Using Data for Great Story Ideas

1. Using Data for Great Story Ideas

2. Objectives for Day 1 • Sort and filter Statistics Canada data • Download the data into a spreadsheet • Navigate Statistics Canada data to understand the difference between rates and raw numbers • Sort and filter Ontario’s public sector salary data • Discuss how to make strong story pitches based on the data you've analyzed

3. Objectives for Day 2 • How to use basic math formulas such as summing, counting, and creating pivot tables to find stories • How to mine stories from the analysis of datasets • How to find data online • Strategies for incorporating these skills into your workflow

4. The 3 Disciplines • To find newsworthy patterns and trends • For visualization to show your trends • For custom web development and internet coding skills to create interactive news applications

5. Examples of Stories Using Data • Walmart: Thousands of police calls. You paid the bill. • 2018 Philip Meyer Award winners • 'We're guinea pigs': Canada's oversight process for implanted medical devices stuns suffering patients • Canada’s highest-paid CEOs • https://www.icij.org/ • Some of the best from 2017

6. Getting into the Data • You need filtering & sorting skills • Find patterns • There’s no math • Excel & Google Sheets

7. Rates and Raw Numbers • Raw numbers are used to track incidents in datasets (e.g.,on the websites of Statistics Canada or Ontario’s public sector salary disclosure) • Raw numbers convey important information and can be misleading • Rates are better used when discussing issues like unemployment and crime • To obtain rates, need denominators: population figures; miles travelled on the road and in the air; medical devices sold, etc.

8. Using Statistics Canada Tables • We use them every day, but do we use them to the best of our ability? • The agency provides some of the country’s most definitive data • New formats allow for easier analysis of the data to do stories on deadline – and beyond • Tutorial: A quick video how-to session on using the agency’s data tables.https://www.statcan.gc.ca/eng/sc/video/howto

9. Statistics Canada Tables • Story: Hate crimes reached all-time high in 2017, Statistics Canada sayshttps://www.cbc.ca/news/canada/toronto/statistics-canada-2017-hate-crime-numbers-1.4925399 • The data: https://www150.statcan.gc.ca/n1/daily-quotidien/181129/dq181129a-eng.htm • Story: Canada loses 51,600 jobs in August, pushing up unemployment ratehttps://www.cbc.ca/news/business/canada-jobs-unemployment-rate-full-time-work-1.4814183 • The data: Labour force characteristics, monthly, seasonally adjusted and trend-cycle

10. Applying what we’ve learned with more StatscanTables • Story: GM's decision to close Oshawa plant raises fears for future of making cars in Canada • The data: Manufacturing sales by industry and province, monthly (dollars unless otherwise noted) • More data: Retail trade sales by industry • Even more data: Labour force characteristics, monthly, seasonally adjusted and trend-cycle, last 5 months

11. Workflow Ideas for using Statistics Canada Data • Create an account that automatically notifies you when there are releases on specific topics and download a PDF of release dates for key economic indicators. • Identify a list of experts within Statistics Canada who can help with your analysis.

12. Follow-up Exercises • Keep track of a StatCan release of a key economic indicator and pitch a same-day story. • Find a way to work some of the StatCan information into the context for a story, interview or visualization.

13. Sunshine List Stories • Story: Ontario releases its annual Sunshine List of top public sector salaries • Data:https://www.ontario.ca/page/public-sector-salary-disclosure-2017-all-sectors-and-seconded-employees • https://www.ontario.ca/page/public-sector-salary-disclosure • Tutorial: sorting and filter salary data

14. Applying What We’ve Learned with Alberta Salaries Data • Story: Chief medical examiner top earner of Alberta government employees • Website: Alberta Public Disclosure of Salary and Severance

15. What We Learned! • How to sort and filter Statistics Canada data. • How to download the data into a spreadsheet for continued analysis. • How to navigate Statistics Canada data to understand the difference between rates and raw numbers. • How to sort and filter Ontario’s public sector salary data. • Discussed strong story pitches based on the data you've analyzed.

16. Follow-up exercises • Once you’ve filed your main story based on the newest salaries data, continue to drill down using a bit of spare time you’ve carved out for yourself. • Create worksheets in your Google Sheet for the various institutions of interest, such as hospitals, municipalities and school boards. • The increasing number of employees like police constables and nurses, who typically earn less than $100,000 a year, may indicate more of them are working overtime, thus straining municipal budgets.

17. Workflow ideas for using salaries data • Find out the release schedule for the data • To prepare, download the previous years’ datasets, using the same techniques we’ve learned. • Once the new data is uploaded, update your dataset and use techniques to go beyond who made the most. For instance, filter for local institutions like hospitals, school boards and municipalities to find categories of employees on the lists

18. Using Data for Great Story Ideas

19. Objectives for Day 2 • How to use basic math formulas such as summing, counting, and creating pivot tables to find stories • How to mine stories from the analysis of datasets • How to find data online • Strategies for incorporating these skills into your workflow

20. Summing - Counting &Pivot Tables • Story: Maxime Bernier's broad regional donor base edges out remaining rivals • Summing and counting using Elections Canada data. • Examine contributions to the candidates in the Conservative Party of Canada’s 2017 leadership race.

21. Summing &Counting • Follow this tutorial which explains how to download, save and open the donations table. • Upload the Conservative Party leadership contribution file to Google Sheet. • Determine which candidate raised the most money and attracted the highest number of donors. • Create a pivot table with the help of this tutorial.

22. Applying What We’ve Learned with Political Contributions Data • Using the same steps, download contribution data for the NDP’s leadership campaign. • Save a back-up copy. • Clean the table • Eliminate the extra material above and below the rows and columns • Upload the cleaned-up table to Google Sheets • Create a pivot table to determine who raised the most money, number of donors and the regions of the country where candidates did the best.

23. Workflow Ideas for using Political Donations Data • Access donations data through federal, provincial and municipal data portals. • Keep a calendar of upcoming releases and carve out time to analyze the data and write stories. • On March 20, 2018, Postmedia announced the Follow the Money project, a database of political donations at every level of government. • Access the data by clicking here.

24. Finding data • Access data through federal, provincial and municipal open-data portals or through access-to-information requests. • There’s an easy checklist to follow when determining the strengths and weaknesses of any dataset such as frequency, when it’s updated, and how the institution uses the information.

25. Finding data • College enrolment: Enrolment and statistical data for colleges of applied arts and technology in the provincehttps://www.ontario.ca/data/college-enrolment • University enrolment:Enrolment and statistical data for universities in the province that receive regular operating funding from the Ministry of Advanced Education and Skills Developmenthttps://www.ontario.ca/data/university-enrolment • Dinesafe Datahttps://www.toronto.ca/city-government/data-research-maps/open-data/open-data-catalogue/#e3c15b0f-5f83-0f12-fabb-c84018395c38

26. Finding data • Public Accounts: https://open.canada.ca/data/en/dataset?portal_type=dataset&q=Public+accounts&organization=pwgsc-tpsgc • Treasury Board Secretariat's Access to Information summaries: https://open.canada.ca/en/search/ati • For more great examples, check out another page I created called The Best of Open Data • National Parole Board Pardon StatisticsPardonsGrantedAndDenied - FY2011-2012 to MY2018-2019.xlsx

27. Develop a “Data State of Mind” • Find set times to look for datasets. • Look for ways to use data to add context to your stories. • Revisit a recent story and ask if it could have been improved with data.

28. Wrap & Action Plan • Create a contact list; do some simple math. • Keep a master workbook with each worksheet containing a data set you’ve used. • Keep a data library for your growing list of calculations, including the ones we’ve learned. • Create a Google alert for “Open Data” to learn when government sites are adding new datasets to their websites. • Set up another Google alert for “data journalism” to track how stories are using numbers. • Create a tweet deck to follow data journalists. • Sign up for the NICAR listserv

29. Reference material • The Data Journalist: Getting the story • Google Sheets guide • Website with additional material