nr14: ten tips for data journalists

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10 things every data journalist should know NR14, Hamburg Jennifer LaFleur Center for Investigative Reporting

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Page 1: Nr14: Ten tips for data journalists

10 things every data journalist should know

NR14, HamburgJennifer LaFleur

Center for Investigative Reporting

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A bit about CIR

Nonprofit investigative newsroomPublic interest investigative journalismBased near San FranciscoAbout 80 staffPrint, web, radio and tv

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#1 data is a powerful reporting tool

It takes you beyond the anecdote

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And It’s easier than dealing with this

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#1 data is a powerful reporting tool

Contrasts are in the data

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Caution: This slide contains extreme nerdiness

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#1 data is a powerful reporting tool

Contrasts are in the dataYour most powerful figures are in the data

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Source: California Health Dept. data, Medicare billing data

Findings: Some hospitals had “alarming rates of a Third World nutritional disorder among its Medicare patients.”

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Contrasts are in the dataYour most powerful figures are in the dataYou can make connections you might not be able to make otherwise

#1 data is a powerful reporting tool

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Data: Youth prison workers, criminal convictions and grievance data

Findings: Employees with criminal backgrounds were more likely to be accused of abusing inmates.

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Data: Federal bridge inspections and stimulus funding.

Findings: Some of the nation’s worst bridges did not get stimulus funds.

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Contrasts are in the dataYour most powerful figures are in the dataYou can make connections you might not be able to make otherwiseYou can test assumptions

#1 data is a powerful reporting tool

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Source: NHTSA complaint data

Findings: “…unintended acceleration has been a problem across the auto industry.”

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#2 data comes from many places

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If something is inspectedLicensedEnforced orPurchased

…There probably is a database

Where’s the data?

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If there is a reportOr a formThere probably is a database

Where’s the data?

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Sometimes data is readily available online for download

Where’s the data?

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Sometimes you have to scrape it.

That usually involves programs that automate searching tasks on Web sites.

Where’s the data?

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More often you need to go to an agency or source to get the data

Where’s the data?

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Source: School district credit card purchases

Findings: District card holders made questionable purchases with their cards.

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#3 people who keep data don’t always want t give it up

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Getting electronic information

Know the law. Know what information you want.Do your homeworkKnow what the appropriate cost should be.Know who does the data entry. Get to know the computer people.

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Just another way of saying no

Huge costsDelay tactics“Oh you silly little journalist”Sending you the wrong thing“Your request was unclear”HIPAAPrivacyPrivatization

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#4 Sometimes holes in data can be a story

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#5 Even when there is no data, you can use techniques for sampling and building a database.

SamplingPhysical surveys – go look at oneTestingQuestionnaires, polls and surveysBuilding from documents

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We built a database of 500 people who had been granted or denied pardons during the Bush administration.

We started with a list of nearly 2,000 people. From that, we pulled a random sample. Then spent months researching the individuals.

We found that even after controlling for other factors, whites were more likely to get a pardon.

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To examine food safety, the Center for Investigative Reporting in Bosnia sampled food – literally -- and had it tested in labs.

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SVT surveyed 355 counties and districts about drug control – all replied (Courtesy Helena Bengtsson)

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#6 Sometimes the crowd can help you

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Where’s the data?

#7 There are many data tools – choose the right one

SpreadsheetsDatabasesMappingStatisticsProgramming

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Source: Salary data and other charter school records

Findings: Reporters Found nepotism in charter schools and administrators earning six-figure salaries to run schools with only a few hundred or a couple of thousand students

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Source: Washington Health Department dataFindings: “MRSA has been quietly killing in hospitals for decades.” But no one had tracked it until this story.

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Source: City Budget

Findings: Some neighborhoods suffer more than others as mayor cuts budgets

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SOURCE: Local health department inspection reports

FINDINGS: At 28% of the venues, more than half of the concession stands or restaurants had been cited for at least one "critical" or "major" health violation.

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#8 Sharing data is good, but give it context and be sure it is right

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Source: EPA and state data on hazardous chemical locationsFindings: Dallas County has 900+ sites that store hazardous chemicals

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Source: Medicaid outcomes data for dialysis facilities

Findings: A CMS online tool did not tell the whole story about facilities. In some counties the gap in measures, such as survival rate were vast.

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Source: Dam inspection data from Texas and federal government

Findings: Dam records had not been updated to account for population growth

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#9 Data intended for one purpose can be used in other ways

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Source: 311 calls for downed trees

Findings: After a tornado swept across New York City, 311 calls for downed trees helps trace its path

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Disparities in water usage

“Water use highest in poor areas of the city”Mapping and statistical analysis

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#10: No data is perfect

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Check your data

• Read the documentation. Understand the contents of every field.

• Know how many records you should have.• Check counts and totals against reports.• Are all possibilities included? All states, all counties,

correct ranges?• Check for missing data, duplicates, internal

problems

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