Submit a talk by February 9th. Voting begins Feb. 12th (10 a.m. Eastern) and closes Feb. 23rd (11:59 p.m. Eastern).
Have you ever wondered how IRE's lightning talks website works? Are you interested in running a medium-sized web application that needs to take user submissions but also stay up under moderate peak load? Do you have a longing to hear me talk about Flask, MongoDB, Varnish and that time we might have been hacked? This is your chance!
A speed-of-light why-what-and-how of Flourish, a new platform that enables non-coding journalists to make the cool interactive stuff they always dreamed of, and helps newsroom developers make reusable templates. With sneak previews of what's coming in the next six months. https://omg.flourish.rocks !
Data journalists love to talk about precision. So do copy editors! I'll show you how thinking like a copy editor can help you find bugs, lock down your methodology and ensure your stories say exactly what you mean.
Frustrated that your time and brain intensive data journalism projects don't reach more people? Start texting them! But first you should know such a close and personal connection with your news consumers will change the way you see your role as a journalist and the way you do your job (for the better!). Outlier Media is a Detroit based journalism service sending high value and personalized data journalism to low-income news consumers over SMS. We're eager to share what we've learned by texting and talking with thousands of news consumers about their information needs.
Install instructions are key. ("Set up code.") Inline comments can be helpful. ("I don't know what's happening here?") You want your team to be able to understand your project. ("Oops, I forgot to add a README.") But nobody who cares about good documentation actually cares about git commits, right? ("Well... shit.")Wrong! Let's talk about the commit message. Why? Because commit messages tell the story of your project. Good documentation begins at the start, and a thorough (but concise!) commit message can save hours down the road. In this lightning talk, we'll learn to write a good one.
Why do non-US and accented data sources tend to look like ⍰⍰⍰⍰? Let's take a trip into the magical land of çharacter encodìng! Learn why Excel can't cope with the Champs-Élysées, how emoji saved the planet, and how to say adiós/さようなら/до свидания to these kinds of problems forever. 👋
This is a story about being careful what you wish for. My open source web oTranscribe has over 90,000 monthly users now, which is cool but also extremely stressful, and made me think again about what defines a successful side project.
A newspaper story's print headline is almost always different from its web headline(s). In this lightning talk, I'll present the most dramatic examples of these differences. For example, "Finding books in the least expected places around L.A." (web) vs. "BOOKS IN ODD NOOKS" (print)? Or, "L.A. leaders oppose 'criminalizing' homeless people. But thousands are jailed for minor offenses" (web) vs. "CAUGHT IN A VICIOUS CYCLE" (print). Which is "better"? I don't know. But here's to a few fun comparisons!
It can be hard picking up new skills in your spare time. Here’s how I learned to take ‘em one dataset at a time and just try and help the news club.
Data journalists provide an essential role in modern newsrooms. We request, clean up and crunch data for stories big and small. We build interactive experiences and data visualizations for important projects. We're the hotness. But what does advancing in journalism look like if you have data skills? Few of us get to become editors. Why? Why does our news judgement mean less than those who come up as writers first? Why is the only career path for most over on the digital or tech side of things? I'll make an argument that just like with bylines, data journalists deserve a seat at the management table too.
That's pretty much it.
SOFTWARE or VAPORWARE is the game where YOU try to guess which features are real and which are an impossible dream. This episode features WORKBENCH, the new open source data journalism platform which *may or may not* scrape any web site, fix typos in 17 languages, produce embeddable pie charts, pilot small aircraft, send alerts when new data is published, automatically map a dictator's shell companies, and make coffee. You'll be THRILLED by what software can do, and be SHOCKED by what turns out to be difficult, when you play SOFTWARE OR VAPORWARE!
Part of publishing an investigation is anticipating how your audience will react, and being ready for it. But what about when the unexpected happens? In December 2017, we published a 5-part series about a state representative. In the middle of the roll out, he killed himself. We share what we learned about being prepared technologically, editorially, and emotionally for the unexpected.
We make better things when we make a lot of things, and small things are often better than big things. It's how we get good! Let's talk about opus projects that stretch into weeks and months and the day-to-day pieces that happen fast. What do we learn from each, and why does some of our best work happen quickly? Along the way, we'll talk Futurama, Darkness on the Edge of Town and Calvin and Hobbes.
Working with wood is more like working with data than anything else I've ever done. It also taught me a lot I never would have considered otherwise. Allow me to be the Nick Offerman of data and impart my experience to you and I'll give you both a new perspective on data and a design for a functional extendable dining room table.
Whether it's the SQL Song or the theme to Scanner Wars, music can help you through the toughest data dilemmas. This "talk" won't be a solo number. If it gets the thumbs up, I'll curate a playlist of data ditties from across the NICAR network. Stay tuned!
If you are the conductor of a way too small philharmonic orchestra, what do you look for in your musicians, if you want to keep performing symphonies through unforeseen circumstances? Via a love letter to the individuals on her team, Product owner Yasmine El Rafie highlights experiences from starting up an agile cross functional newsroom team with developers, designers, data journalists and occasional guest starring digital n00bs.
You may or may not know that Python was named for Monty Python, but who (what) the hell is Julia? Did Wes McKinney, the Pandas founder, just really love the cuddly bear? And what's with all those weird R release nicknames, like "Sincere Pumpkin Patch"? Vote for this lightning talk if you want to hear all the weird, random stuff you never thought you'd want to know about your favorite (or least favorite) programming languages.
A quick talk on data viz and how two fairly simple statistical tests challenged: 1) the state health department's narrative on a researcher's early work on lead poisoning in Flint 2) the interpretation of the performance of charter schools in relationship to traditional public schools in a state department of education report
Journalism isn’t the healthiest industry for someone with eight alcoholics in her family. Using my experience as an addiction reporter and beer enthusiast, I'll talk about how I realized I was using alcohol in unhealthy ways, how I cut back and what you can do if you'd like to drink less while doing a stressful job.
I want to talk about immigrants working in the industry, what the visa challenges they might face (that I've learned or experienced or am experiencing), and maybe focus a little on how others can be better supporters or allies to them.How "just get married" is really not a good suggestion, and can be really hurtful.How job departments and titles and classifications can matter a great deal more.How having a support network not just amongst peers, but also amongst supervisors/managers can mean the difference between being in the country or, well, not.
Whether you're new to data journalism or an experienced newsroom developer, it's easy to get overwhelmed by all the stuff there is to learn--especially at a conference like this, surrounded by so many smart people and cool projects! Let's fight off imposter syndrome and decision paralysis with an effective strategy for boosting our knowledge and our self-confidence: becoming a "tiny expert" in just one tool, API, or process, then doing it again and again. I'll talk about how I've used this over the last couple of years to keep myself motivated as a team of one, explain about how I find bite-sized problems to solve, and give examples that you can use to start your own journey toward tiny expertise.
Data nerds Jon Schleuss and Anthony Pesce started the union at the L.A. Times. Learn how they relied on good data, used the company’s technology against it and organized the newsroom at a historically anti-union paper.
No georeference? No problem. We had a what-if idea and put it together with nontraditional methods. What if you could scroll through the path of the Great American eclipse and look at it from a birds-eye view? ...What if it was one seamless image, from West Coast to East? ...What if you superimpose the umbra of the eclipse as you scrolled? ...What if the page could follow the eclipse in real time? The 30,000-pixel journey involves screenshots, rubber bands, some Photoshop and D3 magic and a lot of hacks, and was literally held together with Scotch tape at points.
Yoda famously says this to Luke when Luke doesn't believe that Yoda can lift his fighter plane out of the swamp. Similarly, data journalists don't always believe in themselves that they can not only run the numbers, but make the calls and write the story. I'm here to say that you can -- and you must, because journalism needs you!
We use data journalism all the time to measure whether public goods – like police protection, or political representation, or educational resources – are being distributed equitably among the communities that our governments serve. If we want to improve the public's trust in our news institutions, we could use similar techniques to check whether our journalistic resources are also being allocated fairly among the communities we cover. We're developing some data tools to help newsrooms do just that – let's work together!
What can international attendees, not so good at english, contribute to this unique conference? Let us take advantage of our weakness by presenting local data-driven/digital projects inside language barriers that, we hope, would be inspirational to U.S. NICARians. This is a collective, quick mic-relay by internationals or current/former foreign correspondents so I hope as many as possible to join.
Trying to make sense of job-hunting in this country, one woman trains a neural network on rejections letters she received. Listen to her talk about the five W’s and one H of it all.
BayesDB is an open source AI software that can help journalists search their data and acquire insights in seconds or minutes that otherwise require hours or days of work by someone with good statistical judgment. It can help identify which voting districts are more likely to be of high risk of voter fraud; which police departments are more likely to engage in racial profiling and bias; or which federal agencies are more likely to hire low-performing contractors. BayesDB is written in Python and allows users to query the probable implications of their data, using SQL as well as the Bayesian Query Language, BQL. Soon, it will also be accessible in the form of a spreadsheet search plugin for Google Sheets.
One of the hardest and most necessary skills to learn in this field is how to kill your darlings. I'll talk about my own experience of watching the entire interactive framework of a project collapse a month before publication, and how moving through the five stages of grief quickly made the project better and saved my sanity.
With significant EPA budget cuts and program rollbacks set in place by the Trump administration, the role of environmental journalists has become vital in watching over the health of the public and the planet. In this talk, I will share the concept of a sensor project being developed by Northwestern University’s Knight Lab that will enable journalists and citizen scientists to collect high-definition air quality data that can be used to uncover at-risk populations.
When starting out as a digital specialist at a big, traditional broadcaster, I thought it would be enought to inform journalists how to go about their digital business. But journalists generally don't have time to read the manual, they certainly don't appreciate being told how to do their jobs, and they don't necessarily agree with you that what you know is relevant. Those were just a few very hard earned lessons that came in handy when starting up a new digital project at the same company. This time however, I had a manual. So here is the cynic's handbook to surviving as a specialist in a sea of corporate know-it-alls.
On April first, in years that end in zero, we participate in a unique national moment. We exercise our constitutional right to be counted in the Decennial Census, a count that influences the structure of our political system, and dictates how $600 billion in federal funds are allocated to local cities and towns. But the Census needs our help. In 2020, it is a high wire act -- our first "online" count, it is sorely underfunded, behind schedule, and dealing with late demands from the DOJ and others. All of this could warp the count, in disheartening yet predictable ways. We are building a National Journalism Network to help cover the 2020 Census. We are forging new connections between local newsrooms and local statistical, computational and demographic expertise to tell stories of the importance of the Census, and to help fend off the inevitable challenges attempting to discredit the count. Join us! A bad Census could bankrupt data journalism for a decade.
You say "after work", I say "bleh". In a work culture that favours social and extraverted journalists, the chances are still that you may find yourself on an intraverted team, if you work as a specialist. How do you make it work when communication is key in meeting deadlines, but everyone feels most at ease staring into their own computer screen? Hear the learnings of an ambivert product owner...
Five tips for making the jump from how-to tutorials to real-life applications of technologies.