Critically Evaluating Data Sources

Evaluating Data Sources | Visualizing and Mapping Data Responsibly | Data Literacy - Academic Literature | Other Sources

Evaluating Data Sources

Visualizing and Mapping Data Responsibly

Data Literacy - Academic Literature:

Fotopoulou, A. (2020) Conceptualising critical data literacies for civil society organisations: agency, care, and social responsibility. Information, Communication & Society, March. The primary purpose of the article is to move forward the debate around how to conceptualise data literacy – and to question how far the concept is useful in the first place. The article draws on empirical research and starts from the premise that it is imperative to develop frameworks and training schemes that enable civil society actors and publics more generally to use open data, to make data more relevant to stakeholders, and to support their engagement in policy debates around datafication.

Gal, I., & Ograjensek, I. (2017). Official statistics and statistics education: Bridging the gap. Journal of Official Statistics, 33(1), 79-100. doi:  This article aims to challenge official statistics providers and statistics educators to ponder on how to help non-specialist adult users of statistics develop those aspects of statistical literacy that pertain to official statistics.

Gibson, J. P., Mourad, T., (2018). The growing importance of data literacy in life science education. American Journal of Botany. 105(12), 1953-1956. To prepare students for the data‐rich future that undoubtedly lies ahead, it is imperative that STEM educators rise to meet this challenge and promote the development of strong data literacy in our students.

Kjelvik, M.K., Schultheis, E.H. (2019). Getting Messy with Authentic Data: Exploring the Potential of Using Data from Scientific Research to Support Student Data Literacy. CBE Life Sci Educ. Jun;18(2):es2. doi: 10.1187/cbe.18-02-0023.  Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise when students are given opportunities to work with authentic data from scientific research.

Sapp Nelson, M. R., (2020). Adding Data Literacy Skills to Your Toolkit. Libraries Faculty and Staff Scholarship and Research. Paper 230. The articles in this issue of Information Outlook [contain]… advice about websites that offer training courses about data, an overview of the seven baseline competencies for data literate employees, and a tool that can help librarians identify which skills to learn. The articles in this issue offer an abundance of useful advice to librarians and information professionals interested in becoming—and helping their clients become—data literate. 

Yoon, A, Copeland, A. Toward Community‐Inclusive Data Ecosystems: Challenges and Opportunities of Open Data for Community‐Based Organizations. J Assoc Inf Sci Technol. 2020; 1– 16. . The benefits of open data for helping to address societal problems and strengthen communities are well recognized, and unfortunately previous studies found that smaller communities are often excluded from the current data ecosystem because of existing technological, technical, cognitive, and practical barriers. This study aims to investigate the process of communitiesʼ data use for community development and decision‐making—focusing on the opportunities and challenges of data for communities. 

Other Sources