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Why our data newsletter asks the community for advice


Why our data newsletter asks the community for advice

Picture of Madolyn Smith
Madolyn Smith — Freelance Data Editor
December 19, 2018

And three unseen tips from our first editions

In May this year, we launched a new fortnightly newsletter to share the data journalism community’s top tips and tricks. We called it Conversations with data, because each edition facilitates a discussion with the community, or offers the opportunity to quiz the field’s top experts (like, say, this edition with Alberto Cairo) on anything and everything data.

Only seven months have passed and already we’ve produced 16 issues, featuring advice from 75 individual community members and 17 expert AMAs. But we didn’t get here without our share of challenges.

Developing our concept

Firstly, as any newsletter editor will tell you, there’s always the question of value. Did the community really need another newsletter?

My inbox (like yours I’m sure) is filled with newsletters dedicated to digital storytelling, media innovation, and fantastic data stories. If we were going to introduce a new one, it would need to be different.

I began thinking about things I value in newsletters. As a longtime subscriber of community-driven listservs, like NICAR-L and Responsible Data, I’ve always found the questions and advice in these forums to be both useful and engaging. I wondered whether these conversations could be replicated in a standalone, facilitated format. So, I dug up an old NICAR thread on the pros and cons of Tableau and threw together a prototype.

Our director loved it — horrah! And so Conversations with data was born.

Sourcing advice from the community

Now that we had a newsletter, I was faced with a new challenge: getting people to participate. Data journalists, like all journalists, are time poor and a tweet calling for advice, to be featured in a newsletter that no one even knows about yet, is not exactly an enticing use of that time.

What to do? In addition to putting out calls for contributions, I ended up researching each of our topics and reaching out to subject matter experts who I thought could make a valuable contribution.

…which led to a separate issue with having too much content.

It’s no secret that the data community is incredibly passionate and supportive of other journalists learning their craft. However, this enthusiasm meant that I would often receive pages of advice, hard tasked to squeeze it into a digestible format for your inbox. With regret, I would cut great — sometimes brilliant — words of wisdom from experts across the field.

Thankfully, this advice is not all lost. Here are three snippets of unseen conversations, that I wish never ended up on the cutting room floor.

1. Crowdsourced data is often personal data — think about efficient ways to get permissions right

Sound advice from the ABC’s aged-care investigation team. In our crowdsourcing edition, they told us about their work crowdsourcing 4,000 survey responses on conditions in facilities across Australia. While their advice on developing survey questions made it into the edition, what didn’t were these words on considering data privacy:

“It was important to the ABC that we were very careful with people’s private information. We guaranteed that we would not publish information provided to us unless we contacted the respondents directly and asked them permission. We wouldn’t necessarily change that permission level, but I would suggest in another project that we be really explicit about what we are collecting as a dataset to be used ‘as and when’ and more specific answers which would require contact with the source before their stories were reported.”

The ABC’s Editorial Policy sets out privacy standards and principles for its reporters.
The ABC’s Editorial Policy sets out privacy standards and principles for its reporters.

2. Start with the question, not the data

Cut from our open data edition, this piece of advice from Eva Constantaras reminds us of the importance of making journalism useable to the public:

“As the US elections proved to us, a lot of data journalism can be published without actually addressing fundamental issues that should inform decision-making. In the end, it’s not about polls that reflect back what people already believe but about informing citizens on issues that they are asking questions about and hopefully plan to vote on.

This story from Pakistan used public data to show parents that children graduating from private school score only slightly better on standardised tests than children in public school. This story from Armenia shows the public health consequences of the widespread use of expired x-ray machines in public clinics. This story from Kenya demonstrates that the gender gap persists, in part because the informal work done by poor women often goes uncounted. They help citizens answer basic questions like ‘Does my government provide quality public education?’ ‘Does it provide reliable healthcare?’ ‘Does it value and support the economic contributions of everyone in society?’ The ‘news you can use’ concept is vital to proving the value of data journalism to small news organisations with tight budgets.”

3. Get talking to data custodians

Nowadays, metadata is typically digitalised, but previously journalists may have used traditional card catalogues like these. Credit: Dr. Marcus Gossler (CC BY-SA 3.0).
Nowadays, metadata is typically digitalised, but previously journalists may have used traditional card catalogues like these. Credit: Dr. Marcus Gossler (CC BY-SA 3.0).

It might seem obvious, but they’ll help you understand what you’re working with. A tip from Naveena Sadasivam at the Texas Observer, which never made it into our environment edition:

“When you get your hands on a big, juicy dataset, don’t dive in immediately. Take some time to talk to the custodians of the dataset and try to understand how it is used. Environmental data can be wonky and technical. Make sure you get a data dictionary or have someone walk you through the dataset. Ask questions about each piece of information, how and why it was collected, what blank cells or ‘N/A’ mean and the units used. My worst nightmare is publishing a story only to find out that I made a fundamental mistake in interpreting the data.”

Looking forward to 2019

While we’re extremely proud of our conversations so far, we’re still keen to ensure that our newsletter is serving the community properly — remember that value we wanted to add?

Conversations with data is a resource by and for journalists: that’s you. To meet this objective, we need your input on what’s worked, what hasn’t, and topics you’d like to see us cover in 2019. Let us know by filling out this short survey.

(And if you’ve read all this way, without having actually read an edition of Conversations with data, you can subscribe here and catch up on our past editions here.)


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