Mdst 3559-01-25-data-journalism
Upcoming SlideShare
Loading in...5

Mdst 3559-01-25-data-journalism






Total Views
Views on SlideShare
Embed Views



1 Embed 14 14



Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
Post Comment
Edit your comment
  • Discuss what interested the students

Mdst 3559-01-25-data-journalism Mdst 3559-01-25-data-journalism Presentation Transcript

  • Data Journalism
    MDST 3559: DataestheticsProf. Alvarado1/25/2011
  • Business
    Course web site
    Course Collab site
    Dataesthetics S11
    Posted as a page on the course web site
    Review at end of class
  • Review
    Dataesthetics is about data design
    Data design is relevant at several levels:
    Data modeling (tables, etc.)
    Processing (code)
    Visualizing (charts, graphs, interfaces, art, etc.)
    Contextualizing (digital storytelling, arguments, presentations, etc.)
    Each level denotes a form a digital representation
  • Overview
    We look at the new field of Data Journalism
    A framing example for the course
    Accessible content
    Shows all of the levels
    Uses available tools
    A great example to imitate
    Thursday we will do our own DJ
    Acquire data and use the tools
  • What is Data Journalism?
  • How is DJ related to traditional journalism?
    i.e. news stories and op eds, aka Plain Old Journalism (POJ)
  • Relation to POJ
    Data work is supplementary to the story
    Combines data, visualization, and story-telling
    But also valuable in itself
    the publishing of interesting data is a journalistic act that stands alone
    “The Guardian curates far more data than it creates” (NJL)
    Data tells a story
    More interactive
    “there’s somebody out there who knows a lot more than you do, and can thus contribute.” (NJL)
  • What is the workflow of DJ?
  • “Find, interrogate, visualize, mash”
    Acquisition from diverse sources
    Well-formatted data sources
    Web scraping from government PDFs, web sites
    Everything ends up in Google Docs
    Data is cleaned up
    Data is interrogated, explored
    Available tools used to make visualizations
  • Example: Afghanistan IEDs
  • Example
    Get IED data from Data Blog link to Google
    Download as CSV
    Change extension to txt
    Open in Excel and save as tab delimited file
    Delete extra data
    Paste into Many Eyes
    Choose Block Histogram
  • Sources
  • Government Data
  • Tools
  • “The technology involved is surprisingly simple, and mostly free. The Guardian uses public, read-only Google Spreadsheets to share the data they’ve collected, which require no special tools for viewing and can be downloaded in just about any desired format. Visualizations are mostly via Many Eyes and Timetric, both free.”
  • TBL says the future of journalism "lies with journalists who know their CSV from their RDF, can throw together some quick MySQL queries for a PHP or Python output … and discover the story lurking in datasets released by governments, local authorities, agencies, or any combination of them – even across national borders."  Same for scholarship?
  • Types of Data
    Sources vary – often must be scraped
    CSV (‘comma separated values’) is the lingua franca
    Once it is in this form, you can do anything with it
    Actually more general—any delimited format
  • Types of Visualization
  • Homework
    Get a Google account and visit Google Docs
    Create a spreadsheet
    Create a ManyEyes account
    Read “Visualization Types”
  • Syllabus