Martin Stabe, interactive producer, Financial Times


Published on

Published in: Technology, News & Politics
1 Like
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • Councils across the country are spending £200m of the £2.6bn they collectively hold in spare cash. But analysis by the FT reveals that councils facing the strongest ballot box pressure on May 5 are planning to spend the spare cash at more than three times the rate of those with no election. “ Drawing on reserves to try and win votes could well mean disappointing voters later as that can’t be a sustainable way of funding services,” Matthew Sinclair, director of the Taxpayers’ Alliance, said. “They could easily just be delaying a more severe reckoning when it becomes clear tough decisions were ducked ahead of a vote.” A fierce dispute has broken out between Labour and the Conservatives over the use of council reserves, with local government minister Grant Shapps accusing Labour councils of “stashing away” billions while making harsh cuts to services to score political points. However, the FT analysis suggests a stronger determinant of whether a council is spending or hoarding its reserves is the timing of its next encounter with the electorate. Government data on planned council spending for 2011-12 show those with elections in May are spending their reserves at the fastest rate. Those councils who have “all-out” elections, where all councillors, as opposed to just half or a third, face the vote, are on average dipping into 8 per cent of their reserves. The figure falls to 2 per cent at the 83 English councils, controlled by one of the three main parties, where no election is taking place. The trend is starkest at Labour councils, where the party’s 18 councils with elections in May plan to spend an average 6 per cent of their reserves this year. The majority of the 35 without elections plan either to add to their reserves, or leave them untouched. Conservative-run councils are, on average, raiding their reserves the most and even those with no election this year plan to spend on average 5 per cent of their reserves. David Sparks, vice-chairman of the Local Government Association which represents more than 400 councils across England and Wales, defended the spending. “ Politicians have always managed finances to win elections,” he said. “If they are coming up to elections, they will do everything they can – that’s what politicians do and we might as well recognise that. “ They will marshal their financial reserves so they will coincide with the electoral cycle.”
  • Source:
  • (31x268 records)
  • Crowdsourcing input
  • Crowdsouring output to generate buzz (and a second-week story)
  • Big push for Istanbul
  • Martin Stabe, interactive producer, Financial Times

    1. 1. The data workflow past, present, future Martin Stabe Financial Times News:Rewired May 27, 2011
    2. 3. “Computer assisted reporting” <ul><li>As the phrase suggests, harks to an era when computerised analysis was rare </li></ul><ul><ul><li>History can trace to 1950s, esp elections </li></ul></ul><ul><ul><ul><li>Key examples from 1980s, esp US legal stories </li></ul></ul></ul><ul><ul><li>Bringing social science methods to journalism </li></ul></ul><ul><ul><ul><li>Statistics </li></ul></ul></ul><ul><ul><ul><li>Polling </li></ul></ul></ul><ul><ul><ul><li>GIS </li></ul></ul></ul><ul><ul><ul><li>Social network analysis </li></ul></ul></ul>
    3. 4. “Enterprise Joins” <ul><li>“Enterprise” </li></ul><ul><ul><li>US journo jargon for a story between ‘off-diary’ and ‘investigative’ </li></ul></ul><ul><li>“Join” </li></ul><ul><ul><li>Database jargon for combining records from two tables </li></ul></ul><ul><ul><li>Using common content to locate common fields across tables </li></ul></ul><ul><ul><li>May be complex, using ‘lookup tables’ </li></ul></ul>
    4. 5. “Enterprise Joins” <ul><li>In other words, finding stories by linking two datasets, esp those not originally intended to be linked </li></ul><ul><li>Often centred on common geographical records used across government </li></ul><ul><ul><li>Postcodes (very good in UK) </li></ul></ul><ul><ul><li>Statistical output areas </li></ul></ul><ul><ul><li>Administrative or electoral geographies </li></ul></ul>
    5. 10. “Interviewing data” <ul><li>Database queries are like questions to an interviewee </li></ul><ul><li>Data can be a reluctant source. “Dirty” data: Artifacts of </li></ul><ul><ul><li>data entry errors </li></ul></ul><ul><ul><li>Lack of coding conventions </li></ul></ul><ul><ul><li>Esoteric systems for storing stray data </li></ul></ul><ul><ul><li>Discrete collection (eg local authorities, government departments) </li></ul></ul>
    6. 14. Adding interactivity <ul><li>“ Data is only useful if it is personal – I want to find out about schools in my area, restaurants near me and so on – or when it reveals something remarkable.” - Bella Hurrell </li></ul>
    7. 15. “The canvas for CAR” <ul><li>“ The Web is the canvas for CAR, better than any other platform we’ve come up with as an industry. It has every advantage that should be available to the CAR practitioners, including unlimited depth, the ability to customize or personalize and the luxury of designing a database so that it will truly be useful to readers. Some papers get this, or are beginning to realize it.” – Derek Willis </li></ul>
    8. 19. “A fundamental change” <ul><li>“ Newspapers need to stop the story-centric worldview. … So much of what local journalists collect day-to-day is structured information : the type of information that can be sliced-and-diced, in an automated fashion, by computers. Yet the information gets distilled into a big blob of text -- a newspaper story -- that has no chance of being repurposed.” </li></ul><ul><ul><li>Adrian Holovaty </li></ul></ul>
    9. 21. The data workflow <ul><li>Obtain data </li></ul><ul><ul><li>Open data releases </li></ul></ul><ul><ul><li>Advanced search </li></ul></ul><ul><ul><li>Screen scraping </li></ul></ul><ul><ul><li>Freedom of Information Act </li></ul></ul><ul><ul><li>APIs, Web </li></ul></ul><ul><li>Clean, analyse and warehouse data </li></ul><ul><ul><li>Excel </li></ul></ul><ul><ul><li>Google Refine </li></ul></ul><ul><ul><li>Google Fusion Tables </li></ul></ul><ul><ul><li>Visokio Omniscope (or Tableau) </li></ul></ul><ul><ul><li>Stata (or SPSS, SAS, R) </li></ul></ul><ul><ul><li>ArcView (or other GIS tools) </li></ul></ul><ul><ul><li>MySQL (or other database manager) </li></ul></ul><ul><li>Publish Data </li></ul><ul><ul><li>Google Fusion Tables </li></ul></ul><ul><ul><li>Static XML (via FTP) </li></ul></ul><ul><ul><li>Dynamic XML (via PHP) </li></ul></ul><ul><ul><ul><li>Parsed by ActionScript in Flash </li></ul></ul></ul><ul><ul><ul><li>Parsed by JavaScript </li></ul></ul></ul>
    10. 22. The data workflow <ul><li>Visualising complex dataset </li></ul><ul><ul><li>Bank debt exposure data </li></ul></ul><ul><ul><ul><li>Monitor site for updates </li></ul></ul></ul><ul><ul><ul><li>CSV source </li></ul></ul></ul><ul><ul><ul><li>Clean in Excel </li></ul></ul></ul><ul><ul><ul><li>Import to MySQL database </li></ul></ul></ul><ul><ul><ul><li>Generate SQL query </li></ul></ul></ul><ul><ul><ul><li>Publish XML </li></ul></ul></ul><ul><ul><ul><li>Parse with ActionScript </li></ul></ul></ul><ul><ul><ul><li>Publish with Flash </li></ul></ul></ul>
    11. 24. <ul><li>NewsrewiredBIS_monitoring.PNG </li></ul>
    12. 33. The data workflow: the future <ul><li>Shifted from static to dynamic output </li></ul><ul><li>Next step is automating the input side </li></ul><ul><ul><li>Source APIs </li></ul></ul><ul><ul><li>Web scraping </li></ul></ul><ul><ul><li>“The web as database” </li></ul></ul>
    13. 36. The data workflow: the future <ul><li>Shifted from static to dynamic output </li></ul><ul><li>Next step is automating the input side </li></ul><ul><ul><li>Source APIs </li></ul></ul><ul><ul><li>Web scraping </li></ul></ul><ul><ul><li>“ The web as database” </li></ul></ul><ul><li>Adding social media on input and output </li></ul><ul><ul><li>Crowdsourcing (Guardian MP expenses) </li></ul></ul><ul><ul><li>Games and viral promotion (NYT budget cutter) </li></ul></ul>
    14. 38. The data workflow: the future <ul><li>Shifted from static to dynamic output </li></ul><ul><li>Next step is automating the input side </li></ul><ul><ul><li>Source APIs </li></ul></ul><ul><ul><li>Web scraping </li></ul></ul><ul><ul><li>“ The web as database” </li></ul></ul><ul><li>Adding social media on input and output </li></ul><ul><ul><li>Crowdsourcing (Guardian MP expenses) </li></ul></ul><ul><ul><li>Games and viral promotion (NYT budget cutter) </li></ul></ul>
    15. 41. Cleaning data
    16. 43. <ul><ul><li> </li></ul></ul><ul><ul><li> </li></ul></ul><ul><ul><li>[email_address] </li></ul></ul><ul><ul><li>@martinstabe </li></ul></ul>