Title
Provenance Inference Techniques: Taxonomy, comparative analysis and design challenges.
Abstract
Provenance has many applications in assessing the data quality, computational efficiency, security, and storage reliability. Provenance inference (PI) is the process of forming conclusions derived through any evidence or reasoning by static code analysis. However, despite its manifold applications, the subject of PI has not been thoroughly studied and emphasized upon. The main objective of this article is to provide a comprehensive review of the available literature on provenance inference techniques (PITs). To achieve this, we first identify the needs and requirements essential for PITs. Then, a thematic classification of the existing PITs is proposed in form of taxonomy. Moreover, we perform a comprehensive comparative analysis by highlighting the strengths and weaknesses of the existing literature on PITs. Furthermore, we have identified a set of design challenges, which should be taken into consideration. Finally, we conclude the paper by presenting recommendations, issues and open research challenges that should be considered by future research studies in this domain.
Year
DOI
Venue
2018
10.1016/j.jnca.2018.03.004
Journal of Network and Computer Applications
Keywords
Field
DocType
Provenance,Provenance inference,Computational efficiency,Security,Data quality
Open research,Data science,Static program analysis,Data quality,Computer science,Inference,Provenance,Thematic map,Strengths and weaknesses,Distributed computing
Journal
Volume
ISSN
Citations 
110
1084-8045
1
PageRank 
References 
Authors
0.35
69
5
Name
Order
Citations
PageRank
Umber Sheikh110.35
Abid Khan28018.94
Bilal A. Ahmed36117.20
Abdul Waheed416632.70
Abdul Hameed519013.33