We now know that our behaviour towards information has been disrupted. As creators, mediators and data consumers, we are faced with new needs. In several respects, the datavisualization is similar to an ally of choice to respond effectively.
– Extract from the White Paper 10:11 “Time is data” –
We now know that our behaviour towards information has been shaken up. As creators, mediators and data consumers, we have to face new needs. In several respects, the datavisualization is similar to an ally of choice to respond effectively.
A positive response to our cognitive specificities
As we have seen before, the Internet has a significant impact on the transformation of our mental processes: memory, concentration, multitasking and learning are all cognitive skills that have been redefined for our digital environment, a study by Mindlab International shows that when making multitasking decisions, we use 20% less cognitive resources when the medium is visual. Visual perception, managed by the visual cortex that analyzes the stimulus received by the retina, is extremely fast in processing the pictorial data. MIT supports this theory with a study by Professor Mary Potter in 2014.
He confirmed the ability of the human brain to quickly understand an image by demonstrating that a pictorial analysis requires only 13 milliseconds of calculation. According to the same test, computers do not yet have such a fast image analysis capability. Therefore, we understand a visual in a minimum of effort: reading an image is therefore a matter of choosing cognitive profitability. On the other hand, the analysis of a text or a situation is not managed by the visual cortex, but by the left cerebral cortex. In 2007, Professor Stanislas Dehaene showed that he is much slower and needs half a second to find the meaning of a term. One of the major advantages of data-notification is that it makes it a priority to use your visual capacities and thus increases the speed of information capture.
It allows to highlight the essential information of the raw data and to script them for a better transmission and memorization. Professor Dehaene also points out that data visualization is both an imaging process, analysis and data management. It is essential that these three elements work in parallel so that the reader, who has become a spectator, can benefit from the added value of a datavisualization. This is the main difficulty of developing a data visualization: it is not only a visual work, but also a multidisciplinary work, integrating at the same time a technical problem, a graphic design and an analysis of the intelligible data, however, choosing a good visual device can be complex, especially in a multidimensional context like Big Data. According to Antal E. Fekete, professor of mathematics and statistics, data visualization allows us to look at data from a new angle: the obvious is brought to light and hidden interpretations appear. His point was illustrated by John Tukey, one of his colleagues, who said: “The greatest value of an image is when it forces us to notice what we would never have expected to see” As we have seen before, the context of data consumption responds to an exponential demand for speed. The need to understand and transmit information quickly is at the heart of each individual’s expectations. Through computer graphics and data analysis, datavisualization makes it possible to maintain a simple and rapid dissemination link of the data and becomes, for example, a means of reducing the time spent on screens. it is a resource that promotes communication between the company and its customers, between members of the same structure or between institutions and citizens. It creates interaction between individuals and a solution to meet the needs of communication and rapid decision-making. It is also an asset to data, giving it operational power and allowing intelligent decision-making by simplifying complex data.
A way to make raw data more accessible
The data may be difficult to understand because of its quantity and quality. It can be difficult to make technical data understandable. Indeed, a flow of information that is too specialized can lead to the same type of cognitive process in humans as when they are confronted with a large amount of information. The data-notification by the study of the data will generate a process of popularization of the information by the image allowing the individual a better understanding, memorization and concentration during the reception of the data. The scenarioization of the data and its analysis will make it possible to reduce the two main difficulties related to the data: quantity and complexity.
To date, it is even possible to go further and use datavisualization to design qualitative services through the creation of digital interfaces. For example, in Canada, researchers have been able to locate infections in premature babies before visible symptoms appear. To achieve this, they generated a flow of more than 1000 data/s, combining sixteen indicators, including pulse rate, blood pressure, respiration and oxygen level. By carrying out a data-update of the data from these indicators, they have succeeded in establishing correlations between minor disruptions and more serious illnesses. Michael Bloomberg, a successful entrepreneur in the digital data industry and mayor of New York City, uses data visualization to increase the efficiency and reduce the cost of public services. In particular, it has improved the city’s fire prevention strategy by registering 25,000 complaints per year about overcrowded housing. The city hall has also created a database listing the city’s 9,000 buildings, supplemented by indicators from 19 municipal agencies: list of tax exemptions, water or electricity cuts, unpaid rents, etc. It is important to note that none of the characteristics selected by the analysts can be considered in itself as a cause of fire, but when put together, they are closely correlated with an increased risk of fire outbreak. This experience has made the work of New York inspectors easier. In the past, only 13% of their visits resulted in an evacuation order. This proportion increased to 70% after the adoption of the new method.
A way to adapt to each individual
Designing a data-notification responds to an increasingly important need for social innovation. Each employee or citizen is put back at the heart of exchanges and decision-making: he or she is recognized both as the creator of the data, but also as an active reader of the data.
Thus, data visualization is a solution to meet the need to focus on the human being and his interactions. It is a tool for holding users accountable within a decision-making process. The realization of a datavisualization necessarily requires a contextual and intelligent analysis of the data. There is an awareness that this data is the result of human interactions and that giving it value also means offering it a social sense. just like neuromarketing, datavisualization can be based on human and cognitive characteristics to positively orient our actions. Today, even if few studies on the impact of data-reporting on our daily lives have been carried out, it would be interesting to bring data visualization towards an objective of improving society and raising awareness. The digital drifts that we have been able to identify: the loss of real sociability, the decline in creativity or even information that is too simplifying could be rebalanced by the datavisualization. The latter is an effective way to meet all the new needs listed in this study, and then for everyone to choose how to use it. It is the reference tool for analysis, interpretation, communication and data exploration. It naturally evolves as a logical response to the behaviours and needs of the connected society. To go further in our reflection, 10h11 and its Research & Development pole contribute to the emergence of scientific studies and research focused on new uses related to data-notification, as well as its effectiveness and necessity in our connected world. Data visualization helps to improve our relationship to data to moderate its density and complexity. It is an emerging practice that is in harmony with the social and cognitive phenomena of data in our society.
However, it is essential to rely on existing methodologies and techniques for the implementation of effective data-notifications.