Simulation Experiments: Better Data, Not Just Big Data

Abstract

Data mining tools have been around for several decades, but the term "big data" has only recently captured widespread attention. Numerous success stories have been promulgated as organizations have sifted through massive volumes of data to find interesting patterns that are, in turn, transformed into actionable information. Yet a key drawback to the big data paradigm is that it relies on observational data--limiting the types of insights that can be gained. The simulation world is different. A "data farming" metaphor captures the notion of purposeful data generation from simulation models. Large-scale designed experiments let us grow the simulation output efficiently and effectively. We can explore massive input spaces, uncover interesting features of complex simulation response surfaces, and explicitly identify cause-and-effect relationships. With this new mindset, we can achieve quantum leaps in the breadth, depth, and timeliness of the insights yielded by simulation models.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2014
Accession Number
ADA617604

Entities

People

  • Susan M. Sanchez

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Agent-Based Simulations
  • Big Data
  • Climate Change Adaptation
  • Commerce
  • Communities
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Experimental Design
  • Information Science
  • Observation
  • Operations Research
  • Simulations

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Strategic Security Studies

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Quantum Computing
  • Space