Data literacy
{{Short description|Data literacy is utilizing data to translate it into understandable information.}}
Data literacy is the ability to read, understand, create, and communicate data as information. Much like literacy as a general concept, data literacy focuses on the competencies involved in working with data. {{cite journal |last1=Acker |first1=Amelia |last2=Bowler |first2=Leanne |last3=Pangrazio |first3=Luci |title=Guest editorial: Special issue – perspectives on data literacies
|journal=Information and Learning Sciences |date=2024 |volume=125 |issue=3/4 |pages=157-162 |doi=10.1108/ILS-03-2024-266 }} It is, however, not similar to the ability to read text since it requires certain skills involving reading and understanding data.{{Cite book|title=Managing Scientific Information and Research Data|last=Baykoucheva|first=Svetla|publisher=Chandos Publishing|year=2015|isbn=9780081001950|location=Waltham, MA|pages=80}}
Data literacy refers to the ability to understand, interpret, critically evaluate, and effectively communicate data in context to inform decisions and drive action. It is not a technical skill but a fundamental capability for everyone, encompassing the skills and mindset necessary to transform raw data into meaningful insights and apply these insights within real-world scenarios.{{Cite book |last=Hanegan |first=Kevin |title=Turning Data into Wisdom: How We Can Collaborate with Data to Change Ourselves, Our Organizations, and Even the World |publisher=Kevin Hanegan |year=2021 |isbn=978-0578639871 |publication-date=January 10, 2021 |pages=31, 232 |language=English}}
Background
As data collection and data sharing become routine and data analysis and big data become common ideas in the news, business,{{cite book|editor=Hey, A. J.|editor2=Tony Hey|editor3=Tansley, S.|editor4=Tolle, K.|title=The fourth paradigm: data-intensive scientific discovery.|year=2009|publisher=Microsoft}} government{{cite web|title=Open Data Philly|url=http://opendataphilly.org/|access-date=14 June 2013}} and society,{{cite journal|author1=Na, L. |author2= Yan, Z. |name-list-style=amp|title=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|journal=Bulletin of Chinese Academy of Sciences|year=2013|volume=1|issue=16}} it becomes more and more important for students, citizens, and readers to have some data literacy. The concept is associated with data science, which is concerned with data analysis, usually through automated means, and the interpretation and application of the results.{{Cite book|title=Practical Steps to Digital Research: Strategies and Skills For School Libraries|last=Stanley|first=Deborah B.|date=2018-07-11|publisher=ABC-CLIO|isbn=9781440856723|location=Santa Barbara, CA|pages=275}}
Data literacy is distinguished from statistical literacy since it involves understanding what data means, including the ability to read graphs and charts as well as draw conclusions from data.{{Cite book|title=Data Information Literacy: Librarians, Data, and the Education of a New Generation of Researchers|last1=Carlson|first1=Jake|last2=Johnston|first2=Lisa|publisher=Purdue University Press|year=2015|isbn=9781557536969|location=West Lafayette, Indiana|pages=15}} Statistical literacy, on the other hand, refers to the "ability to read and interpret summary statistics in everyday media" such as graphs, tables, statements, surveys, and studies.
Role of libraries and librarians
As guides for finding and using information, librarians lead workshops on data literacy for students and researchers, and also work on developing their own data literacy skills.{{cite journal|author1=Koltay, Tibor |title=Data literacy for researchers and data librarians |journal=Journal of Librarianship and Information Science |date=2015|volume=49|issue=1|pages=3–14 |doi=10.1177/0961000615616450 |s2cid=36467384 |url=http://publikacio.uni-eszterhazy.hu/249/1/JOLIS_Data.pdf }}
A set of core competencies and contents that can be used as an adaptable common framework of reference in library instructional programs across institutions and disciplines has been proposed.{{cite journal |last1=Calzada-Prado |first1=Francisco-Javier |last2=Marzal |first2=Miguel-Angel |title=Incorporating Data Literacy into Information Literacy Programs: Core Competencies and Contents |journal=Libri |date=2013 |volume=63 |issue=2 |pages=123–134 |doi=10.1515/libri-2013-0010|hdl=10016/27173 |s2cid=62074807 |hdl-access=free }}
Resources created by librarians include MIT's Data Management and Publishing tutorial, the EDINA Research Data Management Training (MANTRA), the University of Edinburgh's Data Library and the University of Minnesota libraries' Data Management Course for Structural Engineers.