plines today) is also increasing at an even faster rate. Intermediate simulation steps must often be preserved for future reuse because they represent substantial computational investments. The sheer volume of these data sets is only one of the challenges that scientists must confront.” Data analyses in some other disciplines (e.g., environmental sciences, wet laboratories in life sciences) are challenged to work for thousands of distinct, complex data sets with incompatible formats and inconsistent metadata.

While the scientific community and the defense industry have long been leaders in generating large data sets, the emergence of e-commerce and massive search engines has led other sectors to confront the challenges of massive data. For example, Google, Yahoo!, Microsoft, and other Internet-based companies have data that are measured in exabytes (1018 bytes). The availability and accessibility of these massive data sets is transforming society and the way we think about information storage and retrieval.

Social media (e.g., Facebook, YouTube, Twitter) have exploded beyond anyone’s wildest imagination, and today some of these companies have hundreds of millions of users. Social-media-generated texts, images, photos, and videos comprise an unexpected and rapidly growing corpus of data. Data mining of these massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity, and national intelligence. New algorithms that assess these data in ways other than counting hits on key words, such as the analysis of social relationships, involves large graph analyses and requires new scalable algorithms.

Understanding and characterizing typical Web behavior dynamically (because the time scale of changes on the Internet is in minutes) presents remarkable challenges. In this cyber-oriented world, behavior that does not fit the patterns is often related to malware or denial-of-service attacks. Recognizing these in time, estimating the impact on human behavior, and responding is a new and emerging challenge that has few parallels in science.

Capturing and indexing the Internet has created whole sets of new industries. Some of the world’s largest companies are trading in information and have built their business model on appropriately customized advertisements. Interpreting user behavior and providing just-in-time advertisements customized to the users’ profiles require very sophisticated data management capabilities and efficient algorithms. Service-sector companies specializing in Internet-based auctions, like eBay or Amazon, have developed sophisticated analytics capabilities. Almost all Web-based companies today are capturing user actions, even if they do not immediately analyze them. This confluence of technologies has created a whole new industry, one based inherently on massive data.



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