Fake news or not fake news?

The world of social media, and the ever increasing volumes of information available on the internet has led to the crisis of so called ‘Fake News’ – information and data being misrepresented, or even just mis-stated to push one agenda or another. So how do you judge the legitimacy of what you are reading?

The term digital literacy has been coined to describe “the ability to use information and communication technologies to find, evaluate, create, and communicate information, requiring both cognitive and technical skills.” (American Library Association)

There is a fantastic tutorial from the Open University that uses the acronym PROMPT to lead you through assessment of any sort of information, digital, data or otherwise. There is also fullfact.org which is an independent fact-checking charity based in the UK which focusses on checking statistics and data cited in news and the media.

Finally I would recommend looking at digital-literacy.org.uk which offers a whole curriculum, aimed at promoting digital literacy to children throughout their education. While this is a university, and there is a certain amount of assumed knowledge, the resources are still very useful and go into significant amounts of detail!

Data Literacy

Often thought of as a sub-division or a specialist application of digital literacy, data literacy means having full confidence to read, work with, analyze and argue with data, understand and be able to access quality data as well as combine and interrogate data and findings.

The reasoning behind the link often made is clearly shown in this page of the journalism handbook which walks you through some thinking exercises with commonly cited data types in the media.

The next steps in data literacy beyond the ability to recognise questionable data presentation and query statistics is to work with data. There are two very good free sources of data literacy training, Qlik has a very good free Data Literacy course that covers everything from Data Fundamentals to Advanced Analytics skills, and then there is the Data Carpentry website that aims to build coding and data analysis skills beyond the Qlik programme by providing training into specific data analysis techniques such as working with Geospatial data or using Python and R to analyse data.