Cloud computing in Data Journalism – power in information

March 21, 2013 / by / 0 Comment

Technology has established a strong presence in developing economies like India. The usage of communication technology has enormously increased with more and more enterprises going online, and a large number of people finding easy access to the internet. However, with this changing face of the Indian economy comes another story, a story that is not as smooth and sparkling as what we see.

There is still work to be done, there is still much more that technology can do to improve the lives of the people, and with smoother governance this side of the story can be just as sparkling and promising as the other.

India is a vast country with an incredibly large population. Governing 1.22 billion people has always been a challenge. Even though most times the government comes up with developmental schemes, the goals are far from satisfactory. The intent is to collect information and make use of it to elevate the general living standards, but what we have is a whole lot of chaos and confusion. Every year thousands of developmental projects get shoved under the carpet, and nobody ever knows what becomes of them. One constructive way to go around clearing this clutter and mess is to organize the data in such a way that everything is easily accessible from any location and at anytime. Cloud computing in data journalism is the need for the day. Well organized and easily accessible developmental data will add power to journalistic observation. Journalists can store all the required data, such as the names of the districts, people affected by a certain disease, and use this information to attain developmental goals. The government and the people in general can greatly benefit from an organized system that readily stores important data which is required to enhance the quality of life.

What is Data journalism?

In the words of Jonathan Stray, professional journalist and computer scientist, “data journalism is obtaining, reporting on, curating and publishing data in the public interest.”

In data journalism, we use metrics, audits and performance measurement techniques. It is a proven model of governance in the corporate sector. Data journalism is, to simplify matters, the adaptation of this thinking for social improvement. Two changes in the recent past have made it possible for well meaning people to embark upon this empowering path. Firstly, the culture of abundant data consumption is here to stay. While data has always been around in some form or the other, technology has made it possible to effortlessly and seamlessly store and distribute this data. With this change comes a desire to collect more information about things that one encounters in order to evolve oneself and society. In some ways this cultural change compels previously secretive organizations to work with more transparency and share the information with the public. The Right to Information (RTI) act in India is an example of such legislation – this act enables ordinary citizens to demand information from the government on just about anything.

The second factor influencing the evolution of data journalism is the increasing digitization of information within government departments combined with the evolution of standard data formats. This has made a wealth of data available through easily accessible channels. In combination these two factors have brought us very close to a crucial point when it comes to the accountability of government departments and in effect, the evolution of society.

That is one part of the problem – the accessibility of information and data.

The second and equally interesting problem lies in the interpretation and analysis of that data to get to meaningful observations and insights. This, along with other things, requires the processing of large amounts of data in reasonably short periods of time and the storage of this data in structures that can be accessed and queried using standard tools. The advancement of Big Data technologies has made this activity much simpler today. Tools such as distributed databases and cloud computing make it possible for data to be processed and consumed in ways that were not possible even a few years ago. The evolution of these technologies is happening at such a rate that current usage of these technologies is probably lagging, especially when it comes to usage in the non-commercial domain.

With the increasingly easy availability of data and the affordable access to data crunching technologies, it is possible to combine information and technology for the betterment of society.


As with any major change in societal behavior, there are some challenges that will need to be faced and overcome. These challenges exist on two fronts – data security and data presentation. The integrity of data is at the top of the first list. If the data one is using is based on falsehood or even inefficient data collection methods, the entire exercise loses its value. The collection of data requires secure methods for gathering, storing, and disseminating it. When it comes to the visualization of the data that is compiled and crunched, increasing volumes of data present interesting challenges. Not only does the data need to be presented visually in order to be of effective use, but the visualization also needs to be inclusive when it comes to the consumers of the data. The last and probably biggest challenge will probably lie in people’s minds – where the ones with exclusive access to data do not want to part with it, but technology has a way of moving ahead, disruptively, if required.

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