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An (incomplete) checklist for making #geodata #visualizations in data journalism | #ddj #dataviz

An (incomplete) checklist for making #geodata #visualizations in data journalism | #ddj #dataviz | e-Xploration | Scoop.it
luiy's insight:

MAPPABLE CHEAT-SHEET

An (incomplete) checklist for making geodata visualizations in (data-driven) journalism.

 

ALWAYS ASK YOURSELF FIRST:

Is a map really the best way to visualize the data set?

 

DATA HANDLING

 

- Got all geographic elements right? (especially borders & place names)

 

- Check the correct position of geocoded and self drawn map elements (thus preventing mistakes from misused spatial reference systems)

 

- Have all outliers and duplicates been eliminated? Correctly dealt with incomplete data entries?

 

- Have data entries that are not necessary for the final visualization been removed?Have the values been normalized (e.g. by population data)? .........

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#Drone Journalism Lab | #datajournalism #augmented

#Drone Journalism Lab | #datajournalism #augmented | e-Xploration | Scoop.it
Links, thoughts and research into using drones, UAVs or remotely piloted vehicles for journalism at...

Via Pierre Levy
luiy's insight:
About the Lab 

The College of Journalism and Mass Communications at the University of Nebraska-Lincoln established the Drone Journalism Lab in November 2011 as part of a broad digital journalism and innovation strategy. Journalism is evolving rapidly, and journalism education must evolve with it, teaching new tools and storytelling strategies while remaining true to the core principles and ethics of journalism. The lab was started by Professor Matt Waite as a way to explore how drones could be used for reporting.

 

In the lab, students and faculty will build drone platforms, use them in the field and research the ethical, legal and regulatory issues involved in using pilotless aircraft to do journalism.

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Catherine Pascal's curator insight, March 16, 9:08 AM

  Signaux faibles et réalités avec conséquences .... A suivre de près .... !

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Global Investigative Journalism Network » #DataJournalism

Global Investigative Journalism Network » #DataJournalism | e-Xploration | Scoop.it

Via Pierre Levy
luiy's insight:

As our governments and businesses become increasingly flush with information, more and bigger data are becoming available from across the globe. Increasingly, investigative reporters need to know how to obtain, clean, and analyze “structured information” in this digital world. 


Here is a list of resources to get you started, but we want to keep updating our community with the best resources available. Do you know of a great data tutorial we haven't listed, perhaps in a language other than English? Help us keep this resource guide comprehensive by sending your favorite resource to: kate.willson (at) gijn (dot) org.

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Journalism in the Age of Data I #dataviz #datajournalism

Journalism in the Age of Data I #dataviz #datajournalism | e-Xploration | Scoop.it
How journalists are coping with a flood of information by borrowing data visualization techniques from computer scientists, researchers and artists.
luiy's insight:

Journalists are coping with the rising information flood by borrowing data visualization techniques from computer scientists, researchers and artists. Some newsrooms are already beginning to retool their staffs and systems to prepare for a future in which data becomes a medium. But how do we communicate with data, how can traditional narratives be fused with sophisticated, interactive information displays?

 

Watch the full version with annotations and links at datajournalism.stanford.edu.

Produced during a 2009-2010 John S. Knight Journalism Fellowship at Stanford University.

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What Data #Journalists Need to Do Differently | #ddj #bigdata

What Data #Journalists Need to Do Differently | #ddj #bigdata | e-Xploration | Scoop.it
Relying too heavily on the same sources leaves important stories untold.
luiy's insight:

The role of the data journalist has increased dramatically over the last decade.The past few months have seen the launch of several high-profile “data journalism” or “explanatory journalism” websites in the U.S. and the UK – such as Nate Silver’s recently relaunched and somewhat controversialFiveThirtyEight; Trinity Mirror’s ampp3d, a mobile-first site that publishes snappy viral infographics;The Upshot from The New York Times, which aims to put news into context with data; and Vox, where former Washington Post blogger Ezra Klein leads a team that provides “crucial contextual information” around news. The debates (pro and con) around these projects have brought data journalism out of its niche in digital media conferences and trade publications into the limelight.

 

These new media outlets have been received with both praise and criticism. Guardian journalist James Ball, who has been closely associated with the use of data for journalism – from his work with Wikileaks to the “Offshore Leaks” investigations – recently offered an interesting analysis of these developments. He points out a number of limitations in many of these data journalism projects — from the lack of transparency about their data, to the perpetuation of gender inequality among media professionals (“still a lot of white guys”), to the conspicuous absence of one of journalism’s most essential functions: the breaking of news.

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Reuters Connected China Promo | #Datajournalism

Connected China is an interactive tool tracking thousands of people, institutions and connections that form China's elite power structure. For iPad and deskt...
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Inside the $400-million #political network backed by the Kochs | #dataviz

Inside the $400-million #political network backed by the Kochs | #dataviz | e-Xploration | Scoop.it

In an analysis of 2011 and 2012 tax filings, The Washington Post and the Center for Responsive Politics found that a coalition of nonprofit groups backed by a donor network organized by the billionaire industrialists Charles and David Koch raised more than $400 million in the last election cycle. Much of the money was distributed to a maze of limited-liability companies affiliated with the nonprofits, which used some of their resources to turn out conservative voters and run ads against President Obama and congressional Democrats.


Via Claudia Mihai
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Information Geographies » World-wide news web | #dataviz #SNA

Information Geographies » World-wide news web | #dataviz #SNA | e-Xploration | Scoop.it
luiy's insight:

Data

The map uses data from the  Global Database of Events, Language, and Tone (GDELT), which is an initiative aiming to provide a “realtime social sciences earth observatory”, by creating a freely available catalog of events derived from news stories. The database is compiled from stories in media outlets from almost every country in the world. Any story can contain more than one event, and events are automatically parsed out of news stories using a text analysis program called Tabari and encoded using a schema called Cameo.

A large portion of these events (140 million out of 250 million listed events) contains both a location of where the event happened and locations of the two primary actors involved. The Tabari algorithm associates events that it has already picked out of an article with geographic locations mentioned in the same text (by looking at verb usage in surrounding sentences). You can read the introductory paper on GDELT (Leetaru and Schrodt, 2013) for more on the specific geocoding methods employed.

 

We exclude all events where the two actors are geo-coded as being located in the same place (about 91 million events, or 36 percent of the full dataset), and location pairs referred to by fewer than 10 events (about 7 million events). This left us with about 43 million events (17 percent) and 216,000 connections between location pairs to visualize in the map.

 

The first map illustrates all the connections between pairs of locations. The brightness of each line reflects the number of events connecting the two places. The second graphic focus on international events, grouping the connections by country. Colour is used to map the world’s regions and the connections between them, with colour assigned to the ‘edges’ (i.e., connections) based on the colours of the two connected nodes. The thickness of the lines represents the number of events.

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