Data literacy is the ability to read, create and communicate data and has been formally described in varying ways. Discussion of the skills inherent to data literacy and feasible instructional methods-have Emerged as data collectionBecomes routinized and talk of data analysis and Big Data HAS Become commonplace in the news, business,  government  and society in countries across the world . 
Data literacy focuses on the ability to build knowledge of data, and to communicate with others. It is related to other fields, including:
- Statistical literacy
- Media literacy
- Information literacy
- New literacies
- 21st-century skills
- A data-scientific view emphasizes the numeric, statistical nature of data as information, including “… 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. ” 
- A population-focused education view describes it as “… the knowledge of what data are, how they are collected, analyzed, visualized and shared, and is the understanding of how they are applied for benefit or detriment, within the cultural context of security and privacy. ” 
- A workforce-driven example including varying technical and digital formats by describing data literacy “… skill in finding, manipulating, managing, and interpreting data, including not just numbers but also text and images.” 
- Journalism 
- Education  
List of libraries provided data literacy
The Massachusetts Institute of Technology ‘s (MIT) Data Management and Publishing tutorial, The EDINA Research Data Management Training (MANTRA), The University of Edinburgh’ s Data Library and The University of Minnesota ‘s Data Management Course for Structural Engineers.
- Jump up^ Hey, AJ; Tony Hey; Tansley, S .; Tolle, K., eds. (2009). The fourth paradigm: data-intensive scientific discovery . Microsoft.
- Jump up^ “Open Philly Data” . Retrieved 14 June 2013 .
- Jump up^ Na, L. & Yan, Z. (2013). “Promote Data-Intensive Scientific Discovery, Enhance Scientific and Technological Innovation Capability: New Model, New Method, and New Challenges Comments on” The Fourth Paradigm: Data-Intensive Scientific Discovery. “ Bulletin of Chinese Academy of Sciences . 1 (16).
- Jump up^ Carlson, JR; Fosmire, M .; Miller, C .; Sapp Nelson, M. (2011). “Determining Data Information Literacy Needs: A Study of Students and Research Faculty” . Libraries Faculty and Staff Scholarship and Research . 23 .
- Jump up^ Crusoe, D. (November 2016). “Data Literacy defined pro populo: To read this article, please provide a little information.” The Journal of Community Informatics . 3 .
- Jump up^ Harris, Jeanne. “Data Is Useless Without the Skills to Analyze It” . Harvard Business Review . Retrieved 14 June 2013 .
- Jump up^ “Become Data Literate in 3 Simple Steps” .
- Jump up^ “Data Literacy” .
- Jump up^ “Teacher Data Literacy: It’s About Time” Data Quality Campaign