Conference Information
SIGMOD 2020: ACM Conference on Management of Data
Submission Date:
2019-10-22 Extended
Notification Date:
Conference Date:
Portland, Oregon, USA
CCF: a   CORE: a*   QUALIS: a1   Viewed: 66741   Tracked: 158   Attend: 12

Conference Location
Call For Papers
The annual ACM SIGMOD conference is a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results, and to exchange techniques, tools, and experiences. We invite the submission of original research contributions relating to all aspects of data management defined broadly, and particularly encourage submissions on topics of emerging interest in the research and development communities. 


Topics of interest include but are not limited to the following:

    Benchmarking and performance evaluation
    Crowd sourcing
    Data models, semantics, query languages
    Data provenance
    Data visualization
    Data warehousing, OLAP, SQL Analytics
    Database monitoring and tuning
    Database security, privacy, access control
    Database usability
    Databases for emerging hardware
    Distributed and parallel databases
    Graph data management, RDF, social networks
    Information extraction
    Information retrieval and text mining
    Knowledge discovery, clustering, data mining
    Query processing and optimization
    Schema matching, data integration, and data cleaning
    Scientific databases
    Semi-structured data
    Spatio-temporal databases
    Storage, indexing, and physical database design
    Streams, sensor networks, complex event processing
    Transaction processing
    Uncertain, probabilistic, and approximate databases
    Machine learning for data management and vice versa

SIGMOD welcomes submissions on inter-disciplinary work, as long as there are clear contributions to management of data.


All aspects of the submission and notification process will be handled electronically. Submissions must adhere to the paper formatting instructions. Research papers will be judged for quality and relevance through double-blind reviewing, where the identities of the authors are withheld from the reviewers. Author names and affiliations must not appear in the papers, and bibliographic references must be adjusted to preserve author anonymity. Submissions should be uploaded at: (which will be open for submission starting June 9, 2019). 
Last updated by Maxwell Nee in 2019-10-05
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