Today I will be introducing my MA Data Journalism students to SQL (Structured Query Language), a language used widely in data journalism to query databases, datasets and APIs.
I’ll be partly using the mapping tool Carto as a way to get started with SQL, and thought I would share my tutorial here (especially as since its recent redesign the SQL tool is no longer easy to find).
So, here’s how you can get started using SQL in Carto — and where to find that pesky SQL option. Continue reading →
A more ambitious alternative to mapping points is to map shapes: in other words, instead of each data point being placed on a specific point on a map, instead different areas on that map are drawn and coloured/labelled according to the relevant data. Continue reading →
When it comes to data visualisation, everyone loves a map. More exciting than a chart, easier than an infographic, it’s generally the first thing that journalists and journalism students alike ask: “How can we create a map?”
But just because you have some geographical data doesn’t mean you should map it.
Here’s why: maps, like all methods of visualisation, are designed for a purpose. They tell particular types of stories well – but not all of them.
There is also more than one type of map. You can map points, shapes, or routes. You can create heat maps and choropleth maps.
I’ll tackle those different types of maps first – and then the sorts of stories you might tell with each. But the key rule running throughout is this: make sure you are clear what story you are trying to tell, or the story that users will try to find. The test is whether a map does that job best. Continue reading →
Looking across the comments in the first discussion of the EJC’s data journalism MOOC it struck me that some pieces of work in the field come up again and again. I thought I’d pull those together quickly here and ask: is this the beginnings of a ‘canon’ in data journalism? And what should such a canon include? Stick with me past the first obvious examples…
Early data vis
These examples of early data visualisation are so well-known now that one book proposal I recently saw specified that it would not talk about them. I’m talking of course about… Continue reading →
Sid Ryan wanted to see if planning applications near planning committee members were more or less likely to be accepted. In two guest posts on Help Me Investigate he shows how to research people online (in this case the councillors), and how to map planning applications to identify potential relationships.
The posts take in a range of techniques including:
Scraping using Scraperwiki and the Google Drive spreadsheet function importXML
Mapping in Google Fusion Tables
Registers of interests
Using advanced search techniques
Using Land Registry enquiries
Using Companies House and Duedil
Other ways to find information on individuals, such as Hansard, LinkedIn, 192.com, Lexis Nexis, whois and FriendsReunited
If you find it useful, please let me know – and if you can add anything… please do.