I love to imagine the future of Data Journalism because practice leads to action; to come into motion in order to make things happen or transform them into better ones, through experimentation.
But that future requires team work, where good ideas are encouraged, shaped, and brought to life. It also entails investing time to learn, relearn, and share what has been learned; safe routes to a solid knowledge, capable of raising the quality of data analysis and, implicitly, that of journalism as a whole.
Imagining the future also unleashes the potential of creativity and exercises perseverance to discover in the problems that we currently face as an industry, the possibilities to transform ourselves.
Based on these axes, I propose six ways to imagine how data journalism will consolidate as of 2015. They are not written in stone. They are starting points for discussion and evaluation through the perspective of your own experience and the reality of journalism in your country.
The new generation of journalists, those who are currently studying or about to start college, will put an end to the old dichotomy that led many of us to choose this profession because “we are good at writing, not math”.
For future reporters, that division is nonsense because they will not conceive the understanding of reality without expressing the same with data accompanied by a critical narrative view of the facts.
That generation will be skilled in what I call “Grammathematics” (Grammar + Mathematics); and will be so by learning on their own or by taking specialized courses. They will not wait for universities to adapt their curricula to the surroundings imposed by the growth of big data, a trend that will not be reversed.
Society will definitely ride off to an increasingly data-centered culture and the new generation of journalists will not have to ask themselves: What do we do now with these databases? They will know exactly how to analyze it, extract information and, most relevant of all, squeeze the knowledge.
Data journalism is increasingly amalgamated with statistics, mathematics, engineering, computer programming, and any other discipline that involves the development of abstract thinking. That emerging journalism is more holistic, closer to what we now know as Data Science and Business Intelligence.
Its followers are not only able to extract data from various sources and visualize it. They can also correlate it consistently, apply different analysis methods, contextualize it – through deep research – and present it as a solid and useful interactive product; with its ideal viewpoints for mobiles and other devices that capture the interest of their audience and takes them to make more informed decisions.
Journalists will have an intellectually strong arm to navigate amidst databases without the wow factor being the volume of data or software to handle the same. They will know enough about these subjects to, if necessary, do things on their own; but also to communicate effectively with their allied engineers, programmers and interactive designers when the complexity of the project so requires.
What will be crucial is the quality of knowledge generated by the analysis, the balanced visualization of functional and aesthetic aspects, the human story behind the numbers. The reaction caused by the research on audiences exposed to consistent evidence based on data will be a defining matter as well.
It will be necessary to learn to use the data more intelligently, to understand that while large volumes of data may be involved, there is still a risk of producing content, applications and / or visualizations that are totally Irrelevant.
When we get to transform information into knowledge, we will have evolved as an industry. The information itself will cease to be hegemonic in newsrooms; the strategy will be to define, with data, how to create added value for the life of the audience.
Multidisciplinary teams working together in data journalism will no longer be the exception to the rule.
Ideas to define approaches, visualization, audiovisual production, and even the ideal story for multiple platforms will no longer be proposed unilaterally by journalists, but established in conjunction with programmers, engineers, designers, audiovisual producers, and other key professionals in the creation of data based products.
The best way to achieve this integration will be by adapting guidelines of the Project Management methodology; creating a flexible guide of objectives, organization, planning, monitoring, and control of resources for the success of each project.
So, the disconnection where everyone produces their share of the project and then unifies it with that of others will be history.
In my country, Costa Rica, we say: “One swallow doesn´t make a summer”. In that sense, it is not data journalism that which simply takes five or six figures from a source and arranges them in a nice chart.
Data journalism goes far beyond that because it is born from the womb of a rigorous analysis of information; from thorough research to try to understand what lies behind those numbers and how that will impact the lives of people.
Journalism still needs its old storytelling ability, but it must do so by balancing math and grammar.
The substance (the quality of analysis) will be like the foundation of a house; making it consistent will be critical and crucial. Then, we will define the details of the finish (the way of telling).
Taking care of the form will be decisive, but in order to adequately convey to most people the knowledge gained about the problem meticulously analyzed.
In business, nobody creates a product to be left to its fate and see it die. The product is launched, tested, adjusted, and updated so that it remains effective and consumable.
In data journalism, we will learn more of the corporate vision and marketing to keep our projects alive and usable.
As a commandment, we must periodically refresh the data of our applications and update the contents according to the trends revealed to us by the continued study of such data. We will learn also to develop more effective and faster ways to analyze data in real time without losing sight of the useful approach for audiences.