Call For Papers:  Workshop on Self-Managing Database Systems
              co-located at ICDE 2020 in Dallas, Texas, USA

[Main focus]

    The aim of the SMDB workshop is to provide a forum for researchers from both industry and
    academia to present and discuss ideas related to self-management and self-organization in
    data management systems ranging from classical databases to data stream engines to large-scale
    cloud environments that utilize advanced AI, machine learning, and data mining and analysis.

[Important Dates]

    Paper Abstract (optional):    January 6, 2020 (Monday) 5:00:00 PST
    New Paper Submission:         January 23, 2020 (Tursday) 5:00:00 PM PST
    Short Paper Submission:       January 23, 2020 (Tursday) 5:00:00 PM PST
    Notification of acceptance:   February 13, 2020 (Thursday)
    Camera-ready:                 February 28, 2020 (Friday)
    Workshop:                     April 20, 2020 (Monday)

[Submission]

    submission site: https://cmt3.research.microsoft.com/SMDB2020

    Authors of a selection of accepted papers will be invited to submit an
    extended version to the Distributed and Parallel Databases (DAPD) journal.

[Topics of interest]

Topics of interest include, but are not limited to:

    * Principles and architecture of autonomic data management systems
    * Retro-fitting existing systems vs. designing for self management
    * Self-* capabilities in databases and storage systems
    * Data management in cloud and multi-tenant databases
    * Autonomic capabilities in database-as-a-service platforms
    * Automated testing of data management systems
    * Automated physical database design and adaptive query tuning
    * Automated provisioning and integration
    * Automatic enforcement of information quality
    * Robust query processing techniques
    * Self-managing data stream engines and adaptive event-based systems
    * Self-managing distributed / decentralized / peer-to-peer information systems
    * Self-management of internet-scale distributed systems
    * Self-management for big data infrastructures
    * Monitoring and diagnostics in data management systems
    * Policy automation and visualization for datacenter administration
    * User acceptance and trust of autonomic capabilities
    * Evaluation criteria and benchmarks for self-managing systems
    * Self-evaluation of data management services in the cloud
    * Use cases and war stories on deploying autonomic capabilities

[Organizers]

    Panos K. Chrysanthis, University of Pittsburgh, panos@cs.pitt.edu
    Meichun Hsu, Oracle Corporation, meichun.hsu@oracle.com
    Herodotos Herodotou, Cyprus University of Technology, herodotos.herodotou@cut.ac.cy
    Yingjun Wu, Amazon Web Services, wu.yj0616@gmail.com
    Constantinos Costa, University of Pittsburgh, costa.c@cs.pitt.edu



[PC Members]

    Alex Delis, University of Athens, Greece
    Alkis Polyzotis, Google, USA
    Alkis Simitsis, Microfocus, USA
    Andreas Kipf, TU Munich, Germany
    Bailu Ding, Microsoft Research, USA
    Deepak Majeti, Vertica/MicroFocus, USA
    Eduardo Cunha de Almeida, Federal University of Paraná, Brazil
    Jeff Lefevre, UCSC, USA
    Jiaheng Lu, University of Helsinki, Finland
    Kai-Uwe Sattler, Ilmenau University of Technology, Germany
    Khuzaima Daudjee, University of Waterloo, Canada
    Matthias Sax, Confluent, USA
    Ryan Marcus, MIT, USA
    Sam Lightstone, IBM, Canada
    Stefanie Scherzinger, OTH Regensburg, Germany
    Vivek Narasayya, Microsoft Research, USA
    Yao Lu, Microsoft Research, USA

[Web Site]

    https://db.cs.pitt.edu/smdb2020/