Data Science And Scientific Discovery

We live in a world where every day there is a new challenge. As we solve these challenges, we create volumes of information that change the way we perceive the world around us. This systematic method of research, directed at understanding every aspect of our perceivable universe based on evidence, is what we call as science.

THE ROLE OF SCIENCE IN HUMAN HISTORY

The history of science claims a timespan from ancient history to present time. During this period, there has been an emergence of numerous scientific revolutionaries, methods and scientific discoveries. According to Britannica,

“A new view of nature emerged, replacing the Greek view that had dominated science for almost 2,000 years. Science became an autonomous discipline, distinct from both philosophy and technology and came to be regarded as having utilitarian goals”- (Encyclopedia Britannica, 2016)

Over the centuries, the domain of science has expanded exponentially. To a great extent, it has helped us to answer what is happening, why it is happening and what will happen in a wide array of fields such as Astronomy, Biology, Ecology, Genetics, Physics and many more.

So far, scientific research has followed the traditional approach of deductive reasoning. In the deductive process, a hypothesis is created and then experiments are carried out to test its validity. Unfortunately, with this approach, it could be years before sufficient data is gathered from tests to support the claim and back it up with resounding and definitive results.

Figure 1 - Data Intensive Science (Slideshare.net, 2016)

However, this approach has been changing, and at an exponential speed thanks to the advances in knowledge and technology. As an evidence of the speed of growth of the field, today we have access to 2.5 quintillion bytes (Storagenewsletter.com, 2016) of data every day and cheap computational processing power at hand. This renewed scenario has made new techniques of research possible, which were not possible earlier, due to technological and. The field that combines data-oriented techniques is known as “Data Science”.

DATA SCIENCE: A SHIFT OF PARADIGM

Data science is a multidisciplinary field that combines the power of machine learning, artificial intelligence, data mining, statistics, applied mathematics, and visualization. The field also focuses on providing the ability to perform both deductive and inductive reasoning. While the former is hypothesis driven, the later focuses on refining existing hypothesis or generating new hypothesis by spotting interesting patterns available in huge heterogeneous and unstructured data. This approach of data science is helping the scientific community to accelerate the rate of scientific discoveries.

Figure 2 - TimeLine data science (→, 2015)

DATA SCIENCE IN THE AID OF SCIENTIFIC DISCOVERIES

To give an example, In the field of high-energy particle physics, there are instruments such large hadron collider (O'Reilly Media, 2015), that are used to break open atoms and examine its constituents. This process produces exabytes of data, which makes its analysis dependent on powerful supercomputers and advanced data science techniques. These techniques have recently led to the discovery of Higgs-Boson particles and this is considered as a landmark achievement in the history of particle physics.

Another example worthy to be mentioned is from the field of genetics, where the researchers, in order to understand the relationship between complex diseases and genetic effects (Feero, Guttmacher and Manolio, 2010), are also using data science techniques and so far they have been able to identify connections between 2000 genes and 300 common human diseases traits.

Figure 1Large Hydron Collider (Apod.nasa.gov, 2016)  and Genome (IFLScience, 2015)

WHERE DATA SCIENCE IS GOING IS YET TO BE TOLD

The potential of data science is vast and inspiring. Watch this space for more information on data science. During the coming weeks, a deeper study will be performed, starting by providing details on the active users of data science for scientific discovery, the challenges they face and the ways they solve the problems.

Tags: data science, big data, scientific discovery, research, data processing, data analytics, scientific process, inductive process.

Bibliography

Encyclopedia Britannica. (2016). physical science | Definition, History, & Topics. [online] Available at: http://www.britannica.com/science/physical-science [Accessed 22 May 2016].

Storagenewsletter.com. (2016). StorageNewsletter » Every Day We Create 2.5 Quintillion Bytes of Data. [online] Available at: http://www.storagenewsletter.com/rubriques/market-reportsresearch/ibm-cmo-study/ [Accessed 22 May 2016].

O'Reilly Media. (2015). Big science problems, big data solutions. [online] Available at: https://www.oreilly.com/ideas/big-science-problems-big-data-solutions [Accessed 22 May 2016].

Feero, W., Guttmacher, A. and Manolio, T. (2010). Genomewide Association Studies and Assessment of the Risk of Disease. New England Journal of Medicine, 363(2), pp.166-176.

Anon, (2016). [online] Available at: http://renci.org/wp-content/uploads/2015/11/SCi-Discovery-BigData-FINAL-11.23.15.pdf [Accessed 22 May 2016].

Anon, (2016). [online] Available at: https://www.boozallen.com/content/dam/boozallen/documents/2015/12/2015-FIeld-Guide-To-Data-Science.pdf [Accessed 23 May 2016].

→, V. (2015). History of Data Science (Infographic). [online] What's The Big Data?. Available at: https://whatsthebigdata.com/2015/02/17/history-of-data-science-infographic/ [Accessed 23 May 2016].

Apod.nasa.gov. (2016). APOD: 2011 December 18 - Hints of Higgs from the Large Hadron Collider. [online] Available at: http://apod.nasa.gov/apod/ap111218.html [Accessed 23 May 2016].

IFLScience. (2015). Entire Human Genome Can Now Be Sequenced For Just $1,000. [online] Available at: http://www.iflscience.com/health-and-medicine/entire-human-genome-can-now-be-read-1000 [Accessed 23 May 2016].

Slideshare.net. (2016). The fourth paradigm: data intensive scientific discovery - Jisc Digif…. [online] Available at: http://www.slideshare.net/JISC/the-fourth-paradigm-data-intensive-scientific-discovery-jisc-digifest-2016/4 [Accessed 23 May 2016].