The Unveiling of Big Data and Data Mining: A Relative Absolute Relationship
The recent revelations by Edward Snowden, a former contractor for the US National Security Agency (NSA), have sparked unease and anger over the collection of telephone and email records of citizens. The Obama administration claims that this data collection brings security, but critics argue that it is a violation of privacy. However, one thing is certain: when the NSA uses massive amounts of data to “dig out” information, it benefits from the sharply falling prices of computer storage and processing.
A computer model created by researchers at the Massachusetts Institute of Technology (MIT) to analyze patient heart disease data used data mining and machine learning to screen vast amounts of data. The model found that three types of abnormalities in electrocardiogram data were likely to be associated with a second heart attack within a year, and identified high-risk patients who were not screened by existing methods.
Data Mining: The Extraction of Information from Huge Amounts of Data
Data mining, a term that refers to the extraction of information from huge amounts of data, is often implemented by software algorithms. David Krakauer, director of the Wisconsin School of Exploration, noted that the amount of data growth, as well as the ability to extract information, affects science. He stated that computer processing power and storage space have grown exponentially, and costs have declined exponentially, following Moore’s Law.
The Growth of Big Data
In 2005, a 1TB hard drive cost around $1,000, but now it can be purchased for less than $100. This has led to an unprecedented growth in big data, which is being used in various fields, including commerce, security, and scientific research. The Obama administration’s claims of data collection have sparked unease, but the use of big data in scientific research has led to numerous breakthroughs.
The Medical Field: A Milestone in Big Data
In 2003, the first human genome sequence was completed, marking a milestone in the process of large data. This breakthrough led to the expansion of people, primates, mice, and bacterial genomes available data. Each genome contains billions of “letters,” and the risk of flawed calculations has spawned bioinformatics. With the discipline of software, hardware, and complex algorithms, new science types have emerged.
The University of Chicago Bioinformatics Application
The Institute for Susan Baker Hall at the University of Chicago tested 60 cell lines with 5,000 US Food and Drug Administration-approved anti-cancer drugs. After 300,000 tests, the researchers found that they could access all the data, including RNA expression levels, protein data, and micro-RNA expression data. This data was used to develop targeted drugs and clinical testing.
The Internet: A Prairie Fire of Information
The Internet has become a source of information, with over 500 million tweets per day on Twitter. The Truthy project at Indiana University aims to explore this flood of information and study the ongoing discussions. The project uses data mining technology to identify keywords and track online activities of users.
The Brain: A Complex Computing System
The human brain is a complex computing system, and big data is a relative absolute relationship. The Connected Brain project aims to map out plans to interactions between different brain regions. The project uses three magnetic resonance angiography to observe the structure, function, and connectivity of the brain. The researchers expect to collect around 1 million G data from 1,200 healthy human subjects.
Galaxy Zoo: A Big Data Problem
The Galaxy Zoo project broke the rules of big data by using volunteers to classify galaxies. The project initiated in 2007 in Oxford, England, and used 50,000 pictures from the Sloan Digital Sky Survey. The volunteers classified the galaxies, and the results were used to develop new algorithms.
The Desire to Learn
The desire to learn has long been trying to improve image and voice pattern recognition. The University of Wisconsin-Madison’s Krakauer noted that it has not only improved but also had a practical effect. The speech recognition system on the iPhone is an example of how large amounts of data can be used to train algorithms.
A Phase Transition
Large data applications may experience a “phase transition” when the processing power of a relatively small change makes the results of a breakthrough appear. Krakauer noted that “big data” is a relative term, not absolute, and that it can be regarded as a rate - data we can calculate data than we have to compute large data there has been if you think about collecting planetary position data of Danish astronomer Tycho Brahe.
The Intelligent Evolution of the Universe
Krakauer’s field of study is the intelligent evolution of the universe, from the Big Bang to the brain. He noted that he has no doubt that the relationship between input and output, data and decision-making situation is what he is studying.