PODS 2018 : ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems

  in Conferences   Posted on August 4, 2017

Conference Information

Submission Deadline Saturday 09 Dec 2017
Conference & Submission Link https://sigmod2018.org/calls_papers_pods_research.shtml
Conference Dates Jun 10, 2018 - Jun 15, 2018
Conference Address Houston, United States
Proceedings indexed by
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Google Scholar H5-index: 26
CORE 2017 Rating: A*
Guide2Research Overall Ranking: 155
Category Rankings
Databases & Information Systems 41

Conference Call for Papers

Topics of Interest

For the 37th edition, PODS continues to aim to broaden its scope, and calls for research papers providing original, substantial contributions along one or more of the following aspects:

deep theoretical exploration of topical areas central to data management
new formal frameworks that aim at providing a basis for deeper theoretical investigation of important emerging issues in data management
validation of theoretical approaches from the lens of practical applicability in data management. Papers in this track should provide an experimental evaluation that gives new insight in established theories. Besides, they should provide a clear message to the database theory community as to which aspects need further (theoretical) investigation, based on the experimental findings.

Topics that fit the interests of the symposium include, but are not limited to:

concurrency & recovery, distributed/parallel databases, cloud computing
data and knowledge integration and exchange, data provenance, views and data warehouses, metadata management
data-centric (business) process management, workflows, web services
data management and machine learning
data mining, information extraction, search
data models, data structures, algorithms for data management
data privacy and security, human-related data and ethics
data streams
design, semantics, query languages
domain-specific databases (multi-media, scientific, spatial, temporal, text)
graph databases and (semantic) Web data
incompleteness, inconsistency, uncertainty in data management
knowledge-enriched data management
model theory, logics, algebras, computational complexity

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