This document discusses how non-programmers can work with data through various tools and platforms. It mentions Google Spreadsheets and APIs as ways to acquire, represent, and cleanse data without programming skills. Visualization tools like Google Refine, Stanford Data Wrangler, and Many Eyes are presented as options for analyzing structured and unstructured data through visual and human-readable representations.

1. Messing with Data Tony Hirst, Dept of Communication and Systems, The Open University #lak11

2. How can non-programmers do the sort of things that we might normally think we need a developer to do?

3. “Data Is A Dish Best Served Raw” http://eagereyes.org/

4. ND

5. DiscoveryAcquisition as dataRepresentationCleansing(Visual) Analysis

6. APIs, screenscraping and standardised document formats

7. RepresentationStructured OR or unstructuredHuman readable (text) or opaque document format?

8. Google Spreadsheets as a database

10. =QUERY('ISO Country Codes'!A2:B268, "select A,B where A contains 'FRANCE' limit 1")))

12. Many Eyes

16. Visualising Networks

22. [ Context – resource discovery in special interest areas ]

23. http://flic.kr/p/9mvfHh

27. Put the data to work: Google CSEblogroll

29. More views ondelicious…

30. Graph of folk who follow three or more people (ish) who tweeted a link to soti/rin blog post

32. Data Cleansing

33. Google Refine

34. Stanford Data Wrangler

35. Google Analytics

36. http://code.google.com/apis/analytics/docs/gdata/gdataExplorer.html http://bit.ly/fzj9yv

38. OUseful.info