Abstract
Kelp forests serve as an integral abode for aquatic species. Kelp forests are one of the most productive terrestrial systems, providing its denizens the conditions necessary for growth. Wave action allows for the constant motion of the seaweed, which provides maximum sunlight exposure and contact with nutrients.
The kelp forest ecosystem is a complex one. The understanding of the interactions between members of this unique ecosystem can be facilitated through the use of data visualization, a mode through which big data sets — such as the kelp forest — can be better understood.
This particular research project focuses on the kelp forests off the California coast, work that is funded by the NSF/NOAA CAMEO program, and is being conducted by OSU in conjunction with the UCSC, USGS, PISCO, and NOAA.
Previous work has looked at the visualization of this data through the use of D3.js — a javascript library that allows for the creation of dynamic data visualizations — which led to the creation of a network visualization that illustrated the relationship amongst the diverse species found in the kelp forest. While this visualization highlights all the different types of interactions between species, the sheer number of species existent in the SQL database presented a large visualization, one that resulted in a slow load time, as well as a degree of difficulty in parsing the visualization to gain useful insights.
One of the goals with this work was to improve the load time with this particular visualization. Another was to expand the visualizations available through the exploration of a matrix visualization, which would contribute an increased understanding regarding the relationships between species.
