Today's guest post is by Ben Chiewphasa, Economics and Data Librarian with the Navari Family Center for Digital Scholarship, part of University of Notre Dame's Hesburgh Libraries.
I am inspired by the growing number of academic librarians who are actively pursuing community engagement work, facilitating high-impact experiential learning in information literacy through civic engagement and service. These librarians are continually developing services built around engagement and I even noticed that some libraries have even gone as far as to hire/seek out specialized information professionals tasked with primarily coordinating programs that recognize the civic dimension of universities. The case for embedding community engagement in academic libraries is compelling—ranging from libraries already designated as active spaces for community convergence as well as libraries’ technological infrastructure that supports the preservation of community information. As someone who works in the realm of digital scholarship, I see so much potential in incorporating data literacy within the context of community engagement.
So you might have already heard about data literacy (or maybe you haven’t), but what exactly is it? And how can it align with community engaged efforts and initiatives? According to Data Pop-Alliance, the term can be traced to the “Data Revolution” happening all around us. Various advocates, policy makers, etc. see potential in fostering active citizenry through data sciences skills-training. We are seeing the rise in nonprofits such as Girls Who Code, Code for America, etc. that focus on tackling the digital divide by providing code programs for targeted populations. Data Pop-Alliance’s Rahul Bhargava et al. (2015) give one of the most comprehensive and compelling definitions of data literacy which is grounded in five principles: 1) “desire and ability” includes the recognition that technology can help foster opportunities for exploring human intent and capacity; 2) the concept of data literacy “ability” as a spectrum—in other words, we should avoid pitting the data literate against the data illiterate; 3) seeing “data” as individual facts, statistics or pieces of information; 4) data literacy is actionable and goal-oriented ; 5) “Through or about data” suggests that data literacy is not only about data analysis, but also looks at how individuals interrogate and interact with social structures.
Examples of Data Literacy & Community Engagement Efforts
I am a new-ish Economics and Data Librarian with the Navari Family Center for Digital Scholarship (Hesburgh Libraries, University of Notre Dame). Before my arrival, the center had already collaborated with three local partners—the City of South Bend, enFocus (a local non-profit) and the St. Joseph County Public Library—on a “Civic Switchboard” subaward (IMLS LG-70-17-0146-17) to conduct an assessment of the data literacy needs of local non-profit organizations. The project’s goal was to strengthen these extant partnerships, enabling prior work to advance to the next step by supporting the data training needs of local organizations. Denise Riedl, Chief Innovation Officer for the City of South Bend, reminds us that the South Bend region houses a vibrant data ecosystem consisting of “governments, university researchers, nonprofits, religious institutions, civic technologists, start-ups, community organizers, and educators. Each of these stakeholders plays a different role; some crunch numbers, some release open data, some teach skills, and others focus on putting data insights into action in their neighborhoods.” Ultimately, a data literate community can enhance communication which, aspirationally, helps our community address food access, lower risk of lead contamination, systemically coordinate regional grants, and so on.
Here’s another example of a community engagement effort that links together data literacy, South Bend, and the library: The summer of 2020 saw the beginning stages of a fruitful partnership with Notre Dame’s Center for Civic Innovation (CCI), Lucy Family Institute for Data and Society, and the Navari Family Center for Digital Scholarship in building a Michiana region-based data intermediary resource called dataMichiana. The program affiliates met with local advocates and professionals who are knowledgeable in the areas of health, education, law, and race. During that same summer, a team of dataMichana interns focused their efforts on visualizing how housing instability can impact educational outcomes. And in 2021, another intern team created storyboards to visualize and contextualize school mobility rates against income and racial data within the Michiana region. The interns were supported by Matthew Sisk (GIS Librarian) with the Navari Family Center for Digital Scholarship and Danielle Wood with CCI. Ben Brubaker from Riley High School served as project lead and Elizabeth Maradik (City of South Bend Community Investment) acted as a mentor.
The Case for Data Literacy & Community Engagement
Having been only in my current role for less than a year, I am still getting my footing—recognizing, too, that I started my new job amid a pandemic. As a data librarian, I provide information literacy, data analysis, and data visualization support via consultations as well as workshops and library instruction. Being actively embedded in the “data space,” I define, collect, manipulate, analyze, present, and share data. I recognize that data is not immutable nor is it ever neutral—data is perpetually influenced by the various systems it operates under. Data are byproducts of unequal social relations and, therefore, context is necessary for conducting ethical analysis. As Catherine D’Iganzio and Lauren F. Klein eloquently point out via Data Feminism, there is truly no such thing as “raw” data—rather, data has been “cooked” by all sorts of systems: how the data is made accessible/findable, how it was collected, why it was collected, sampling biases (i.e., data from Instagram generally skews young), and so forth. Active citizenry can help restore context to “cooked” data existing within our communities. Without understanding a community’s composition through engagement, there can be misrepresentation, misunderstandings, miscommunication, and missed opportunities—rendering community data as harmful rather than a source for good.
Framing Our Work around Asset-Based Community Development
My colleague, Matthew Sisk, and I would like to continue to strengthen existing relationships with the City of South Bend to continue to help solidify data sciences skills-training in a meaningful and impactful manner. At this juncture, we are currently in communication with our City of South Bend partners to strategize next steps in providing data skills training opportunities for nonprofits. Moving forward, I’d like for the library’s role to be intentional about Asset-Based Community Development (ABCD).
ABCD provides a framework for organizations to acknowledge existing resources as catalysts for self-directed community change (Kretzmann & McKnight, 1993). As a “grassroots model that builds on the assets, or skills and talents of local residents, associations, and organizations” (Edwards et al., 2013, p. 24), we would like community engaged data literacy initiatives to identify our community members as experts within their respective settings. ABCD’s ethos nicely aligns with Rahul Bhargava et al.’s (2015) plea to not pit the “data literate” against the “data illiterate.” ABCD goes against the assumption that the investment in outside agents is necessary to solve in-house deficiencies. Rather, we should focus our attention towards the positive/inspirational fabric already woven within a given community. ABCD sees internal people as active citizens (instead of “clients”) who have sole autonomy in community development (Mathe & Cunningham, 2003).
Data literacy coupled with the open data movement empowers communities and encourages active citizenry. However, the reality is that most people are far removed from engaging with their local, community-level data via a host of barriers ranging from the technological, cognitive, and logistical. For example, the Civic Switchboard subaward report (IMLS LG-70-17-0146-17) notes that South Bend non-profit organizations rated talent capacity and financial resources as the major obstacles that prevent them from accomplishing ambitious goals. Nevertheless, we cannot disregard/forget that these non-profit organizations are best positioned to articulate authentic, real-world problems and potentially come up with real-world solutions. Applying data science skills to actual community case studies allows learners to connect new information and knowledge with current, personally-relevant situations. Authentic tasks also help to set the tone for realistic expectations, opening up conversation on existing limitations—either from tool constraints and/or the state of local data availability or access. By focusing on existing problems and authentic tasks, the vision is to empower participants to collect and analyze relevant data in efforts to affect positive change.
A Graduate Student Service-Learning Component?
Although we are still in the planning/brainstorming stages of truly jumpstarting a community engagement effort centered on data literacy and local non-profits within the South Bend (Indiana) region, we also see potential in implementing a service-learning component for PhD students/candidates—specifically those belonging in the Navari Family Center for Digital Scholarship Pedagogy Fellowship Program, a new program that I led in launching this academic year. This program is an opportunity for Notre Dame PhD students to build their instructional expertise and experience related to digital scholarship in support of enhancing competitiveness on the job market. Fellows gain experience in evidence-based and innovative instructional methods, collaborative teamwork, communicating their research and scholarly interests outside of their discipline, and build digital skills (including, but not limited to geographic information systems, data analysis/visualization, natural language processing, and discipline-specific tools). I currently co-lead this program with my colleague Arnaud Zimmern and we work with a thoughtful and impressive cohort who continue to impress us day-by-day.
In order to create synergies between this graduate student program and community-engaged data literacy efforts, we must resist being opportunistic—rather than irresponsibly dropping PhD students into a service-learning opportunity, we will first need to critically think through whether the inclusion of graduate students as instructors/co-creators of data literacy curriculum is compatible with community needs; and if, in fact, their inclusion is compatible, the program has the potential to foster stewards of change for the next generation of community-engaged scholars and instructors. We would facilitate a space that allows tomorrow's faculty members to problem solve beyond traditional systems of higher education by, for example, figuring out how to best invite (and compensate) our community experts to participate more fully in co-authorship and curriculum development.
We live in a data-driven world and librarians are well positioned to help students/patrons/learners find, access, critically assess, and use data ethically. But to sincerely add or (many a time) restore context to data which surrounds us, we’ll need to actively and intentionally engage with our communities. By doing so, we avoid subjugating knowledge, making assumptions that current “best practices” are universally applicable (see the CARE Principles for Indigenous Data Governance), and so forth.
Bhargava, R., Deahl, E., Letouzé, E., Noonan, A., Sangokoya, D., & Shoup, N. (2015). Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of Data. https://dspace.mit.edu/handle/1721.1/123471
D’Ignazio, C., & Klein, L. F. (2020). Data feminism. The MIT Press.
Edwards, J. B., Robinson, M. S., & Unger, K. R. (2013). Transforming libraries, building communities: The community centered library. Scarecrow Press.
Kretzmann, J. P., & McKnight, J. L. (1993). Building communities from the inside out: A path toward finding and mobilizing a community’s assets. The Asset-based Community Development Institute.
Mathie, A., & Cunningham, G. (2003). From clients to citizens: Asset-based Community Development as a strategy for community-driven development. Development in Practice, 13(5), 474–486. https://doi.org/10.1080/0961452032000125857