The goal of scientific visualization is to help scientists view and better understand their data as their research matures. It is often difficult to understand the data by direct inspection due to its massive size and complexity. Scientific visualization can help with these difficulties by representing the data so that it may be viewed entirely. In the case of varying data during an experiment, animations can be created that show this variation in a natural way. Viewing the data in this way can attract the scientist’s attention to interesting parts of the data (Visualisation Group, 2009).
A visualization of Atmospheric CO2 in the period between March 1958 and March 2011 is a useful example (CO2now.org). Trying to identify any relationships and long-term trends from the data table of atmospheric carbon dioxide concentrations taken over several years may be impossible. However, if this set of numerical information is plotted on the graph – as shown on the website, those complicated numbers start to make sense. The horizontal axis shows different years that were interesting for scientist to investigate, and the vertical axis shows the level of carbon dioxide (CO2) concentration in units of parts per million that coincides in each year. Thus, the graph is showing us the change in atmospheric CO2 concentrations over time. A more important role that graphs play is helping scientists to interpret their data. On the graph, it is easier for scientists to see that the concentration of atmospheric CO2 steadily rose over time (i.e. the upward inclining black broken line shows the long-term trend of average annual CO2 concentrations), and since 1985 it has exceeded its acceptable safety limit.
The ability to visualize their researched statistics, scientists is encouraged to go beyond this initial launch. The relationship between rising CO2 concentration and natural and seasonal changes would be further interpreted. Moreover, it may be concluded that the long-term increase is related to the growing number of human activities that release (Egger 2004). Different campaigns may be set up to discourage burning fossil fuels, using plastic bags etc.
In conclusion, visualization is not only supportive tool in scientific research but also a constructive technique to communicate the research’s results to the public. Visualization helps scientists to move beyond their initial point of collecting data, to make those data become meaningful and useful. Therefore, scientists are encouraged to use scientific visualization from the beginning of their experiments and not just when they think they have everything operating properly (Visualisation Group, 2009)
The co2now.org (2011), Earth CO2 Homepage [Online]. Available at <http://co2now.org/>
Visualisation Group (2009), About the Visualisation Group [Online]. Available at < http://www-vis.lbl.gov/About/>
Anne E. Egger, Ph.D. “Visualizing Scientific Data: An essential component of research,” Visionlearning Vol. SCI-2 (1), 2004.