Looking back on some tumultuous years in journalism, including Donald Trump’s campaign against fake news and the rise of the digital area, we asked Jimmy Wales, founder of Wikipedia and WikiTribune, five quick questions about his view on the current state of trust in journalism.
How would you describe the state of trust in journalism?
Journalism has been under huge financial pressure for a few years and somehow lost its way. However, trust is now starting to get back after the public realized that quality journalism matters.
Access to Wikipedia is free. Does that mean that trust is free?
Trust is about honesty and this does not really cost anything. The other way round, money can corrupt honesty.
How do you go about Fake News?
We have to manage them with trust. In the mainstream and quality media we’ve got to do all things right and share transcripts, audios, … things to prove what we are saying. Only this way we can restore trust and show the people that we are not simply making something up.
How do you verify data for Wikipedia?
We verify the data with very old-fashioned techniques, like transcripts, interviews and documents. All of this is very old-fashioned journalism. If you look at later techniques, data journalism, for instance, is a very important tool in journalism of the modern world. So much can be learned from large sets of data, particularly financial contributions to politicians. It is a rich source of very good information.
How do you see the future of journalism?
I am optimistic about journalism in the future because it is a core function in society. And even if the transition from digital business models has been very difficult, I do not think that the public does not care about the truth anymore. They do. We just have to find models to make it work!
Michaela Gruber is a journalism and media management student, based in Vienna, Austria. During her studies she spent a semester abroad in France, where she started working for HEI-DA.
As the company’s communication officer, she is in charge of the Data Journalism Blog and several social media activities. This year, Michaela was HEI-DA’s editor covering the Data Journalism Awards in Lisbon, Portugal.
When talking to John Keefe, Product Manager & Bot Developer at Quartz, he encourages the journalism community to experiment with chat bots and try different tools. In this video, he shares some tips and tricks with us on what platforms to use and how journalists can build chat bots themselves.
Building chat bots is not as hard as it seems!
I would say, just give it a try!
Michaela Gruber is a journalism and media management student, based in Vienna, Austria. During her studies she spent a semester abroad in France, where she started working for HEI-DA.
As the company’s communication officer, she is in charge of the Data Journalism Blog and several social media activities. This year, Michaela was HEI-DA’s editor covering the Data Journalism Awards in Lisbon, Portugal.
After a year of hard work, collecting and sifting through hundreds of data projects from around the world, the news is finally out. The thirteen winners (and one honourable mention) of the Data Journalism Awards 2018 competition were announced on 31 May in Lisbon. Together they are the best of what the world of data journalism had to offer in the past year. They also teach us a lot about the state of data journalism.
All of the work I have done over the past few months has given me a pretty good perspective of what’s going on in the world of data journalism. Managing the Data Journalism Awards competition is probably the greatest way to find out what everybody has been up to and to discover amazing projects from all over the world.
And today I want to share some of this with you! Most of the examples you will see in this article are projects that either won or got shortlisted for the Data Journalism Awards 2018 competition.
When a news organisation submits a project, they have to fill in a form asking them to describe their work, but also how they made it, what technology they used, what methodology… And all of this information is published on the website for everyone to see.
So if you‘re reading this article in the hope of finding some inspiration for your next project, as I am confident you are, then here is a good tip: on top of all of the examples I will show you here, you can take a look at all of the 630 projects from all over the world which were submitted this year, right on the competition website. You’re welcome.
So what have we learned this year by going through hundreds of data journalism projects from around the world? What are the trends we’ve spotted?
Data journalism is still spreading internationally
And this is great news. We see more and more projects from countries that have never applied before, and this is a great indicator of the way journalists worldwide, regardless of their background, regardless of how accessible data is in their country, regardless of how data literate they are, are trying to tell stories with data.
Some topics are more popular than others
One of the first things we look at when we get the list of projects each year, is what topics did people tackle? And what we’ve learned from that is that some topics are more attractive than others.
Whether that’s because it is just easier to find data on them, or it’s easier to visualise things related to those topics, or it’s just the kind of big stories that everyone expects to see data on each year, we can’t really know for all of them. It’s probably a good mixture of all of this.
The refugee crises
The first recurrent topic that we’ve seen this past year is the refugee crises. And a great example of that is this project by Reuters called ‘Life in the camps’, which won the award for Data visualisation of the year at the Data Journalism Awards 2018.
This graphic provided the first detailed look at the dire living conditions inside the Rohingya refugee camps in Cox’s Bazar. Using satellite imagery and data, the graphic documented the rapid expansion and lack of infrastructure in the largest camp cluster, Kutupalong. Makeshift toilets sit next to wells that are too shallow, contaminating water supply.
This project incorporates data-driven graphics, photo and video. Reuters gained access to data from a group of aid agencies working together to document the location of infrastructure throughout the Kutupalong camp by using handheld GPS devices on the ground. The graphics team recognised that parts of the data set could be used to analyse the accessibility of basic water and sanitation facilities. After some preliminary analysis, they were able to see that some areas had water pumps located too close to makeshift toilets, raising major health issues.
They displayed this information in a narrative graphic format with each water pump and temporary latrine marked by a dot and overlaid on a diagram of the camp footprint. They compared these locations to the U.N.’s basic guidelines to illustrate the potential health risks. Reuters photographers then used these coordinates to visit specific sites and document real examples of latrines and water pumps in close proximity to each other.
Technologies used for this project: HTML, CSS, Javascript, QGIS and Illustrator.
Elections/Politics
Next topic that came up a lot this year was politics, and more specifically, anything related to recent elections, not just in the US, but also in many other countries. One great example of that was the Data Journalism Awards 2018 ‘News data app of the year’ award winner, ‘The atlas of redistricting’, by FiveThirtyEight in the US.
There’s a lot of complaining about gerrymandering (the process of manipulating the boundaries of an electoral constituency so as to favour one party or class) and its effects on US politics. But a fundamental question is often missing from the conversation: What should political boundaries look like? There are a number of possible approaches to drawing districts, and each involves tradeoffs. For this project, the team at FiveThirtyEight looked at seven different redistricting schemes; and to quantify their tradeoffs and evaluate their political implications, they actually redrew every congressional district in the U.S. seven times. The Atlas of redistricting allows readers to explore each of these approaches — both for the nation as a whole and for their home state.
The scope of this project really makes it unique. No other news organization covering gerrymandering has taken on a project of this size before.
To make it happen, they took precinct-level presidential election results from 2012 and 2016 and reallocated them to 2010 Census voting districts. That enabled them to add more up-to-date political data to a free online redistricting tool called Dave’s Redistricting App. Once the data was in the app, they started the long process of drawing and redrawing all the districts in the country. Then, they downloaded their district boundaries from the app, analysed their political, racial and geometric characteristics, and ultimately evaluated the tradeoffs of the different redistricting approaches. Sources for data included Ryne Rohla/Decision Desk HQ, U.S. Census Bureau, and Brian Olson.
Technologies used for this project: Ruby, PostGIS, Dave’s Redistricting App, Node, D3
An other great example of how politics and elections were covered this year comes from the Financial Times. It is called ‘French election results: Macron’s victory in charts’ and was shortlisted for the Data Journalism Awards 2018 competition.
Let’s say it, elections are a must for all data news teams around the world. That’s probably the topic where the audience is the most used to seeing data combined with maps, graphics and analysis.
Throughout 2017 and 2018, the Financial Times became an expert in:
producing rapid-response overnight analyses of elections,
leveraging their data collection and visualisation skills to turn around insightful and visually striking reports on several elections across Europe,
responding faster than other news organisations both in the UK and even those based in the countries where these elections have taken place.
Over and above simply providing the top-line results, they have focused on adding insight by identifying and explaining voting patterns, highlighting significant associations between the characteristics of people and places, and the political causes they support.
To deliver this, the team developed highly versatile skills in data scraping and cleaning. They also have carried out ‘election rehearsals’ — practice runs of election night to make sure their workflows for obtaining, cleaning and visualising data were all polished, and robust to avoid any glitches that might come up on the night of the count.
The work has demonstrably paid off, with readers from continental Europe outnumbering those from Britain and the United States — typically far larger audiences for the FT — for the data team’s analyses of the French, German and Italian elections.
For each election, the team identified official data sources at the most granular possible level, with the guidance of local academic experts and the FT’s network of correspondents.
R scripts were written in advance to scrape the electoral results services in real time and attach them to the static, pre-sourced demographic data.
Scraping and analysis was primarily conducted in R, with most final projection graphics created in D3 — often adapting the Financial Times’ Visual Vocabulary library of data visualisation formats.
Technologies used for this project: R, D3.
Crime
The last topic that I wanted to mention that was also recurrent this past year is crime. And to illustrate this, I’ve picked a project called ‘Deaths in custody’ by Malaysiakini in Malaysia.
This is an analysis of how deaths in police custody are reported, something that various teams around the world have been looking at recently. The team at Malaysiakini compared 15 years of official police statistics with data collected by a human rights organisation, called Suaram. The latter is the sole and most comprehensive tracker of publicised deaths in police custody in the country.
The journalists behind this project found that overall, deaths in Malaysian police custody are underreported, with one in four deaths being reported to the media or to Suaram.
They also highlight the important role that families of victims play in holding the police accountable and pushing to investigate the deaths. They created an interactive news game and a guide on what to do if somebody is arrested, both of which accompany the main article, taking inspiration from The Uber game that the Financial Times developed in 2017.
The game puts players in the shoes of a friend who is entangled in a custodial dilemma between a victim and the police. Along the way, there are fact boxes that teach players about their rights in custody. The real-life case that the game is based on is revealed at the end of the game.
Technologies used for this project: Tabula, OpenRefine, Google Sheets, HTML, CSS, Javascript, UI-Kit Framework, Adobe Photoshop.
We’ve changed the way we do maps
Another thing that we’ve learned by looking at all these data journalism projects is that we have changed the way we do maps.
Some newsrooms are really getting better at it. Maps are more interactive, more granular, prettier too, and integrated as part of a narrative instead of standing on their own, making us think that more and more journalists don’t do maps for the sake of doing maps, but for good reasons.
An example of how data journalists have made use of maps this past year is this piece by the BBC called ‘Is anything left of Mosul?’
It is a visually-led piece on the devastation caused to Mosul, Iraq, as a result of the battle to rid the city of Islamic State (IS). The piece not only gives people a full picture of the devastating scale of destruction, it also connects them to the real people who live in the city — essential when trying to tell stories from places people may not instantly relate to.
It was also designed mobile-first, giving users on small screens the full, in-depth experience. The feature uses the latest data from Unosat, allowing the BBC team to map in detail which buildings had suffered damage over time, telling the narrative of the war through four maps.
The feature incorporates interactive sliders to show the contrast of life before the conflict and after — a way of giving the audience an element of control over the storytelling.
They also used the latest data from the UNHCR, which told them where and when displaced people in Iraq had fled to and from. They mapped this data using QGIS’ heatmapping software and visualised it using their in-house Google Maps Chrome extension. They produced three heatmaps of Mosul at different phases of the battle, again telling a narrative of how the fighting had shifted to residential targets as the war went on.
The project got nearly half a million page views over several days in English. They also translated the feature into 10 other languages for BBC World Service audiences around the world.
Technologies used for this project: QGIS mapping software, Microsoft Excel, Adobe Illustrator, HTML, CSS, Javascript, Planet satellite imagery, DigitalGlobe images
Another example of how the data journalism community has changed the way it does maps, is this interactive piece by the South China Morning Post called ‘China’s Belt and Road Initiative’.
The aim of this infographic is to provide context to the railway initiative linking China to the West.
They combined classic long-form storytelling with maps, graphs, diagrams of land elevations, infrastructure and risk-measurement charts, motion graphics, user interaction, and other media. The variety of techniques were selected to prevent the extensive data from appearing overwhelming. The split screen on the desktop version meant readers could refer to the route as they read the narrative.
We are not talking about boring static maps anymore. And this is an example of how new teams around the world, and not just in western countries, are aiming for more interactivity, and a better user journey through data stories, even when the topic is complex. It is thanks to the interactivity of the piece and the diversity of elements put together that the experience becomes enticing.
They used data from the Economist Intelligence Unit (EIU). Using Google Earth, they plotted and traced the path of each initiative to obtain height profiles and elevations to explain the extreme geographical environments and conditions.
Technologies used for this project: Adobe Creative Suite (Illustrator, Photoshop…), QGIS Brackets io Corel Painter, Microsoft Excel, Javascript, Canvas, JQuery, HTML, CSS — CSS3, Json, CSV, SVG.
New innovative data storytelling practices have arrived
Another thing we saw was that data teams around the world are finding new ways to tell stories. New innovative storytelling practices have arrived and are being used more and more.
Machine learning
It is probably the most used term in current conversations about news innovation. It has also been used recently to help create data-driven projects, such as ‘Hidden Spy Planes’ by BuzzFeed News in the US, the winner of the JSK Fellowships award for innovation in data journalism at this year’s Data Journalism Awards.
This project revealed the activities of aircrafts that their operators didn’t want to discuss, opening the lid on a black box of covert aerial surveillance by agencies of the US government, the military and its contractors, and local law enforcement agencies.
Some of these spy planes employed sophisticated surveillance technologies including devices to locate and track cell phones and satellite phones, or survey Wi-Fi networks.
Before these stories came out, most Americans would have been unaware of the extent and sophistication of these operations. Without employing machine learning to identify aircraft engaged in aerial surveillance, the activities of many of aircraft deploying these devices would have remained hidden.
In recent years, there has been much discussion about the potential of machine learning and artificial intelligence in journalism, largely centered on classifying and organising content with a CMS, on fact-checking for example.
There have been relatively few stories that have used machine learning as a core tool for reporting, which is why this project is an important landmark.
Technologies used for this project: R, RStudio, PostgreSQL, PostGIS, QGIS, PostGIS, OpenStreetMap
Drone journalism
Another innovative storytelling practice that we’ve noticed is drone journalism, and here is an example called ‘Roads to nowhere’ from The Guardian.
It is an investigation using drone technology, historical research and analysis, interviews, as well as photomosaic visualizations.
It was a project that specifically looked at infrastructure in the US and the root causes of how cities have been designed with segregation and separation as a fundamental principle. It shows through a variety of means how Redlining and the interstate highway system were in part tools to disenfranchise African-Americans.
People are still living with this segregation to this day.
Most of the photos and all of the videos were taken by drone in this project. This is innovative in that it is really the only way to truly appreciate some of the micro-scale planning decisions taken in urban communities throughout the US.
Technologies used for this project: DJI Mavic Pro drone, a Canon 5Diii camera to take the photos, Shorthand, Adobe Photoshop. Knightlab’s Juxtapos tool to make it come to life with the slide tool
AR
Another innovative technique that has a lot of people talking at the moment is Augmented Reality, and to illustrate this in the context of data journalism, I am bringing you this project called ExtraPol by WeDoData in France.
Extrapol is an augmented reality app (iOS and Android) that was launched a month before the French presidential campaign in April 2017. Everyday, official candidates posters could be turned into new live data visualisations to inform the audience on the candidates. This data journalism project treated 30 topics in data such as: their geographical travels in France during the campaign, the cumulated number of years they have ruled a political mandate, etc.
This is probably the first ephemeral daily data journalism news app which uses augmented reality. This was the first time that real life materials, the official candidates posters, were ‘hacked’ to fact news on the politicians.
Technologies used for this project: Python, Javascript, HTML, CSS, PHP, jsFeat, TrackingWorker, Vuforia, GL Matrix, Open CV, Three.js, Adobe Illustrator, After Effect and Photoshop
Newsgames
They aren’t a new trend, but more and more newsrooms are playing with this. And this example, called ‘The Uber Game’ by the Financial Times in the UK, has been a key player in the field this year, inspiring news teams around the world…
This game puts you into the shoes of a full-time Uber driver. Based on real reporting, including dozens of interviews with Uber drivers in San Francisco, it aims to convey an emotional understanding of what it is like to try to make a living in the gig economy.
It is an innovative attempt to present data reporting in a new, interactive format. It was the third-most read by pageviews throughout 2017.
Roughly two-thirds of people who started the game finished it — even though this takes around 10 minutes and an average of 67 clicks.
Technologies used for this project: Ink to script the game, inkjs, anime.js, CSS, SCSS, NodeJS, Postgres database, Zeit Micro, Heroku 1X dynos, Standard-0 size Heroku Postgres database, Framer, Affinity Designer
Collaborations are still a big thing
And many organisations worldwide have had a go at it, in many regions around the world.
Paradise Papers
Of course we have the Paradise Papers investigation (pictured above) coordinated by the ICIJ with 380 journalists worldwide.
Based on a massive leak, it exposes secret tax machinations of some of the world’s most powerful people and corporations. The project revealed offshore interests and activities of more than 120 politicians and world leaders, including Queen Elizabeth II, and 13 advisers, major donors and members of U.S. President Donald J. Trump’s administration. It exposed the tax engineering of more than 100 multinational corporations, including Apple, Nike, Glencore and Allergan, and much more.
The leak, at 13.4 million records, was even bigger in terms of the number of records than the Panama Papers, and technically even more complex to manage.
The record set came from an array of sources from 19 secrecy jurisdictions. It also contained more than 110,000 files in database or spreadsheet formats (excel, CSVs and SQL). ICIJ’s data unit used reverse-engineering techniques to reconstruct corporate databases. The team scraped the records in the files and created a database with information of companies and individuals behind them.
The team then used ‘fuzzy matching’ techniques and other algorithms to compare the names of the people and companies in all these databases to lists of individuals and companies of interest, including prominent politicians and America’s 500 largest publicly traded corporations.
Technologies used for this project:
For data extraction and analysis: Talend Open Studio for Big Data, SQL Server, PostgreSQL, Python (nltk, beautifulsoup, pandas, csvkit, fuzzywuzzy), Google Maps API, Open Street Maps API, Microsoft Excel, Tesseract, RapidMiner, Extract
For the collaborative platforms: Linkurious, Neo4j, Apache Solr, Apache Tika, Blacklight, Xemx, Oxwall, MySQL and Semaphor.
For the interactive products: JavaScript, Webpack, Node.js, D3.js, Vue.js, Leaflet.js and HTML.
For security and sources protection: GPG, VeraCrypt, Tor, Tails, Google Authenticator, SSL (client certificates) and OpenVPN.
Monitor da violencia
Now here is an other collaborative project that you may not know of but is also quite impressive. It is called ‘Monitor da Violencia’, and it won the Microsoft award for public choice at this year’s Data Journalism Awards. It was done by G1 in Brazil, in collaboration with the Center for the Study of Violence at University of São Paulo (the largest university in Brazil) and the Brazilian Forum of Public Security (one of the most respected public security NGOs in Brazil).
This project is an unprecedented partnership which tackles violence in Brazil. To make it possible, G1 staff reporters all over Brazil kept track of violent deaths through the course of one week. Most of these are crimes that generally become forgotten — cases of homicides, robberies, deaths by police intervention, and suicides. There were 1,195 deaths in this period — one every 8 minutes on average.
All these stories have been cleared and written by more than 230 journalists spread throughout Brazil. This is a small sample — compared to the 60,000 annual homicide rate — but it represents a picture of the violence in Brazil.
The project aims at showing the faces of the victims; trying to understand the causes of this epidemic of deaths. As a first step, a news piece was written for each one of the violent deaths. An interactive map, complete with search filters, showed the locations of the crimes as well as the victim’s photos.
The second step was a collective and collaborative effort to find the names of unidentified people. A campaign was launched, including online, on TV and social media, so that people could help identify many of the victims.
A database was assembled from scratch, containing information such as the victims’ name, age, race, and gender. Also, the day, time, weapon used, and the exact location of the crime, among others.
Technologies used for this project: HTML, CSS, Javascript, Google Sheets, CARTO
Onwards and upwards for data journalism in 2018
The jury of the Data Journalism Awards, presided over by Paul Steiger, selected 13 winners (and one honorable mention) out of the 86 finalists for this year’s competition, and you can find the entire list, accompanied by comments from jury members, on the Data Journalism Awards website.
The insights I’ve listed in this article today show us that not only is the field ever-growing, it is also more impactful than ever, with many winning projects bringing change in their country.
Congratulations again to all of the winners, shortlisted projects, but also to all the journalists, news programmers, and NGOs pushing boundaries so that hard-to-reach data becomes engaging and impactful projects for news audiences.
Now in its seventh year, the Data Journalism Awards was launched in 2012. In the first edition, it received close to 200 projects. Over the years it has grown to become the first international awards recognising outstanding work in the field of data journalism, receiving the highest amount of submissions in the history of the competition in 2018.
Marianne Bouchart is the founder and director of HEI-DA, a nonprofit organisation promoting news innovation, the future of data journalism and open data. She runs data journalism programmes in various regions around the world as well as HEI-DA’s Sensor Journalism Toolkit project and manages the Data Journalism Awards competition.
Before launching HEI-DA, Marianne spent 10 years in London where she worked as a web producer, data journalism and graphics editor for Bloomberg News, amongst others. She created the Data Journalism Blog in 2011 and gives lectures at journalism schools, in the UK and in France.
Stephanie Sy of Thinking Machines (Philippines), Yolanda Ma of Data Journalism China and Esra Dogramaci of Deutsche Welle, formerly Al Jazeera (Germany), new members of the Data Journalism Awards jury, talk innovation, data journalism in Asia and the Middle East, and women in news.
left to right: Yolanda Ma (Data Journalism China), Esra Dogramaci (Deutsche Welle, formerly BBC and Al Jazeera), and Stephanie Sy (Thinking Machines) join DJA Jury
We welcomed three new members to the Data Journalism Awards jury last year (pictured above). They are all women, strong-willed and inspiring women, and they represent two regions that are often overlooked in the world of data journalism: Asia and the Middle East.
What was your first project in data journalism or interactive news and what memory do you keep from it?
Esra Dogramaci: In 2012, Invisible Children launched a campaign to seek out Lord’s Resistance Army(LRA) leader Joseph Kony and highlight the exploitation of child soldiers. Then, at Al Jazeera, we wanted to see what people in North Uganda, who lived in one of the areas who were affected by the LRA actually had to say about it. They would ‘speak to tweet’ and we would map their reactions on Ushahidi using a Google Fusion table in the background.
Uganda Speaks by Al Jazeera
Although Al Jazeera had started doing this kind of projects back in 2009 during the war on Gaza (the experiment’s page of the Al Jazeera Lab website has now disappeared but can be viewed through WebArchive.org), it picked up steam during Egypt’s 2011 Arab Spring where, due to lack of broadcast media coverage, protesters were using social media to bring attention to what was happening.
Interactive story by Thinking Machines
Stephanie Sy: Our first data journalism project as a team at Thinking Machines was a series of interactive stories on traffic accidents in Metro Manila. We cleaned and analysed a set of Excel sheets of 90,000 road accidents spanning 10 years.
It was the first project we worked on as a mixed team of journalists, designers, and data scientists, and the first time we tried to build something from scratch with d3.js! I worked on the d3 charts, and remember being in utter despair at how hard it was to get the interactive transitions to render nicely across different browser types. It was surprisingly well received by the local civic community, and that positive feedback emboldened us to keep working.
Connected China, Thomson Reuters
Yolanda Ma: One of my first projects was Connected China for Thomson Reuters, which tracked and visualised the people, institutions and relationships that form China’s elite power structure (learn more about it here).
This project taught me the importance of facts and every piece of data in it (thousands, if not millions in total) went through a rigid fact-checking process (by human beings, not machines, unfortunately). I learned by doing that facts are the bones of data journalism, not fancy visualisations, even though this project turned out to be fancy and cool, which is good too.
Now, what was the latest project you worked on and how do the two compare?
ED: Towards the end of last year, I taught a data journalism module to City University London Master’s students who were able to pull together their own data visualisation projects in the space of an hour. The biggest difference is how vastly the interfaces have improved and how quick and intuitive the designs and interactive softwares are now. There are a lot more companies switched on to storytelling beyond TV or text and that knowledge combined, how do you stand out in the world of online news?
Complementary to that Al Jazeera was always a front runner because they were willing to take risks and try something new when no one else was. In the newsrooms I’ve worked at or see since, there is still a general aversion to risk taking in preference of safety — though everyone knows that to survive and thrive in this digital media landscape, its risk taking, innovation that is going push those boundaries and really get you places.
SS: Our latest related data story is a piece we put together visualising traffic jams across Metro Manila during the holiday rush season. This time we were looking at gigabytes of Waze jams data that we accessed through the Waze API. It definitely grew out of our early work in transit data stories, but reflects a huge amount on growth in our ability to handle complex data, and understanding of what appeals to our audience.
One big piece of learning we got from this is that our audience in the Philippines mainly interacts with the news through mobile phones and via Facebook, so complex d3 interactives don’t work for them. What we do now is to build gifs on top of the interactives, which we then share on Facebook. You can see an example of that in the linked story. That gets us a tremendous amount of reach, as we’re able to communicate complex results in a format that’s friendly for our audience.
YM: I’ve been doing data journalism training mostly in the past few years and helping others do their data projects, so nothing comparable really. The latest project I worked on is this Data Journalism MOOC with HKU in partnership with Google News Lab. It is tailored-made for practitioners in Asia, and it’s re-starting again soon (begins March 6), so go on and register before it’s too late!
What excites you about the future of data journalism and interactive news?
ED: The ability to tell stories in a cleaner, more engaging way. Literally everything can be turned into a story just by interrogating the data, being curious and asking questions. The digital news world has always been driven by data and it’s exciting to see how “traditional” journalism is embracing this more. I love this example from Berliner Morgenpost where they charted this bus line in Berlin, combined with a dash cam comparing various data such as demographics, voting. Its an ingenious way of taking complex data and breaking it into a meaningful, engaging way rather than pie charts.
M29 from Berliner Morgenpost
SS: There are tremendous amounts of data being generated in this digital age, and I think data journalism is a very natural evolution of the field. Investigative journalists should be able to use computer science skills to find their way through messy datasets and big data. It’s absolutely reasonable to expect that a news organization might get a 1 terabyte dump of files from a source.
YM: It excites me because it is the future. We live in the age of data, and the inevitable increasing amount of data available means there is growingly huge potential for data journalism. People’s news consumption is also changing and I believe personalisation is one of the key characteristics for the new generation of consumers, which means interactive news — interactive in many different ways — will thrive.
How are Asian and Middle Eastern media organisations (depending on your experience) doing in terms of data journalism and interactive news compared to the rest of the world?
ED: I think Al Jazeera has always been a pioneer in this. They have a great interactive team that drew together people from various disciplines within the organisation — coders, video people, designers, journalists — before everyone else was doing it and they’ve been able to shed light on stories that wouldn’t usually be picked up on by mainstream media radars.
SS: We have a few media organisations like the Philippine Center for Investigative Journalism, Rappler, and Inquirer who have been integrating data analysis into their reporting, but there isn’t anyone regularly producing complex data journalism pieces.
Our key problem is the lack of useful datasets. A huge amount of work goes into acquiring, cleaning, and triple checking the raw data. Analysis is “garbage in, garbage out” and we can’t create good data journalism without the presence of good data. This is where the European and North American media organisations have an edge. Their governments and civic society organisations follow open data standards, and citizens can request data [via FOIA]! The Philippine government has been making serious progress towards more open data sharing, and I hope they’re able to sustain that commitment.
Example that illustrates my point: PCIJ’s Money Politics project is a great example of an organisation doing the data janitorial work of acquiring and validating hard-to-find data. During our last presidential elections in 2015, GMA News Network and Rappler both created hugely popular election tracking live data stories.
PCIJ’s Money Politics
YM: Media organisations in Asia are catching up on data journalism and interactive news. There are some challenges of course, for example, lack of data in less developped countries, lack of skills and talents (and limited training opportunities), and even poor infrastructure or unstable internet especially in rural areas that would limit the presentation of news stories. Despite the difficulties, we do see good works emerging, though not necessarily in English. Check out some of the stories from the last GIJN’s Investigative Journalism Conference held in Nepal and you’ll get an idea.
Example that illustrates my point: This Caixin Media data story analysed and visualised the property market in China for the past few years.
Another New Normal, Caixin Media
What view do you have on the role of women in the world of news today? How is it being a woman in your respective work environment? Do you feel it makes a difference? If so, which one and why?
ED: Women are underrepresented not just in news coverage but in leadership positions too. I have to admit though that being at Deutsche Welle, I see a lot more women in senior management and it feels like a much more egalitarian working environment. However looking at my overall experience as a woman in news, you do face a lot of sexism and prejudice. Every woman I know has a story to tell and when the latest story about Uber came out a lot of my female colleagues around me were nodding their heads.
What got me through challenging times is having a fantastic network of female role models and mentors who are there to support you. That was one piece of advice I gave to prior teams, get a mentor. A lot of women feel isolated or feel the way they are treated is normal but it’s not. Women should also be aware that there is a real risk you will be punished if you speak up, challenge the status quo and tow the party line. If this happens, it’s an environment or team you probably shouldn’t be in anyway.
SS: It’s alarming to see parties around the world trying to stifle the voices of anyone who doesn’t belong and calling any news that doesn’t flatter them as “fake news.”. It’s important for us to speak up as women, and to practice intersectionality when it comes to other marginalised communities. As people who work with data, we can see past the aggregates and look at the complex messy truth. We must be able to communicate that complexity in order for our work to make a difference.
YM: Most of the data journalism teams in China are led by woman, and I think they are doing really well 🙂
What do you think makes a great data journalism project? What will you be looking for when marking projects for the Data Journalism Awards this year?
ED: Simplicity. It’s easy to get lost in data and try to do too much, but it’s often about taking something complex and making it accessible for a wider audience, getting them to think about something they haven’t or perhaps consider in a different way. I’ll be looking for the why — why does this matter, does this story or project make a dent in the universe?
After all, isn’t that what telling stories is about? The obvious thing that comes through is passion. It’s also something obvious but you can tell when a person or team has cared and really invested into the work versus projects being rolled off a conveyor belt.
SS:A great data journalism project involves three things: novel data, clever analytical methods, and great communication through the project’s medium of choice. I’m hoping to see a wide variety of mediums this year!
Will someone be submitting an audio data journalism project? With all the very exciting advances in the field of artificial intelligence this year, I’m also hoping to see projects that incorporate machine learning, and artificial intelligence.
YM: I believe data journalism is after all journalism — it has to reveal truth and tell stories, based or driven by data. I’ll be looking for stories that do make an impact in one way or another.
If you had one piece of advice for people applying for the Data Journalism Awards competition, what would it be?
ED: Don’t be intimidated by the competition or past award winners. Focus on what you do best. I say this especially for those applying for the first time, I see a lot of hesitation and negative self talk of ‘I’m not good enough’ etc. In every experience there’s something to learn, so don’t hesitate.
SS: Don’t forget to tell a story! With data science methods, it’s easy to get lost in fancy math and lose track of the narrative.
YM: Tell us a bit about the story behind your story — say, we may not know how hard it might be to get certain data in your country.
What was the best piece of advice you were ever given in your years of experience in the media industry?
ED: Take every opportunity. That’s related to a quote that has been coming up over and over again for the past week or so, “success is when preparation meets opportunity.”
SS: One of my best former bosses told me to imagine that a hungover, unhappy man with a million meetings that day was the only reader of my work. He haunts me to this day.
YM: I started my career with the ambition (like many idealistic young people) to change China. My first (and second) boss Reg Chua once said to me, don’t worry about changing China but focus on making small changes and work with a long-term vision. Sounds cliche.
He said that to me in 2012. The next year, together with two other friends I started DJChina.org, which started in 2013 as a small blog and now grown to be one of the best educational platforms for data journalism practitioners in China. The year after, in 2014, Open Data China was launched (using the domain name I registered a few years back), and indicated a bottom-up movement to push for more open data, which was incorporated into national policy within a year. So I guess all these proved that Reg was right, and it could be applied to anywhere, or anything. Think big, act small, one story (or project) at a time, and changes will happen.
left to right: Yolanda Ma (Data Journalism China), Esra Dogramaci (Deutsche Welle, formerly BBC and Al Jazeera), and Stephanie Sy (Thinking Machines)
Stephanie Sy is the founder of Thinking Machines, a data science and data engineering team based in the Philippines. She brings to the jury her expertise in data science, engineering and storytelling.
Yolanda Ma is the co-founder of Data Journalism China, one of the best educational platforms for data journalism practitioners in China. Not only representing the biggest country in Asia, she also has experience teaching data skills to journalists and a great knowledge of data journalism from her region.
Esra Dogramaci has now joined Deutsche Welle and formerly worked with the BBC, Al Jazeera in Qatar and Turkey, as well as the UN Headquarters and UNICEF. She brings to the DJA jury significant experience in digital transformation across news and current affairs, particularly in social video and off platform growth and development.
Marianne Bouchart is the founder and director of HEI-DA, a nonprofit organisation promoting news innovation, the future of data journalism and open data. She runs data journalism programmes in various regions around the world as well as HEI-DA’s Sensor Journalism Toolkit project and manages the Data Journalism Awards competition.
Before launching HEI-DA, Marianne spent 10 years in London where she worked as a web producer, data journalism and graphics editor for Bloomberg News, amongst others. She created the Data Journalism Blog in 2011 and gives lectures at journalism schools, in the UK and in France.
Michaela Gruber is a journalism and media management student, based in Vienna, Austria. During her studies she spent a semester abroad in France, where she started working for HEI-DA.
