Accession Number:

AD1132144

Title:

Data Provenance and Financial Systemic Risk

Descriptive Note:

[Technical Report, Study/Analysis]

Corporate Author:

MITRE CORP MCLEAN VA

Personal Author(s):

• Seligman, Len
• Brady, Shaun
• Blaustein, Barbara
• Mutchler, Paula
• Chapman, Adriane
• Worrell , Charles

Report Date:

2013-01-01

Pagination or Media Count:

5

Abstract:

We describe the needs for data provenance in a large-scale analytic environment to support financial systemic risk analysis. Government financial regulators need to make sense of the outputs of thousands to tens of thousands of simulation runs invoked by a large analytic staff automatic capture of data provenance dataset sources and processing steps supports analysts without adding to their workloads. We present an architecture for automated provenance capture from both simulations and data transformation tools. Finally, we describe a prototype implementation and next steps.

Descriptors:

• data sets
• risk analysis
• models
• prototypes
• simulations
• corporations
• risk
• automatic
• biological sciences
• case studies
• databases
• engineering
• environment
• information systems
• relational databases
• algorithms
• computers
• data integration
• experimental design
• high performance computing

Subject Categories:

• Information Science
• Economics and Cost Analysis

Distribution Statement:

[A, Approved For Public Release]