to acquire more knowledge and master more information and to eliminate human error in large-scale information management, it has become clear in recent years that big data technologies, and the archives of data they accrue, bring with them new and important uncertainties in the form of new biases, systemic errors, and, as a result, new ethical challenges that require urgent attention and analysis. This collaboratively written article outlines the conceptual framework of the Uncertain Archives research collective to show how cultural theories of the archive can be meaningfully applied to the empirical field of big data. More specifically, the article argues that this approach grounded in cultural theory can help research going forward to attune to and address the uncertainties present in the storage and analysis of large amounts of information. By focusing on the notions of the unknown, error, and vulnerability, we reveal a set of different, albeit intertwined, configurations of archival uncertainty that emerge along with the phenomenon of big data use. We regard these configurations as central to understanding the conditions of the digitally networked data archives that are a crucial component of today’s cultures of surveillance and governmentality.

This paper explores three cases of Do-It-Yourself, open-source technologies developed within the diverse array of topics and themes in the communities around the Public Laboratory for Open Technology and Science (Public Lab). These cases focus on aerial mapping, water quality monitoring and civic science practices. The techniques discussed have in common the use of accessible, community-built technologies for acquiring data. They are also concerned with embedding collaborative and open source principles into the objects, tools, social formations and data sharing practices that emerge from these inquiries. The focus is on developing processes of collaborative design and experimentation through material engagement with technology and issues of concern. Problem-solving, here, is a tactic, while the strategy is an ongoing engagement with the problem of participation in its technological, social and political dimensions especially considering the increasing centralization and specialization of scientific and technological expertise. The authors also discuss and reflect on the Public Lab's approach to civic science in light of ideas and practices of citizen/civic veillance, or "sousveillance", by emphasizing people before data, and by investigating the new ways of seeing and doing that this shift in perspective might provide.

The growing number of tools for data novices are not designed with the goal of learning in mind. This paper proposes a set of pedagogical design principles for tool development to support data literacy learners.  We document their use in the creation of three digital tools and activities that help learners build data literacy, showing design decisions driven by our pedagogy. Sketches students created during the activities reflect their adeptness with key data literacy skills. Based on early results, we suggest that tool designers and educators should orient their work from the outset around strong pedagogical principles.