The real power for security applications will come from the synergy of academic and commercial research focusing on the specific issue of security. This book is suitable for those interested in understanding the techniques for handling very large data sets and how to apply them in conjunction for solving security issues.
ICPSR maintains and provides access to a vast archive of social science data for research and instruction, including a data archive of more than 500,000 files of research in the social sciences. It hosts 16 specialized collections of data in education, aging, criminology, criminal justice, social work, sociology, substance abuse, terrorism, and other fields.
You do not need to be on-campus to create an account but you must log in to your account from a UNCW IP address or UNCW-owned computer at least once to be associated with the UNCW membership.
Aggregates statistical information on over 60,000 topics from more than 18,000 sources, including market research institutes, trade organizations, scientific journals, government databases, and many other private and public resources. Find more detailed information.
The best known and most popular single source of statistics on the social, political, and economic organization of the United States. This database is designed to serve as a convenient, easy-to-use statistical reference source and as a guide to statistical publications and sources.
The largest collection of poll data anywhere—1935 to present, all US polling firms, broad topical coverage of opinions and behavior on social issues, politics, pop culture, international affairs, and more. International and US datasets available for immediate download. Find more information.
You must create an account to access datasets, create crosstabs in RoperExplorer, or download more than 50 questions from iPOLL.
A database of elections data, authoritative analyses, concise explanations, and historical materials to help researchers investigate and understand voting and elections in America from 1789-present.
Mining Massive Data Sets for Security by 