New Big Data Analyses with Topology
The term ‘big data’ has become increasingly prevalent in modern dialogue. Professionals throughout a variety of fields have referred to the importance of ‘big data’ in their progress and many others’.
According to an article titled “Big data is being reshaped thanks to 100-year-old ideas about geometry,” scientific developments in Switzerland recently amounted in the creation of a 3-D brain cell atlas using the brain of a mouse. Although the production of such a tool was a feat, scientists have begun undergoing the laborious process of trying to understand this atlas.
In the past, mostly mathematicians and statisticians analyzed data sets, specifically through developments in the Internet and other technologies. Currently, a transformation is occurring in the data analysis field in which experts will be able to better understand certain types of big data sets.
The mouse brain map problem constitutes much of the mathematical subject of topology, the study of characteristics of certain shapes. During the 1900s, topology was studied most theoretically. Since then, however, applications, such as the mouse brain, have emerged, deeming the subject increasingly pertinent to our understanding of different complexities.
As topology focuses on characteristics, it is well-versed to maintain pattern analyses despite interference or outliers. Because of this, topology is seen as a medium to create newer drugs, particularly through its shapely applications to ‘molecule space’ and mapping.
Specifically, the field is called topological data analysis, or TDA. Essentially, TDA influences and categorizes data sets depending on how large they are and what the sets look like. It has become a preferred method of showing data.
While the field of topology and its newfound purpose in big data continue to develop, humanity is getting just a little bit closer to understanding the world around, inside, and outside of us.
By Archita Harathi