Data Provenance and Financial Systemic Risk

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.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2013
Accession Number
AD1132144

Entities

People

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

Organizations

  • MITRE Corporation

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Automatic
  • Biological Sciences
  • Case Studies
  • Computers
  • Corporations
  • Data Integration
  • Data Sets
  • Databases
  • Engineering
  • Environment
  • Experimental Design
  • High Performance Computing
  • Information Systems
  • Models
  • Prototypes
  • Relational Databases
  • Risk
  • Risk Analysis
  • Simulations

Fields of Study

  • Computer science

Readers

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