Provenance-Based Belief

Abstract

Provenance has been touted as a basis to establish trust in data. Intuitively, belief in a hypothesis should depend on how much one trusts the relevant data. However, current proposals to assess trust based solely on provenance are insufficient for rigourous decision making. We describe a model of provenance and belief that is necessary and sufficient to incorporate - trust in the data - in a way that supports normative inference. The model is based on the observation that provenance can be viewed as a causal structure which can be used to compute belief from assessments of the accuracy of sources and transformations that produced relevant data. In our model, data sources are like sensors with associated conditional probability tables. Provenance identifies dependencies among sensors. Together, this information allows construction of causal networks that can be used to compute the belief in a state of the world based on observation of data. This model formalizes the role of source accuracy, and provides a method for formally assessing belief that uses only information in the provenance store, not the contents of the data.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
AD1108381

Entities

People

  • Adriane Chapman
  • Barbara Blaustein
  • Chris Elsaesser

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Biomedical
  • C4I

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Application Software
  • Bayesian Networks
  • Biomedical Research
  • Causal Reasoning
  • Climate Change
  • Computations
  • Computer Programs
  • Corporations
  • Data Management
  • Department Of State
  • Hong Kong
  • Internet
  • Materials
  • Models
  • Networks
  • Observation
  • Probability
  • Reasoning
  • Uncertainty
  • Weapons Of Mass Destruction
  • World Wide Web

Fields of Study

  • Computer science

Readers

  • Educational Psychology
  • Emergency Management and Homeland Security.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference