Data is everywhere—from government statistics to the architect creating new concepts of the world through to companies and businesses analyzing historical data for accurate projections. Similarly, the journalist must have access to data to produce reliable news and stories. By this, we mean open data access. This is the idea that some data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents, or other mechanisms of control. It is data anyone can access, use, or share. Where journalism is telling a story, open data gives stories new perspectives, more credibility, and easier means to explain complex topics and issues to the audience.
The growth of data is the next significant thing. With data, we can respond to problems around us, such as financial, transport, science and environment, natural disasters, climate change, and to which we can have structured solutions. How do we then combine data, technology, and writing in the service of telling stories about our world today and yesterday? Although journalists can go all out independently to gain such additions to their skills, curricula must move forward, and teach us more of what we need to know, show us these possibilities exist and are helpful–to face the growing trends of digitization.
Traditional journalistic work is presented to the reader in its complete, hopefully perfect form, while open journalism encourages reader participation from the start. It represents a key change in the role’s perception of news agencies—rather than being a sheer distributor of the news; it becomes a knowledgeable voice that steers a discussion around the news.
Open journalism has the power to turn all of us into experts, each with our own unique experience, skills, and perspective that contribute to the global story, and reporters who can use the power of the web can produce stronger, better stories.
What then is data journalism?
It is a journalism specialty reflecting the increased role that numerical data is used in the production and distribution of information in the digital era. It reflects the increased interaction between content producers (journalists) and several other fields such as design, computer science, data science and analytics, and statistics. Data journalism can be based on any data that has to be processed first with tools before a relevant story is possible. Here, we consider computer-assisted reporting, data-driven journalism, coupled with data visualization.
Computer-assisted reporting describes the use of computers to gather and analyze the data necessary to write news and stories. Using computers, software, and the Internet has changed how reporters work across the world. Reporters routinely collect information in databases, analyze public records with spreadsheets and statistical programs, study political and demographic changes with geographic information system mapping, conduct interviews by e-mail, and research background for articles on the Web. Collectively this has become known as computer-assisted reporting or CAR.
Data-driven journalism describes a journalistic process based on analyzing and filtering large data sets for the purpose of creating a news story. This process thrives on resources such as open-source software, open access publishing, and open data. It covers a wide range of tools, techniques, and approaches to storytelling, aiming at providing information and analysis to help inform us all about important issues of the day.
It is primarily a workflow that consists of digging deep into data by scraping, cleaning, and structuring it, filtering by mining for specific information, visualizing and making a story. When information was scarce, most of our efforts were devoted to hunting and gathering. Now that information is abundant and overflowing, the processing is more important—the need to analyze to bring sense and structure out of the never-ending flow of data, and presentation to get what is relevant to the consumer. Like science, data journalism discloses its methods and presents its findings in a way that can be verified by replication.
It builds on the growing availability of open data that is freely available online and analyzed with open-source tools. It strives to reach additional levels of service for the public, helping consumers, managers, and politicians to understand patterns and decide based on the findings. Data-driven journalism might help to put journalists into a role relevant to society in a new way. Simply, it is about journalists using data to enhance their stories. If you have ever seen a graph or an infographic in a news story, then you have been exposed to data journalism. Data is a significant source for journalists to use because it lends credibility to their sources and can help explain complex topics to the public visually.
See it as a new set of skills for searching, understanding, and visualizing digital sources in a time that basic skills from traditional journalism just are not enough. It is not a replacement of traditional journalism, but an addition to it. Data-driven journalism is the future; hence journalists need to be data-savvy. Traditionally, you would get stories by chatting or interviewing people. Today, a more effective way is the use of data and equipping yourself with the tools to analyze it, picking out what is interesting and keeping it in perspective, helping people out by really seeing where it all fits together. It is bridging the gap between statistics users and a skilled user of words—identifying trends that are not just statistically significant, but relevant to decoding the integrally complex world of today.
Talking about data visualization involves the creation and study of the visual representation of data, meaning information that has been abstracted in some schematic or graphic form, including attributes or variables for the units of information. A primary goal of data visualization is to communicate information clearly and efficiently via statistical graphics, plots, and information graphics. Numerical data may be encoded using dots, lines, or bars to visually communicate a quantitative message. It is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends, and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization. It makes complex data more accessible, understandable, and usable.
However, the challenges and opportunities presented by the digital revolution continue to disrupt journalism. In an age of information abundance, journalists, and citizens alike all need better tools, whether we are gathering health data to analyze causes and effects of Ebola on the West African sub-region; the extent of damage to natural resources in DR Congo; processing a free school feeding exercise data dump; looking for the best way to visualize the number of illegal Ghana electricity connection points or visualizing the number of Ghana water company burst pipes.
Today, for news to even reach citizens, journalists must get creative and ensure the content that matters to people is reaching them in quality. Only quality journalism can survive the ‘disruption’. Journalists must improve and increase the value of data for the public by picking through datasets. Adding visualizations and infographics further enhances journalists’ stories, and shapes new angles to narrate and discuss topics. Thus, journalists are becoming data providers to the audience and are on the front-line making data into knowledge.
Author: Richard Kafui Amanfu – (Director of Operations, Institute of ICT Professionals, Ghana)
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