The Investigative Data Team

Portfolio for DJA 2016

The Investigative Data TeamThe Investigative Data Team

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ContentsIntro 3

Most beloved dogs in Denmark 4

My income 6

The VAT hustlers 8

This is how your neighbors voted 10

Which refugees do municipalities prefer 12

Where can you afford to live? 14

An equal society: Who stays home with a sick child? 16

Too much zinc in the farmland 17

Denmark gone bankrupt 18

The escape 20

See interactive version

Click to see a demo of the interactives in the Portfolio

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The Investigative Data Team at The Danish Broadcasting Corporation is proud to submit a portfolio with 10 of our best projects from 2015/2016. The team has achieved a variety in our publications that shows a range from small, quick stories based on data and illus-trated with original and creative graphic design to large projects that integrate the best from investigative journalism with advanced data-tools combined with collabo-ration with TV documentary, TV news and radio news. The Data Team was launched October 2013. Our goal is to make unique, interesting and relevant news using data as a source and a method for the online news site of the Danish Broadcasting Corporation. Our stories are sometimes large, investigative projects that

takes months to research, but it might as well just be small, interesting data-sets that are fast and easy to publish - but might be the facts that sets the record straight, gets the debate going or just makes our readers curious about a subjects.

The Data Team has seven regular members: An editor, three journalists, two IT-develop-ers and one graphic designer. Many projects are shared with other teams, so we collabo-rate with other journalists from other parts of the news organization to reach radio- and TV-audiences as well. Team-members have also occasionally been temporary replaced by other colleagues due to illness or materni-ty leave: that’s why many names appear in the credits.

Intro

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The Investigative Data TeamThe Investigative Data Team

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Danes loves dogs. More than 20 pct. of families in Denmark own one or more dogs. A few breeds are particularly popular, and the Data Team decided to find out where in Denmark which breeds are trending.

Data was not difficult to acquire, since all dogs (of official breed) are registered in a database. What was unique for this small project was our solution for visualization: we wanted to use something other than a drop-down-box or similar: why not a dial? Plus, hand-drawn images of the various dogs?The visualization is a HTML-container with scalable SVG inside for the UI-elements and finally the images of the dogs are resized server-side to optimize the rendering. The SVG-part makes it ultra-scalable; some minor differences do however exist between mobile and desktop; mostly related to touch/mouse.

Publication: 19th February 2016

Credit: Kresten Morten Thye Munksgaard, Jens Lykke Brandt, Mads Ra�e Hein and Mads Mostrup Jensen.

Details/tools

Link to article 2 Link to article 1

Do all the trigonometry, apply some logic and voilà: a responsive user-interface for selecting a dog, show-ing a simple map of Denmark with the popularity visualized and finally the numbers for each area.A note on the data and map: data on breeds were aggregated on zip-codes in sets not corresponding to any official administrative division. So an official map of all zip-codes was used as a base in QGis. In QGis the zip-codes were merged using a query and the result was exported, thinned out and converted with http://mapshaper.org and finally processed into a simple SVG used directly – no need for advanced zoom-functions, panning and the like this time.

Den undersøgende databaseredaktion

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What I love about this data-story is the interactive visu-alization. It’s so beautiful with the water-colored dogs, the simple intuitive motion of the interactive design and the details about specific dogs in different parts of the country. It’s playful and very easy for our readers to use.

Katrine Birkedal Frich - Editor

See interactive version

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Denmark has a very, very small gap between rich and poor. But is this a good thing or not? That was a topic at the Danish Broadcasting Corporation this winter. While TV and radio covered the subject with news, debates, and documentaries, the Data Team decided to use income-data to interact with the readers. We wanted to let them see the national variation in income and test their assumption about where in the distribution their personal income is. We acquired data from Statistics Denmark and developed an interactive component.

What was unique for this small project was our solution for visualization. We made a small gamifi-cation aspect where people first had to guess how many Danes earn less than you before being shown their own result. We saved their answers and we were surprised by the result: More than 140.000 Danes checked out their income com-pared to the national variation - and most of them guessed that they were in a lower percentile, than they actually were.

Publication: 3rd of March 2016

Credit: : Kresten Morten Thye Munksgaard, Mads Ra�e Hein, Benjamin Hughes Dalsgaard and Benny Box

Link to article

My income

See interactive version

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The interactive component was developed over several iterations focus-ing on mobile-first development. In each iteration we got a more focused visualization in regards to text, animations, UI and design. We user tested the interactivity in each iteration to ensure that the graphic was easy to understand and to use.

The visualization was developed using HTML, CSS and JavaScript (ES2015). We used the D3js-library to draw the bar-chart and noUiSlider to create a slider working seamlessly with all platforms. We ran into an all too well known problem on smartphones, which was showing additional information about the bar-chart. This is normally done by clicking a bar and getting some kind of information in a pop-up-box. On desktop this is done by hovering, but we wanted to try something new on smartphones: we used the DeviceOrientation-API to create a hover-box that shi�ed around by tilting your phone. This ensured an easy and very useable way of interacting with the bar-chart.

Details/tools

The purpose of making users guess how many people earns less than them was to open their eyes to the fact that they were probably better off than they thought. And it worked. Three out of four users were told, that more people make less than them, compared to what they guessed.

“Kresten Morten Thye MunksgaardJournalist

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Output: More than 50 articles on dr.dk, 3 interac-tive visualizations and a joint-venture with the documentary department which led to three docu-mentaries (45 minutes each) and several segments on the main evening news program.People and companies pay taxes and VAT in Den-mark to support common goods such as public health care, schools, roads, pensions, etc. But when companies pay VAT the system is based on a fair amount of trust rather than control from the tax authorities towards the companies. The risk of getting caught if you cheat the authorities is very low. As a result, the tax-system is victim of compre-hensive fraud with VAT every year.The Data Team – and the documentary-team at DR – decided to investigate how, where, and who are behind the fraud.

This investigation was so comprehensive, thorough and deep that we were able to reveal a huge network of scam-businesses with links to interna-tional fraud. We revealed who is behind the fraud, how it works and who benefits. We wrote stories revealing companies that not only cheat the tax authorities, but also the costumers when they sell old, filthy candy to discount price. And not the least we wrote about the links between the scam-busi-nesses in Denmark and terrorists in Spain. A link, which according to VAT-expert Richard Ainsworth from USA, never has been as clearly documented.This investigation is a masterpiece of data analysis based on the unfolding of a network in a dark, secret world of crime where no information is handed easily.

Publication: 12th of January 2016 to 15th of February 2016

Credit: Bo Elkjær, Nis Kielgast, Benjamin Hughes Dalsgaard, Mads Ra�e Hein, Mathias Sommer, Troels Kingo

Larsen and Mads Nilsson.

Link to article

The VAT hustlers

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This is the first time ever I have been able to document that chocolate sold to kids is used to cheat the taxpayers for millions and millions of kroner. And di-rectors for some of the compa-nies in this network are now being investigated by police in Spain for their role in terrorism.

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Bo ElkjærJournalist

The interactive solutions were developed in an iterative fashion. One specific thing we acquired from these iterations, was an image of a hand that hovers over the clickable plus-signs in the interac-tive component. When a plus is clicked, the hand is removed. This ensures the user knows how to use the interactive component.Another thing we learned from the iterations was that including an animated icon showing a mouse that indicated the further scrolling helped the user. This icon is slowly removed depending on how far a

user has scrolled on the page.All the interactive elements were developed using Google spreadsheet. All the text in the interactive elements were edited in a Google spreadsheet and updated automatically during the development phase. The interactive elements make a AJAX-call to the Google Spreadsheet API every time it is loaded, getting the newest text. This makes text editing better for designers, journalists and developers. When all text is finished the JSON-file providing this text is stored on the server.

Details/tools

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1. Identifying and buying data from the officialDanish statistical institution, Statistics Denmark.

2. Manage data and find stories in correlations.3. Create geographical areas corresponding to

polling-stations.4. Visualize data and make it interactive.

The first part was interesting due to the financial constraints: we wanted all the data available, but

Details/tools

Up to the general election in Denmark in June 2015 we decided that we wanted to let the Danes know how their neighbors voted in the election. We wanted to make a map with the results from more than 1400 different polling stations and also show variations in education, family-type, employment, age, and citizenship just to mention a few. Unfortu-nately, no authorities had an updated map, so we

had to create it ourselves combining large public data-sets to create hand-drawn polygons.

Our detailed map was the second most read article on the election-night only surpassed by the story showing the national result. Later we have had several companies and authorities asking if they could use or buy the map.

Publication: 18th of June 2015

Credit: Mads Ra�e Hein, Jens Lykke Brandt, Kresten Morten Thye Munksgaard

Link to article

This is how your neighbors voted

that was very expensive. We settled for a mix of variables that would describe Danes in several ways. A�er purchasing data, it arrived during a few weeks. And time was not our friend.Data was managed in Excel since the number of rows were below 1500. The number of columns was relatively high though. Data were crunched thor-oughly, understood and analyzed.A parallel process was underway to construct the

There were at least four large parts in this project:

polygons covering all voter-addresses connected to a polling-station. There was an outdated test-version available from Danish Geodata Agency. So it was possible. Somehow.In the end we downloaded three official databases, unpacked them into usable formats and imported them into a MS SQL-server. This was done with programs in C#.Once inside the database some data-transformation was carried out before joining the data: the poll-station for an address was in one data-base (CPRVej), the address-database (AWS) had the land-parcel-id for every address and the parcel-database (Matrikelkortet) had the polygon of every parcel in Denmark. Thus we ended up with every land parcel in Denmark and the poll-station it was associated with. In QGis the outdated map was used as a base-map. Several municipalities had changed the layout of their polling-station areas and those were redrawn in QGis. Then exported and processed.usable on mobile devices as well.

Putting it all togetherLots of data, many parameters and +1400 detailed areas comprised of one or more polygons. It was all put together in Google Fusion Tables and visualized on a Google Map. We ran into several of the limits in Google Fusion Tables and had to circumvent a few in order to represent data correctly.User interface was added as were data-legends and pop-up-boxes with text and charts showing the election-result.The result works very well in full-screen on a huge screen. But we made it usable on smartphones as well.

See interactive version

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1. Identifying and buying data from the official Danish statistical institution, Statistics Denmark.2. Manage data and find stories in correlations.3. Create geographical areas corresponding to polling-stations.4. Visualize data and make it interactive.

The first part was interesting due to the financial constraints: we wanted all the data available, but

that was very expensive. We settled for a mix of variables that would describe Danes in several ways. A�er purchasing data, it arrived during a few weeks. And time was not our friend.Data was managed in Excel since the number of rows were below 1500. The number of columns was relatively high though. Data were crunched thor-oughly, understood and analyzed.A parallel process was underway to construct the

polygons covering all voter-addresses connected to a polling-station. There was an outdated test-version available from Danish Geodata Agency. So it was possible. Somehow.In the end we downloaded three official databases, unpacked them into usable formats and imported them into a MS SQL-server. This was done with programs in C#.Once inside the database some data-transformation was carried out before joining the data: the poll-station for an address was in one data-base (CPRVej), the address-database (AWS) had the land-parcel-id for every address and the parcel-database (Matrikelkortet) had the polygon of every parcel in Denmark. Thus we ended up with every land parcel in Denmark and the poll-station it was associated with. In QGis the outdated map was used as a base-map. Several municipalities had changed the layout of their polling-station areas and those were redrawn in QGis. Then exported and processed.usable on mobile devices as well.

Putting it all togetherLots of data, many parameters and +1400 detailed areas comprised of one or more polygons. It was all put together in Google Fusion Tables and visualized on a Google Map. We ran into several of the limits in Google Fusion Tables and had to circumvent a few in order to represent data correctly.User interface was added as were data-legends and pop-up-boxes with text and charts showing the election-result.The result works very well in full-screen on a huge screen. But we made it usable on smartphones as well.

Our map was the only of its kind in Denmark even though many medias and or-ganizations had asked for it. For me, the best thing about the map is that it makes all Danes able to learn more about the similarities and differences of the people living in a specific neighborhood.

“Kresten Morten Thye MunksgaardJournalist

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Refugees arriving in Denmark were one of the hot topics in the general election in June 2015. We decided to investigate how refugees are distributed between the Danish municipalities a�er getting asylum and whether this was done in a reasonable manner. Preferably ensuring a quick integration into both communities and jobs.We discovered that municipalities can ask for specific nationalities, but only 48 of 98 municipalities did so.

By going through the hand-written (!) wish-list we saw that especially people of Syrian nationality were “in demand”, which was interesting consider-ing the sky-rocketing influx the last five years. However, we also noticed that municipalities had asked for engineers, but getting none – while others without this preference did. The Danish authorities promised a better allocation of refugees a�er this discovery.

Publication: 5th of June 2015

Credit: Karsten Østergaard Nielsen, Mads Ra�e Hein, Benjamin Hughes Dalsgaard, Jens Lykke Brandt, Kresten Morten Thye Munksgaard

Link to article 1 Link to article 2

Which refugees do municipalities prefer

See interactive version

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The interactive component is developed using JavaScript, D3js, HTML and CSS. It shows the individual preferences for selected municipalities. On smartphones it has an alternative municipality-selector accessed through a ‘hamburger-menu’.

Details/tools Infographic

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Kresten Morten Thye MunksgaardJournalist

The main focus of the political discus-sion on refugees is how to get refu-gees into jobs as fast as possible. We were able to make it visible for our readers that it was possible to make a smarter allocation of refugees between Danish Municipalities, which probably will raise the chance of getting more refugees employed.

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In Denmark 20 pct. of all homes are “public housing”. These apart-ments and houses are subsidized when built and thus considered affordable for people with lower income. But when the Data Team decided to analyze the data from more than 560.000 public houses and the level of rent, we found that it’s very random and opaque: rent can be very cheap for some - but up to 4 times more expensive for others at the same size and location.To enable people to compare their own level of rent, we designed an interactive solution with all data regarding the highest and lowest level of rent in public housing in each of the 98 munici-palities in Denmark. As always we designed the tool for mobile-first. We got the data by scraping a public webpage.

Publication: 30th of December 2015

Credit: Nis Kielgast, Frederik Fabricius Smitt,Jens Lykke Brandt andMads Ra�e Hein

Link to article 1

Link to article 2

Where can you afford to live?

All data revealed in the interactive solution was verified manually. This was a great data-piece that revealed several discrepancies in the public housing sector. Many previously untold to the public.

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By analyzing data we found out, that living in a public house is a bit like a lottery: You can win a great and cheap place to live - or you can get the opposite.

Nis KielgastJournalist

In Denmark 20 pct. of all homes are “public housing”. These apart-ments and houses are subsidized when built and thus considered affordable for people with lower income. But when the Data Team decided to analyze the data from more than 560.000 public houses and the level of rent, we found that it’s very random and opaque: rent can be very cheap for some - but up to 4 times more expensive for others at the same size and location.To enable people to compare their own level of rent, we designed an interactive solution with all data regarding the highest and lowest level of rent in public housing in each of the 98 munici-palities in Denmark. As always we designed the tool for mobile-first. We got the data by scraping a public webpage.

Details/tools

All data revealed in the interactive solution was verified manually. This was a great data-piece that revealed several discrepancies in the public housing sector. Many previously untold to the public.

The web-scraper was programmed in Python using Selenium. Data was handled and analyzed in Excel.For the article we used a simple solution: choose your municipality and then the data are shown or updated. All done responsively.

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Can women become truly equal at the workplace if the bosses have to take in to consideration that women will need more time at home to take care of their children than a male employee? The answer was not easy, but thanks to the data and the story, it was the talk of the town for a while.

Katrine Birkedal Frich - Editor

Details/tools

In Denmark we take pride in being a society where men and women are very equal. We work the same hours, we have same rights and same duties. But when it comes to childcare it’s still an ongoing debate: do men and women share this responsibility equally – and is it a desirable goal?That is why, this data-story was very interesting.

The Data Team found a data-set from Statistic Denmark that reveals the facts about equality. The data-set showed that Danish mothers (still) takes almost twice as many days at home (and away from work) with their sick children as the fathers do. This simple – but surprising – data was the foundation for a huge debate about consequences and causes. This story and our info-graphics were some of the most read and shared stories at dr.dk and social media.

Publication: 4th of January 2016

Credit: Lea Hovmand Jørgensen and

Mads Ra�e Hein

Link to article

An equal society: who will stay at home with a sick child?

1Sygedag

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When we mapped the data we realized that the problem with pollution turned out to be more wide-spread than we ever would have thought. I think that is why it had a huge political astermath and also led to new grants for more scientific investigation into this matter.

Kristian SlothJournalist

In Denmark we have 4000 pig farms. The proportion of huge farms is the largest in Europe and we export to several countries in the world.

Farmers add zinc to the food to lower infection risks – and instead of using antibiotics. The pigs absorb about 6% of the zinc and excretes 94%. The slurry of feces and urine are used by the farmers as a fertilizer. But zinc is not easy to get rid of a�er being spread on farmland. The Data Team got hold of an unpublished scientific report that for the first time in Denmark revealed that fertilizing of farmland has led to a pollution of zinc in an extent that represent a treat to human health and the environment.

With data and visualization, the Data Team revealed the problematic truth to the public.

Publication: 5th of October 2015

Credit: Kristian Sloth and Ninni Pettersson

(graphic designer)

Link to article

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Too much zinc in the farmland

See interactive version

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Who benefits when companies go bankrupt? A data-driven investigation analyzing 45.000 bank-ruptcies in Denmark during the last 10 years show a remarkable answer: The lawyers, who in the first place are hired to secure money for the creditors.45.000 Danish companies went bankrupt during this period. While it’s well known that the financial crisis gave bankruptcy fraudsters good conditions, it is unknown to the public how the majority of bankruptcies are handled: How long does it take before a company is dissolved and all assets distributed? What do lawyers, who treat the thou-sands of bankruptcies, profit? And what is le� for the creditors? The Data Team set out to dig into

data on bankruptcies to examine the consequences of the waves of bankruptcies that have washed over the country in the past 10 years. Earlier, the Bank-ruptcy Council analyzed data-sets with a few hun-dred bankruptcies to assess how long the proceed-ings lasted. The Data Team have pooled numerous public data-sets and managed to create a unique overview of more than 32.000 finished Danish corporate bankruptcies.Journalist Bo Elkjær spent about four months on research and data-processing. In the process colleagues from other teams were given side-stories and the main story was used by web-news, radio-news, TV-news, and TV-documentary-teams.

Publication: 10th of April 2015

Credit: Bo Elkjær, Kristian Sloth, Thomas Rix and Mads Ra�e Hein

Link to article 1 Link to article 2

Denmark gone bankrupt

See interactive version

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Everything should be checked - i.e. 45.000 bankruptcies. That’s why this project is so unique - it was an herculean task.

Bo ElkjærJournalist

Details/tools The initial data-set was scraped from a website using C# to iterate through and parse data from relatively well-formed HTML. A package called HTMLAgilityPack was used to do this easily. Data was saved as a simple CSV-file that later was opened and analyzed in Microso� Excel, Google Sheets and Google Open Refine.

The data-set contained more than 50.000 records and was visualized on a map of Denmark. To plot and animate that amount of points D3 was used - along with TopoJSON, TweenLite, TimeLineLite on a canvas-element.

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Europe is facing the worst refugee-crisis in 70 years. The Data Team decided to develop a big interactive component that would show global data, then for Europe, then zoom to Denmark and at the end from one person’s route from Syria to Denmark in a feature and on a map. We presented the newest data possible from UNHCR, Eurostat, Frontex, the Danish Immigration

Publication: 4th of November 2015

Credit: Benjamin Hughes Dalsgaard, Jens Lykke Brandt, Mads Ra�e Hein, Bo Elkjær, Frederik Fabricius

Smitt, Katrine Birkedal Frich and Nis Kielgast

Link to article 1 Link to article 2

Service, and the municipalities in Denmark. The main task was to collect and compare all the data – and then visualize it all in a way that gave the reader access to as much data as possible. We didn’t want to leave out too much, but would rather make the reader discover the data and draw their own conclu-sions based on the numbers and facts.

PÅ FLUGT

The escape

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This project came from the simple idea of zooming in on the refugee crisis starting with the perspective of the world and then slowly zooming in on Denmark and end up with one person’s way into Denmark. The interactive is developed using LOTS of D3js especially D3 animations, handlebars templating engine, HTML, CSS and Webpack. We wanted to show with dots how many refugees were coming from different countries. This was done by letting one circle represent 5.000 refugees, which gave 424 circles. These circles were moved into their respective country, showing how many refugees are leaving the different countries. The countries and the dots are then transformed, so that the dots represent a bar-chart. Next step transforms them into showing refugees over time. This was our way of humanizing bar-charts. At several stops in the narrative, users can click the elements, countries/municipali-ties, and see more detailed data. For the personal refugee story, we interviewed a refugee about his jour-ney to Denmark. His journey was plotted into a map with relevant pictures and videos from the interview. This makes for a more personal and heart-felt story when the crisis is focused on just one man’s incredible journey.

Details/tools

This interactive presentation of the refugee-crisis is a detailed and nu-anced way to show the data. The read-ers are not forced to any specific opinion, but are able to choose a perspective of the world, Europe, Denmark, or the 22-year old refu-gee Tarek from Syria. The graphic speaks to your head with the hardcore data - and your heart with the feature of one individual.

“Mads Ra�e HeinGraphic designer

See interactive version

See interactive version