Amanote Research
Register
Sign In
Facilitating Fine Grained Data Provenance Using Temporal Data Model
doi 10.1145/1858158.1858163
Full Text
Open PDF
Abstract
Available in
full text
Date
January 1, 2010
Authors
Mohammad R. Huq
Andreas Wombacher
Peter M. G. Apers
Publisher
ACM Press
Related search
Efficient Parallel Data Structures for Fine-Grained Hypercube Multiprocessors.
Fine-Grained Provenance of Users’ Interpretations in a Collaborative Visualization Architecture
Hair Data Model: A New Data Model for Spatio-Temporal Data Mining
Modified Fine-Grained Data Access Control Algorithms for File Storage Cloud
International Journal of Computer Applications
A Forensic Enabled Data Provenance Model for Public Cloud
Journal of Digital Forensics, Security and Law
Fine-Grained Social Relationship Extraction From Real Activity Data Under Coarse Supervision
Towards a Universal Data Provenance Framework Using Dynamic Instrumentation
IFIP Advances in Information and Communication Technology
Computer Networks
Information Systems
Management
Communications
Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets With Various Granularities
Proceedings of the AAAI Conference on Artificial Intelligence
Supporting Fine-Grained Generative Model-Driven Evolution
Software and Systems Modeling
Modeling
Software
Simulation
