Edit page in Livemark
(2023-09-20 07:42)

What is Data Literacy? 📖

The ability to read, understand, create, and communicate with data.

-- Wikipedia

Data literacy (datalit) encompasses “the ability to collect, manage, evaluate, and apply data, in a critical manner” (Ridsdale et al 2015).

Photo by LuidmilaKot

Much of this is already taught in grade school, as part of mathematics and science curriculum. How do you see your own datalit skills?

We generally see data literacy as a broad field with complementary skills in economics, linguistics, and more.

There are several models, such as the competencies matrix by Ralph Krüger, which suggest how data literacy should be taught and applied. A useful mental model is the DIKW pyramid, which I extended here to differentiate between "structured data" (secondary data, in science) and "raw measurements" (primary data).

Data Cake

Image by Epic Graphic

A good metaphor is cooking. If data is the raw ingredient and we manage to produce tasty information, then knowledge is what you gain when you consume it... Wisdom is gained through staying fit - with a healthy information diet!

What is open data? 🗺️

"We are increasingly reliant on data to make decisions." Open Knowledge is a global non-profit promoting a healthy, well-balanced relationship to data. They are one of many organizations you can turn to for advice on data literacy.

Opendata.ch is the Swiss chapter of Open Knowledge, running events and supporting a community of practitioners and institutional members since 2012. The Data Café and Hackdays on a variety of topics help to boost data literacy around the country. They also help to promote jobs and opportunities for startups and established companies.

Opendata.swiss is the central project of the Swiss federal government to support a high standard of open data publication and use. Run by the Federal Statistical Office, the teams works closely with other departments, cantons and municipalities, stakeholders in the industry and community, and promotes outstanding examples of data reuse.

There are many other interesting organizations deserving of mention, which support data literacy in particular areas such as OpenStreetMap (mapping), Wikimedia (open content, linked data), AlgorithmWatch (privacy, ethics), ONIA (hardware, networks), ...