Finding Stories in Data

Size: px

Start display at page:

Download "Finding Stories in Data"

Holly Morrison
5 years ago
Views:

1 Finding Stories in Data David

2 Improve understanding of how to source, analyse and visualise data to discover insight and tell stories. Aim

3 Aims Identify a number of data driven stories. Understand the stages in creating an open data story. Create your own open data story using analysis tools. Visualise your findings using an interactive graphic.

4 Examples: Telling stories with data

7 Data is a source

8 Two main methods of using data as a source 1. Story first data used to enhance, fact check, dig deeper 2. Data first story found/ presented through data analysis

9 Story, then data

10 Data then story

11 Thanks to David Ottewell Head of Data Journalism Trinity Mirror (Regionals) for permission in using this slide

12 Thanks to David Ottewell Head of Data Journalism Trinity Mirror (Regionals) for permission in using this slide

13 Thanks to David Ottewell Head of Data Journalism Trinity Mirror (Regionals) for permission in using this slide

14 Using data as a source must have visualisation

Using data as a source (necessarily) big investigation http://ampp3d.

15 Using data as a source (necessarily) big investigation

16 Data for education

18 h"p:// new- york/

19 Self discovery

20 Show me the money

21 LFB Fire Station Closures

22 Data discovery patterns

23 Finding data on the web (of documents) Government data Google advanced Aggregators and portals Scraping

24 Government data

25 data.gov.xx

26 Google advanced site: Get results only from certain sites or domains link: Find pages that link to a certain page related: Find sites similar to one you already know filetype: Find certain file types only

27 Aggregators and portals Collect together data from across the web into one place. enigma.io transportapi

28 Scraping If you can t obtain usable data (csv, xls) then you may have to resort to scraping. scraperwiki.com import.io

29 Finding data on the web (of data) 1. Add random extensions (.xml,.json,.csv etc) 2. Look for alternative links (rss feeds etc) 3. Look for embedded data 4. Do some content negotiation 5. Spot the API 6. Scrape (or search google again) How the web should work, but people forgot that Tim put this in when he invented it!

30 Duck typed data If it looks like a duck and quacks like a duck, then it s probably a duck. Basically, keep an eye out for tables, lists and other stuff that looks like data.

31 1. Adding random extensions UK Trade Tariff BBC Music and Programmes Try using the following:.csv.json.xml.rss.rdf

32 2. Look for alternative links Scroll down!

33 2. Look for alternative links RSS

csv etc) informa*on if there is *me. 2. Look for alternative links (rss feeds etc) 3.

34 Finding data on the web (of data) Techniques 3-5 are not covered in this session. Please 1. Add ask random your trainer extensions for more (.xml,.json,.csv etc) informa*on if there is *me. 2. Look for alternative links (rss feeds etc) 3. Look for embedded data 4. Do some content negotiation 5. Spot the API 6. Scrape (or search google again)

35 Exercise: Find a story File:Stöwer_Titanic.jpg

36 1. Go through (some of) the Checklist for Exploring Data 2. Create a pivot table 3. Five ideas for finding a story q q q Choose one story you want to tell Create a headline (Bonus: Create a chart, e.g. with datawrapper.de) Exercise

37 2012/may/24/data-journalism-punk

38 The data percolator

39 Data percolation: A model of data preparation and analysis Gather Prepare Produce See also: the Data Journalism Handbook

40 Data percolation: A model of data preparation and analysis Gather Prepare Produce

41 How should I budget my time? Explore Gather Prepare Produce

45 How should I budget my time? Gather Prepare Produce 1.1 FIND reliable data sources 1.2 Understand your RIGHTS 1.3 Visualise and UNDERSTAND your data 2.1 CLEAN your data 2.2 TRANSFORM it where useful 2.3 COMBINE it with other data sets 3.1 REDUCE and find the story 3.2 Think and understand the CONTEXT 3.3 Do your results pass a SENSE-CHECK?

46 Time planning Gather Produce Prepare 2.1 CLEAN 2.2 TRANSFORM 2.3 COMBINE 2.4 ENRICH 2.5 ANALYSE

47 Tools Excel Refine Datawapper.ie Plot.ly CartoDB d3.js

48 Chose one or more of the following to try: q q q q q Data cleaning in Refine Enriching data to discover insight (in Refine) Creating interactive graphics in Plot.ly Creating interactive maps in cartodb. Exercises Building you own interactive website and d3.js visualisation.

49 Thank You David

Mail. Having your mail stored in the cloud means you can access it just about anywhere on just about any device with an internet connection.

Mail. Having your mail stored in the cloud means you can access it just about anywhere on just about any device with an internet connection. Microsoft Office 365 is a set of cloud services available free to education entities from Microsoft. With your Microsoft Office 365 account, you receive access to the following services: For now, we are