A time-and-value centric provenance model and architecture for medical event streams
Author(s) -
Min Wang,
Marion Blount,
John Davis,
Archan Misra,
Daby Sow
Publication year - 2007
Publication title -
singapore management university institutional knowledge (ink) (singapore management university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/1248054.1248082
Subject(s) - computer science , event (particle physics) , process (computing) , provenance , database transaction , volume (thermodynamics) , software , software architecture , data science , database , software engineering , distributed computing , data mining , operating system , petrology , physics , quantum mechanics , geology
Provenance becomes a critical requirement for healthcare IT infrastructures, especially when pervasive biomedical sensors act as a source of raw medical streams for large-scale, automated clinical decision support systems. Medical and legal requirements will make it obligatory for such systems to answer queries regarding the underlying data samples from which output alerts are derived, the IDs of the processing components used and the privileges of the individuals and software components accessing the medical data. Unfortunately, existing models of either annotation or process based provenance are designed for transaction-oriented systems and do not satisfy the unique requirements for systems processing high-volume, continuous medical streams. This paper proposes a simple, but useful, hybrid provenance model called Time-Value Centric (TVC) provenance.
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