Today, we’re happy to announce a new IMLS funded project led by the Information School (iSchool) at the University of Washington. Open Data Literacy (ODL) will be a three year project focused on improving accessibility and use of open data by communities that can benefit most from public sector information. Practically, ODL will advance data literacy by developing new curriculum for iSchool students and public librarians; coordinating internships, fieldwork, and action research projects between UW and public institutions with open data initiatives, and; producing community workshops and open education resources that are freely available to the general public.
So, stay tuned! Over the coming weeks we’ll be posting updates from our on-going work with the Washington State Department of Transportation, the Seattle Public Library, the City of Seattle, and State of Washington’s Office of Innovation.
*A short note on Data, Literacy, and Data Literacy
One of the overarching goals of the ODL project is to bring some clarity as to what data literacy can and should mean in the context of open data. In a variety of contexts (education research, public administration, STEM advocacy, etc) there is little agreement about what it means to be ‘data literate’. And, this may be for good reason — both ‘data’ and ‘literacy’ are relational concept. They mean different things to different communities of practice.
Definitions of data literacy in LIS often include a laundry list of competencies, such as “…understanding what data mean, including how to read graphs and charts appropriately, draw correct conclusions from data, and recognize when data are being used in misleading or inappropriate ways.” (Carlson, J., Fosmire, M., Miller, C. C., & Nelson, M. S. 2011). In the context of STEM education, these skill-sets also include statistical competencies such as inferential reasoning, or the ability to produce basic summary statistics (Gal, 2002; Makar et al., 2011).
We believe each of these approaches — LIS and STEM education — are important to understanding data literacy in the context of openly licensed, and freely available data. However, we also believe that data literacy — in the context of public institutions and civic engagement— requires skills beyond simply obtaining, manipulating, and managing data.
In short, we see the background assumptions, ethics, values, cultures, and practices of public institutions as a reflection of the context in which data are produced and used. Therefore, the Open Data Literacy project is invested in building both conceptual and practical tools that can help diverse communities access, use, and share open data.
Calzada Prado, J., & Marzal, M. Á. (2013). Incorporating data literacy into information literacy programs: Core competencies and contents. Libri, 63(2), 123–134.
Carlson, J., Fosmire, M., Miller, C. C., & Nelson, M. S. (2011). Determining data information literacy needs: A study of students and research faculty. Portal: Libraries and the Academy, 11(2), 629–657.
Gal, I. (2002). Adults’ statistical literacy: Meanings, components, responsibilities. International Statistical Review, 70(1), 1–25.
Makar, K., Bakker, A., & Ben-Zvi, D. (2011). The reasoning behind informal statistical inference. Mathematical Thinking and Learning, 13(1–2), 152–173.