Ranking & Metrics
Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.
Research Impact Score:4.79
Contributing Best Scientists:
H5-index:27
Papers published by Best Scientists
Research Ranking (Computer Science)112
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