This use of computers in the journalistic proses was named Computer-assisted reporting or CAR and altho this innovative attempt was successful it will take one more decade for this new technology to be more widely adopted. The next innovation was during the late 1960s when  Philip Meyer, a journalist for the Detroit Free Press, used a mainframe computer to prove that it was not only individuals from the less-educated Southern regions who were involved in the riots that at the time were spreading throughout Detroit[5]. Meyer later wrote a very influential book titled Precision Journalism that advocated for using these techniques in journalism [6]. 

But during the 2000s with the use of computers at that point integrated into the working environments, a new term for their use emerged. Data journalism was quoted for the first time by Simon Rogers in 2008 in the Guardian Insider Blog [7], as CAR was viewed as a technique for gathering and analyzing data to enhance investigative journalism, data journalism focuses on the role of data in the entire journalistic workflow[5]. Data journalism places greater emphasis on the data itself, rather than solely using data to find or enhance stories. Additionally, while investigative reporters used to struggle with a lack of information, they now face an overwhelming abundance of data they may not know how to handle effectively. 

As information has become more plentiful, the focus of journalism has shifted from hunting and gathering information to effectively processing it. The abundance of data available today can be attributed, in part, to the rise of open data initiatives. The use of open data has led to an exponential increase in the amount of information available, as governments, organizations, and individuals share data that was previously inaccessible. The term “open data” was first used in the context of environmental data in a report titled “On the Full and Open Exchange of Scientific Data” in 1995[8], which called for the sharing of environmental data to enable global scientific collaboration. However, it was not until the early 2000s that the concept of open data gained broader recognition, particularly in the context of government data. The Open Knowledge Foundation launched in 2004, played a significant role in promoting the use of open data, and the launch of Data.gov by the U.S. government in 2009 marked a major milestone in the open data movement. Since then, many other countries and organizations have followed suit, recognizing the potential of open data to drive innovation, promote transparency, and empower citizens. The fields of data journalism and open data have been researched extensively in academia; however, there remains a lack of research exploring their combination. 

Despite sharing the goal of enhancing accessibility and transparency of information for the public, the evolution of data journalism and open data movements has been independent of each other. It is surprising that the combination of these two fields has received little research attention, especially with the increasing availability of open data and data analysis tools that have intertwined the two. The emergence of data journalism has underscored the significance of data analysis in journalism, and open data initiatives have significantly expanded the available information. Although both movements have been extensively researched in academia, their fusion remains largely unexplored. With the growing availability of open data and data analysis tools, it is crucial to continue exploring the potential of merging these fields to promote transparency, accountability, and social progress.

In conclusion, the combination of open data and data journalism is critical for promoting transparency and accountability in today’s society. Journalism plays a vital role in uncovering corruption and promoting social change, and the use of technology has greatly expanded its potential.