Data Literacy ~ Data Discovery and Exploration
Data Discovery and Exploration
Automatically finding, visualizing and narrating important findings within datasets (such as correlations, exceptions, clusters, links and predictions) that are relevant to users without requiring them to build models or write algorithms (Gartner, 2019, Toolkit).
The knowledge and skills to search, identify, locate and access data from a range of sources related to the needs of an organization (Statistics Canada, 2020). The methods include: summary statistics; frequency tables; outlier detection; and visualization to explore patterns and relationships in the data (Statistics Canada, 2020).
Relevant Links
These links are typically articles defining data literacy that include this theme in their definition.
Statistics Canada, Canada.ca, 2020;, Nancy Law, David Woo, Jimmy de la Torre, Gary Wong, UNESCO Institute for Statistics, 2018;, Gartner, 2019;, Apolitical, 2021;, Chantel Ridsdale, et.al., Dalhousie University, 2015;, Databilities, Data to the People, 2020;, Annika Wolff, Daniel Gooch, Jose J. Cavero Montaner, Umar Rashid, Gerd Kortuem, 2016;, Helena Sternkopf, Roland M. Mueller, University of Hawai'i at Manoa, Proceedings of the 51st Hawaii International Conference on System Sciences, 2018;, Andreas Grillenberger, Ralf Romeike, Proceedings of the 13th Workshop in Primary and Secondary Computing Education, 2018;, Edith Gummer, Ellen B. Mandinach, Teachers College Record, 2015;