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NICAR22 will feature a mix of panels, demos, hands-on and on-demand data training, networking for in-person and virtual attendees and more. Some panels and demos will be live-streamed.
Here’s a look at some of the sessions we’re planning. Please note that this list is preliminary and subject to change. Full session details, including speakers and descriptions, will be released in the coming weeks.
Exposing residential segregation and other housing problems
Getting the most out of the 2020 census data
Using data on the law enforcement beat to tell rich investigative stories
How to spot red flags in government contracting data
Covering the student debt crisis and access to higher education
How to squeeze court records to get the most juice
Managing big data for investigating disaster emergency and recovery processes
Best practices to get and use data on the LGBTQ community
Finding health data for stories
Using DataLab to analyze federal education data
How reporters can sensitively cover and uncover issues in the Arab community
Finding data to tell stories for historically marginalized communities
Don't get duped on immigration data
Data deep dives: Out-of-the-box data stories
Following the money in Pandora Papers
Local data set bonanza
Quick-turn data story ideas
Data deep dives: Collaborations
Data deep dives: Phil Meyer winners
Creating a pipeline to management for journalists of color and those from historically marginalized communities
A roadmap for editors
Infusing a data-driven mindset throughout the newsroom
Make your data work visible and respected in the newsroom
Best practices for teaching data journalism
Using nontraditional data to expand data journalism education beyond U.S.-centric narratives
Working with journalism students, data, and media partners to tell stories for social good
Broadcast: Data stories that don't look like data stories
Broadcast: How to tell compelling data stories on podcasts and in video
Three statistical paradoxes worth knowing
Conducting your own surveys and other mass information collection
Mobile and desktop data reporting tools
Lessons learned from coronavirus trackers (especially for small teams)
Extending DocumentCloud to power advanced visualization, data gathering and analysis
Who is behind this website?
Making numbers count
Web accessibility beyond the surface level
How to use investigative techniques to hold algorithms and artificial intelligence accountable
AP Harvester demo
Case studies in machine learning
Three ways to automate your scraping
Using data in pursuit of solutions journalism
Using social network analysis to report on power and influence
How to diversify your sources
Data viz when the data isn't quite there yet
Dataviz 101: Keep it simple
How and why to make your data analysis reproducible
Make your data story ironclad
How to track online political messaging and ads
Parsing FEC filings quickly
Uncovering foreign influence operations in the U.S.
Following state election money
How to get data through state records laws
Navigating the federal Freedom of Information Act
Early-career journalists
Mid-career journalists
Veteran journalists
Students
Educators
Journalists of color
LGBTQ+ community
Managers
Radio and TV broadcasters
Hitchhiker's guide to APIs
OpenRefine for power washing your data
PDF 1: Using free online tools
PDF 2: Advanced PDF processing with OCR and command-line tools
Python: Intro to data analysis using Pandas
Python: Intro to web scraping
Python: The fundamentals
Python: Introduction to text mining and other machine-learning techniques
QGIS 1: Importing and displaying geographic data
QGIS 2: Building your first map
R 1: Intro to R and RStudio
R 2: Data analysis and plotting
R 3: Gathering and cleaning data
R: Advanced dataviz techniques
Regular expressions for the rest of us
SQL 1: Exploring data
SQL 2: Grouping and summing data
SQL 3: Joining tables
SQL: Cleaning dirty data
SQL: Update queries, sub-queries and more advanced techniques
R: Introduction to statistics
R: Linear and logistic regression and other statistical methods
Using GitHub in your newsroom
Web development 1: HTML and CSS
Web development 2: Introduction to JavaScript
Web development 3: JavaScript for Data Visualization and Introduction to Build Tools
An introduction to VisiData
Finding racial disparities in education through data
Scraping without programming
Indexing your database for faster queries
Mapping disparities in the news using Census data and QGIS
Introduction to graph databases for data journalism
Finding needles in haystacks with fuzzy matching
3D modeling in the browser
Finding the story: Federal judges' financial disclosures
Mapping and geographic data analysis with the simple features package in R
Datawrapper pro-tips
Introduction to GitHub actions
Introduction to Observable Notebooks
2020 census data via IPUMS
Pulling political ads from Facebook, Google, Snapchat and more
Scraping government dashboards and platforms
Finding the story: Climate change data
Finding the story: Nonprofit data
Command-line for reporters (Mac)
Three handy command-line tools for working with data: csvkit, jq, pup
Excel 1: Getting started with spreadsheets
Excel 2: Formulas & sorting
Excel 3: Filtering & pivot tables
Excel 4: Advanced Pivot Tables
Excel: Basic stats
Excel: Using string functions to manipulate data
Excel: Cleaning dirty data
Geocoding and avoiding pitfalls
Mapping for analysis and online display
First Python Notebook
First visual story
First Github scraper
Digging into data
Exploring and visualizing your data in R
Interviewing your data with SQL
Intro to R
Introduction to web development
Mastering Google Sheets: Web scraping, running scripts and other tricks
PyCAR
Upping your Excel game
Web scraping with Python
Turning stacks of documents into data
Using data to report on inequities
Managing high-performing technology teams in journalism
Editing the data story
Statistics
Writing the data narrative
Interviewing
Federal FOIA: How to make optimal requests, navigate delays, appeals, and litigation
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