The IRE Resource Center is a major research library containing more than 23,250 investigative stories — both print and broadcast. Add to that more than 3,000 tipsheets from our national conferences on how to cover specific beats or do specific stories and you have a resource that no reporter or editor should be without. These stories and tipsheets are searchable online or by contacting the Resource Center directly (573-882-3364 or rescntr@ire.org) where a researcher can help you pinpoint what you need. Browse or search the tipsheet section of our library below. Logged-in members can view the tipsheets free online:
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Finding Data Online
There are plenty of clues on the Web that data exist, even though so much information is buried deep beyond search engine eyes. This session will highlight advanced searches and strategies for finding data that can't be found with a traditional search engine. We'll also point you to the best sites for tracking down local, national and international data. All you need is a browser and some curiosity.
Tags: data online
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Campaign finance the data science way
The Center for Investigative Reporting and IRE teamed up with the San Francisco data science company Kaggle to help bridge the gap in journalism between hacking, math and substantive expertise. They challenged data scientists to approach a database journalists have looked at a million times over: federal campaign contributions. We'll introduce you to the winner of the competition and discuss the tools the data scientists used and their results.
Tags: hacking; math; data; campaign contributions; campaign finance
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Connecting the dots with NodeXL
NodeXL is an add-in for Excel 2007 and 2010 that allows you to do network analysis (aka social network analysis) in a familiar spreadsheet environment. You'll learn how to use the software by turning data from 2007 on voting patterns in the US Senate into an informative graphic revealing the chamber's underlying dynamics - and highlighting the few senators who broke the partisan mold.
Tags: None
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Python programming for the rest of us
We will cover the basics and show you how a little programming can save you hours or days of time and make you look like a genius to your boss. Requirements: a laptop, a Google sign-in and curiosity. https://github.com/roncampbell/nicar-2013#nicar13
Tags: Python; programming
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(Way) beyond charts: Making interactive fun
Don't forget fun when making your interactives! We'll showcase witty and offbeat interactive graphics and news games from a few outlets we love, with the inside scoop on how each graphic was created, how the ideas got greenlighted, and tools you'd need to make them yourself. http://sisiwei.com/nicar-making-interactive-fun/#/
Tags: graphics; infographics
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Cracking Codes
Learn about datasets that can help localize health stories, including pharmaceutical company spending on doctors, nursing home violations and hospital quality, among others. We will dive into Medicare data and data that local and state reporters can use.
Tags: health data; Medicaid; nursing homes; drugs
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Making Health Data Sexy
Learn about datasets that can help localize health stories, including pharmaceutical company spending on doctors, nursing home violations and hospital quality, among others. We will dive into Medicare data and data that local and state reporters can use.
Tags: Medicare data; nursing home; hospital; pharmaceuticals
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Making timelines
Displaying a series of events can be as simple as drawing a straight line. But if you want to get fancier, there are a bunch of other options to display chronologies and storylines. In this talk, we'll take a tour of current timelines in the wild and walk you through three open-source tools to help you make your own: ProPublica's TimelineSetter, Zach Wise's TimelineJS, and WNYC's Vertical Timeline. http://lenagroeger.s3.amazonaws.com/timelines/timelines.html
Tags: data
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Dodging disasters: How to avoid making errors with data
We'll cover common assumptions and mistakes in data-driven stories, from misunderstanding data to writing bad SQL. Learn techniques for checking your work and creating a safety net to help you sleep at night.
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Dodging disasters: How to avoid making errors with data
We'll cover common assumptions and mistakes in data-driven stories, from misunderstanding data to writing bad SQL. Learn techniques for checking your work and creating a safety net to help you sleep at night.
Tags: data, SQL; data-driven stories