Challenges in Data Collection and Analysis in Multi-National Experimentation
Abstract
Military Warfighting Experimentation is an event used to learn whether a function, method, process, machine, etc will work, or better stated, to learn "how it will work," in a simulated environment in order to make educated determinations for real world operations. In order to make these educated determinations, analysts must collect applicable data and analyze it in a manner/method which answers the questions or hypotheses being investigated. Is the appropriate data being collected and does the analysis plan reflect the aims of the experiment? These questions are applicable in any experimentation endeavor. Multi-national experimentation is no exception. Some of the same challenges that face multi-national experimentation face other types of experimentation while some are uniquely multi-national. We plan to focus upon our insights from experiments MNE4 (Multi-National Experiment 4) and UR 2015 (Urban Resolve 2015) as our basis of exploration realizing that not all findings presented are uniquely multi-national. Realizing that no two experiments are rarely the same, the purpose of this paper is not to create firm and fast rules for data collection and analysis in multi-national experimentation but to leverage findings for future experiments such that we do not "reinvent the wheel". This should help advance and improve the overall community's experimentation results and products.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2007
- Accession Number
- ADA481447
Entities
People
- Jeff Duncan
- Philip S. Farrell