Catherine D'Ignazio | Massachusetts Institute of Technology (MIT) (original) (raw)

Data: Visualization, Literacy, Pedagogy by Catherine D'Ignazio

This is a long-form blog post from the MIT Center for Civic Media blog that examines non-binary g... more This is a long-form blog post from the MIT Center for Civic Media blog that examines non-binary gender data in the context of big data and computational applications circa 2016. Gender is almost always treated as a binary, immutable characteristic of humans. These applications thus reinforce the idea that the world is only made up of two groups (male, female) which is categorically, empirically, and historically untrue. The blog post explores some of the ethical territory for how, when, and whether non-binary gender should be represented in large data sets.

Working with data is an increasingly powerful way of making knowledge claims about the world, how... more Working with data is an increasingly powerful way of making knowledge claims about the world, however there is 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 (as citizens, as community members, as 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 means of bridging that 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 essay proposes the term creative data literacy to recognize that non-technical learners may need alternate pathways towards data than those coming 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 data creators, data publishers, tool developers, tool and visualization designers, tutorial authors, government, community organizers and artists.

—In this paper, we begin to outline how feminist theory may be productively applied to informatio... more —In this paper, we begin to outline how feminist theory may be productively applied to information visualization research and practice. Other technology-and design-oriented fields such as Science and Technology Studies, Human-Computer Interaction, Digital Humanities, and Geography/GIS have begun to incorporate feminist principles into their research. Feminism is not (just) about women, but rather draws our attention to questions of epistemology – who is included in dominant ways of producing and communicating knowledge and whose perspectives are marginalized. We describe potential applications of feminist theory to influence the information design process as well as to shape the outputs from that process.

Data-centric thinking is rapidly becoming vital to the way we work, communicate and understand in... more Data-centric thinking is rapidly becoming vital to the way we work, communicate and understand in the 21st century. This has led to a proliferation of tools for novices that help them operate on data to clean, process, aggregate, and visualize it. Unfortunately, these tools have been designed to support users rather than learners that are trying to develop strong data literacy. This paper outlines a basic definition of data literacy and uses it to analyze the tools in this space. Based on this analysis, we propose a set of pedagogical design principles to guide the development of tools and activities that help learners build data literacy. We outline a rationale for these tools to be strongly focused, well guided, very inviting, and highly expandable. Based on these principles, we offer an example of a tool and accompanying activity that we created. Reviewing the tool as a case study, we outline design decisions that align it with our pedagogy. Discussing the activity that we led in academic classroom settings with undergraduate and graduate students, we show how the sketches students created while using the tool reflect their adeptness with key data literacy skills based on our definition. With these early results in mind, we suggest that to better support the growing number of people learning to read and speak with data, tool designers and educators must design from the start with these strong pedagogical principles in mind.

Big Data projects are being rapidly embraced by organizations working in the social good sector. ... more Big Data projects are being rapidly embraced by organizations working in the social good sector. This has led to a proliferation of new projects, with strong criticisms in response focusing on the disempowering aspects of these projects. This paper identifies four main problematic aspects of Big Data projects in the social good sector to focus on: lack of transparency, extractive collection, technological complexity, and control of impact. Leveraging Paulo Freire's concept of "Popular Education", we identify an opportunity to work on these issues in empowering ways through literacy education. We discuss existing definitions of data literacy and find a need to create an extended definition of Big Data literacy. Surveying existing approaches to building data literacy, we identify the need for new approaches and technologies to address the problematic aspects of Big Data projects. To flesh out this concept of "Popular Big Data", we close by offering seven ideas for how the field can ensure that Big Data projects are in line with the values of organizations working in the social good sector.

We propose that a bottom-up, participatory, grassroots approach to environmental investigation an... more We propose that a bottom-up, participatory, grassroots approach to environmental
investigation and data collection addresses the key issues of inclusion, accountability,
and credibility, by building public participation into the data lifecycle.
We envisage forms of participation in which members of the public take part in creating,
analyzing, and understanding datasets, and using them to advocate for change.
In the following FAQ essay, we refer to this as a “Small Data” approach, and examine
the implications of this approach in a series of questions and proposed answers.

Civic Media by Catherine D'Ignazio

In the last ten years, a growing range of products, gadgets, toys and new initiatives has made it... more In the last ten years, a growing range of products, gadgets, toys and new initiatives has made it possible for people to collect data about the physical world around them, share this information and create novel data sets. The rise of quotidian sensors promises to democratize science, but raises complex questions about what science requires in addition to data, and whether access to sensors turns cities into smart cities, journalists into data analysts and citizens into scientists. We identify and explore five paradigms for the use of sensors by everyday citizens: smart cities, sensor journalism, crowdsourced journalism, citizen sensing and citizen science. We include two case studies that complicate aspirations for citizen sensors as a tool for empowerment. One case is Safecast, a start-up that formed after the Fukushima Daiichi nuclear disaster in Japan which designed a highly accurate radiation sensor in order to monitor radiation levels in the environment and verify whether the government was publishing accurate information. Our second case considers the coquí, a DIY water conductivity sensor that D'Ignazio has been using to teach journalism students about water quality. From these case studies, we see evidence that individuals empowered by sensors are best understood not as citizen scientists or crowdsourcing subjects, but as effective and empowered citizens. We posit that Michael Schudson’s “monitorial citizen” may be the most apt paradigm to consider for the emancipatory potential of popular sensing.

From the International Handbook of Media Literacy Education.

The growing diversity of news sources available online has led to a significant methodological ch... more The growing diversity of news sources available online has led to a significant methodological change in field of global news coverage. Studies of media attention and framing require sophisticated analytic tools to permit analysis of a large volume of content consumed by a broad readership. Geographic focus continues to be a topic of interest to media organizations, media analysts, and media consumers. Detecting and recognizing geographic locations (toponyms) in news media is a well-established field with many commercial and open source tools available. An evaluation is performed of various existing tools to compare their accuracy and appropriateness for use within media organizations and for media analysis. The concept of focus, indicating the location an article is primarily about, is extended into the news realm and added to an existing tool to increase relevance for the aforementioned applications. Potential applications as well as initial experiments using geoparsing for news organizations are discussed, in addition to ideas for future work building on these tools.

Researchers have tested a variety of personal informatics systems to encourage diversity in the p... more Researchers have tested a variety of personal informatics systems to encourage diversity in the political leaning, geography, and demographics of information sources, often with a belief in the normative value of exposure to diverse information sources. Methods attempted have included information labeling of media sources, personalized metrics of reading behavior, personalized visualization of social media behavior, recommendation systems, and social introductions. Although some of these systems demonstrate positive results for the metrics they define, substantial questions remain on the interpretation of these results and their implications for future design. We identify challenges in defining normative values of diversity, potential algorithmic exclusion for some groups, and the role of personal tracking as surveillance. Furthermore, we outline challenges for evaluating systems and defining the meaningful social impact for information diversity systems operating at scale.

Feminist Tech & Inclusive Design by Catherine D'Ignazio

Science and Engineering Ethics, 2018

This paper explores three cases of Do-It-Yourself, open-source technologies developed within the ... more 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 collabora-tive 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 All authors have made equal contribution to the work. * Hagit Keysar

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Breastfeeding is not only a public health issue, but also a matter of economic and social justice... more 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.

In recent years, the CHI community has begun to discuss how HCI research could improve the experi... more In recent years, the CHI community has begun to discuss how HCI research could improve the experience of motherhood. In this paper, we take up the challenge of designing for this complex life phase and present an analysis of data collected from a design process that included over 1,000 mother-submitted ideas to improve the breast pump, a technology that allows mothers around the world to collect and store their breast milk. In addition to presenting a range of ideas to improve this specific technology, we discuss environmental, legal, social, and emotional dimensions of the postpartum period that suggest opportunities for a range of additional supportive technologies. We close with insights linking our findings to ongoing discussions related to Feminist HCI theory, crowdsourcing, and participatory design.

This paper outlines questions about the role of design and the designer in addressing issues of s... more This paper outlines questions about the role of design and the designer in addressing issues of social justice, particularly in light of the fact that justice issues are not purely technical in nature. Treating them as such may lead to design for an unjust, unhealthy status quo. Using a case study of a large, human-centered hackathon where participants innovated breastpump designs, I suggest three preliminary ideas for how designers might tackle the ecology of a sociotechnical problem more holistically.

Art, Place, Cartography by Catherine D'Ignazio

Papers by Catherine D'Ignazio

Proceedings of the Design Society

Design and engineering are socio-technical enterprises used to solve real-world problems. However... more Design and engineering are socio-technical enterprises used to solve real-world problems. However, students in these fields are often under-equipped to consider the ethical and societal implications of their work. Our prior work showed that these societal considerations are more consistently embedded in design pedagogy in non-engineering than in engineering courses at MIT. Here, we examine underlying causes for this through a survey of instructors (231 courses from 29 departments). The main contribution of this work is an analysis of whether and how instructors incorporate social, ethical, and policy considerations in design pedagogy. The majority of respondents (60.6%) included these topics in their courses, primarily through discussion of social justice, identity groups, and ethics. These concepts were included more in non-engineering courses (65.8%) than engineering courses (46.9%). Many instructors, especially in engineering, cited irrelevance as the reason for not engaging with...

From the International Handbook of Media Literacy Education.

Science and Engineering Ethics, 2018

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Proceedings of the Design Society

Routledge eBooks, Apr 20, 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

International Encyclopedia of Human Geography, 2009

De´rive A term coined by the Situationist Internationale to denote a mode of experimental behavio... more De´rive A term coined by the Situationist Internationale to denote a mode of experimental behavior or way of passing through urban spaces. In practice, dé rives are often ways of walking that attempt to research, through direct observation and/or individual experience, diverse facets of the spatial environment. De´tournement A term coined by the Situationist Internationale to denote a process that involved removing cultural signs and media elements (painting, literature, film, words, and gestures) from their original context and recontextualizing them in a new context, often for the purposes of social and political critique. Psychogeography Entails the study of the precise laws and specific effects of the geographical environment, consciously organized or not, on the emotions and behavior of individuals.

Data Visualization in Society

We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point... more We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point that the human relations and impacts currently produced and reproduced through data are unequal. Likewise, white men remain overrepresented in data-related fields, even as other STEM (Science, Technology, Engineeering and Medicine) fields have managed to narrow their gender gap. To address these inequalities, we introduce teaching methods that are grounded in feminist theory, process, and design. Through three case studies, we examine what feminism may have to offer visualization literacy, with the goals of cultivating self-efficacy for women and underrepresented groups to work with data, and creating learning spaces where, as Philip et al. (2016) state, 'groups influence, resist, and transform everyday and formal processes of power that impact their lives'.

2022 ACM Conference on Fairness, Accountability, and Transparency

Data ethics and fairness have emerged as important areas of research in recent years. However, mu... more Data ethics and fairness have emerged as important areas of research in recent years. However, much work in this area focuses on retroactively auditing and "mitigating bias" in existing, potentially flawed systems, without interrogating the deeper structural inequalities underlying them. There are not yet examples of how to apply feminist and participatory methodologies from the start, to conceptualize and design machine learning-based tools that center and aim to challenge power inequalities. Our work targets this more prospective goal. Guided by the framework of data feminism, we co-design datasets and machine learning models to support the efforts of activists who collect and monitor data about feminicide-gender-based killings of women and girls. We describe how intersectional feminist goals and participatory processes shaped each stage of our approach, from problem conceptualization to data collection to model evaluation. We highlight several methodological contributions, including 1) an iterative data collection and annotation process that targets model weaknesses and interrogates framing concepts (such as who is included/excluded in "feminicide"), 2) models that explicitly focus on intersectional identities rather than statistical majorities, and 3) a multi-step evaluation process-with quantitative, qualitative and participatory stepsfocused on context-specific relevance. We also distill insights and tensions that arise from bridging intersectional feminist goals with ML. These include reflections on how ML may challenge power, embrace pluralism, rethink binaries and consider context, as well as the inherent limitations of any technology-based solution to address durable structural inequalities. This work is licensed under a Creative Commons Attribution International 4.0 License.

2022 ACM Conference on Fairness, Accountability, and Transparency

Fairness in Machine Learning (ML) has mostly focused on interrogating the fairness of a particula... more Fairness in Machine Learning (ML) has mostly focused on interrogating the fairness of a particular decision point with assumptions made that the people represented in the data have been fairly treated throughout history. However, fairness cannot be ultimately achieved if such assumptions are not valid. This is the case for mortgage lending discrimination in the US, which should be critically understood as the result of historically accumulated injustices that were enacted through public policies and private practices including redlining, racial covenants, exclusionary zoning, and predatory inclusion, among others. With the erroneous assumptions of historical fairness in ML, Black borrowers with low income and low wealth are considered as a given condition in a lending algorithm, thus rejecting loans to them would be considered a "fair" decision even though Black borrowers were historically excluded from homeownership and wealth creation. To emphasize such issues, we introduce case studies using contemporary mortgage lending data as well as historical census data in the US. First, we show that historical housing discrimination has differentiated each racial group's baseline wealth which is a critical input for algorithmically determining mortgage loans. The second case study estimates the cost of housing reparations in the algorithmic lending context to redress historical harms because of such discriminatory housing policies. Through these case studies, we envision what reparative algorithms would look like in the context of housing discrimination in the US. This work connects to emerging scholarship on how algorithmic systems can contribute to redressing past harms through engaging with reparations policies and programs.

There is a large and growing population of novice learners entering the field of working with dat... more There is a large and growing population of novice learners entering the field of working with data to tell stories, but they face many challenges related to process, methods and tools. This paper argues that activities focused on building physical manifestations of data, where some variable is mapped onto a physical artifact, are uniquely well-suited to scaffolding a process and exposing learners to methods so that they may take the next step in a learning journey. We introduce our pedagogical motivations as well as three principles that guide our work - use familiar materials, stay low-tech, and create a playground. Three case studies demonstrate how the playful activities we create based on these principles help novice learners explore advanced concepts very quickly. This work strongly suggests that creating data sculptures helps novices overcome initial barriers to learning, set expectations for a data storytelling process, and feel empowered to take the next step

Patterns

Gender-related violence against women and its lethal outcome, feminicide, are a serious problem t... more Gender-related violence against women and its lethal outcome, feminicide, are a serious problem throughout the world. Official government data on gender violence and feminicide are often absent, incomplete, infrequently updated, and contested. We draw on data feminism to situate feminicide data as missing data. Building on qualitative interviews, this study discusses the informatic work of ten activist and civil society organizations across six countries who combat missing data by producing counterdata. Activists enact alternative epistemological approaches to data science that center care, memory, and justice. Activists also face significant information challenges that increase monitoring labor and add emotional burden to reading about violent deaths. This work contributes to literature on data activism and critical data studies, proposing feminicide data practices as an important research subject. The empirical insights contribute to human-computer interaction (HCI) research, suggesting ways that the field may support and sustain the counterdata production practices of activists.

conference on computer supported cooperative work, Oct 17, 2020

Harmful data practices produce and perpetuate structural inequities that are compounded by the in... more Harmful data practices produce and perpetuate structural inequities that are compounded by the intersections of one's gender, race, ethnicity, class, sexuality, ability, and citizenship. This panel mobilizes 'critical refusal' as an organizing principle and lens for examining interlocking struggles across data domains, contexts, practices and cultures within CSCW and social computing research.

Patterns, 2022

Muchos de los artículos y las propuestas más-que-textuales que se presentaron para este número es... more Muchos de los artículos y las propuestas más-que-textuales que se presentaron para este número especial incluían tecnologías de visión artificial y otras prácticas mediadas por datos e inteligencia artificial (IA). Con el propósito de ofrecer una perspectiva crítica sobre la investigación (de diseño) basada en datos, decidimos explorar el campo emergente del feminismo de datos a través de entrevistas en línea con tres académicas y profesionales que aplican la teoría y la práctica feminista interseccional al trabajo basado en datos: Catherine DʼIgnazio, Lauren Klein y Maya Livio. Con Catherine DʼIgnazio y Lauren Klein, autoras del libro Data Feminism (2020), abordamos la idea del feminismo de datos como una manera de pensar (y actuar) sobre los datos y la ciencia de datos, la que se caracteriza por estar informada por el pensamiento feminista interseccional. Desde la necesidad de examinar y desafiar las estructuras de poder en el proceso de recopilación de datos hasta la necesidad ...

par Catherine D'Ignazio Professeure-assistante de visualisation de donnees et de medias civiq... more par Catherine D'Ignazio Professeure-assistante de visualisation de donnees et de medias civiques au Emerson College, Boston (Etats-Unis) ; kanarinka.com. La visualisation de donnees, ou infographie, est a la mode et chacun s'enthousiasme pour les nouveaux outils qui permettent d'en produire — nous en avons denombre, avec mon collegue Rahul Bhargava, plus de cinq cents. Malgre cette richesse technique, on manque souvent d'outils permettant une reflexion critique sur la politique et l'ethique de la (...)

Conference Companion Publication of the 2020 on Computer Supported Cooperative Work and Social Computing, 2020

Keywords of the Datafied State, 2024

Available at: https://datasociety.net/library/keywords-of-the-datafied-state/ There are several ... more Available at: https://datasociety.net/library/keywords-of-the-datafied-state/

There are several different definitions of missing data. While some might refer to data that is literally absent, as in statistical approaches to missing data that attempts to interpolate what might fill in the gaps,1 others, such as the artist and educator Mimi Ọnụọha, take “missing data” to mean something more political — “something [that] does not exist, but it should.”2 In the same line as Ọnụọha, our definition of missing data refers to information that goes uncounted (or otherwise unrecorded), despite social and political demands that such data should be collected and made available. Our concept of missing data may include entirely absent data, as well as data that is sparse, neglected, poorly collected and maintained, purposely removed, difficult to access, infrequently updated, contested, and/or underreported. Missing data, in the expanded definition we propose in this essay, is a political concept. On one hand, missing data can function as a challenge from civil society to formal institutions, including governments, religious institutions, and corporations. In these cases, it represents a demand from specific communities about public issues that concern society writ large. On the other hand, missing data may be actively desired and produced by marginalized groups seeking to protect information about their community and culture from the eyes of institutions. In these cases, the data is “missing” for institutions, which make a demand for information that is actively protected by and kept within a community. In this sense, missing data is also a relational concept because it implies a directionality — an informatic demand from one group or institution to another group or institution. Missing data is not always a bad thing, nor always a good thing. Instead of thinking of it normatively, the locus of analysis should be on the social context, who is making the demand to whom, and the political context for which specific information is deemed to be missing. Our definition differs from other more technical notions of missing data that may not consider or highlight the unbalanced power relationships between different social actors, such as marginalized communities and the state. In this sense, the definition of missing data proposed here explicitly includes a political demand, because the group making the demand for information is trying to charge another group or institution with the responsibility for the absence of this data. When this relates to marginalized groups making demands on the state, groups are also trying to assert the institutional neglect of the group or issue represented by the data. Given the focus on the datafied state, this article will focus particularly on missing data related to governments, where civil society groups demand that the government collect specific data or where the government demands data that communities seek to protect.