TY - GEN
T1 - Towards web-scale how-provenance
AU - Deutch, Daniel
AU - Gilad, Amir
AU - Moskovitch, Yuval
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/19
Y1 - 2015/6/19
N2 - The annotation of data with meta-data, and its propagation through data-intensive computation in a way that follows the transformations that the data undergoes ('how-provenance'), has many applications, including explanation of the computation results, assessing their trustworthiness and proving their correctness, evaluation in presence of incomplete or probabilistic information, view maintenance, etc. As data gets bigger, its transformations become more complex, and both are being relegated to the cloud, the role of provenance in these applications is even more crucial. But at the same time, the overhead incurred due to provenance computation, in terms of time, space and communication, may limit the scalability of how-provenance management systems. We envision an approach for addressing this complex problem, through allowing selective tracking of how-provenance, where the selection criteria are partly based on the meta-data itself. We illustrate use-cases in the web context, and highlight some challenges in this respect.
AB - The annotation of data with meta-data, and its propagation through data-intensive computation in a way that follows the transformations that the data undergoes ('how-provenance'), has many applications, including explanation of the computation results, assessing their trustworthiness and proving their correctness, evaluation in presence of incomplete or probabilistic information, view maintenance, etc. As data gets bigger, its transformations become more complex, and both are being relegated to the cloud, the role of provenance in these applications is even more crucial. But at the same time, the overhead incurred due to provenance computation, in terms of time, space and communication, may limit the scalability of how-provenance management systems. We envision an approach for addressing this complex problem, through allowing selective tracking of how-provenance, where the selection criteria are partly based on the meta-data itself. We illustrate use-cases in the web context, and highlight some challenges in this respect.
UR - http://www.scopus.com/inward/record.url?scp=84944315773&partnerID=8YFLogxK
U2 - 10.1109/ICDEW.2015.7129547
DO - 10.1109/ICDEW.2015.7129547
M3 - Conference contribution
AN - SCOPUS:84944315773
T3 - Proceedings - International Conference on Data Engineering
SP - 68
EP - 70
BT - ICDEW 2015 - 2015 IEEE 31st International Conference on Data Engineering Workshops
PB - Institute of Electrical and Electronics Engineers
T2 - 2015 31st IEEE International Conference on Data Engineering Workshops, ICDEW 2015
Y2 - 13 April 2015 through 17 April 2015
ER -