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Panel on “Data Infrastructures and Data Management Research: Close Relatives or Total Strangers?”

  • Yannis Ioannidis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7338)

Abstract

In 1981 the “1st LBL Workshop on Statistical Database Management” was held in Berkeley, CA. It was essentially the first step towards establishing the new at the time and very important branch of the data management field that deals with scientific data. A few years later, the third edition of the event already had another ‘S’ added in its acronym and was named the “3rd Int’l Workshop on Statistical and Scientific Database Management”. Eventually, the series became the well-known annual SSDBM conference. For more than 30 years, the requirements for managing and analyzing the data created in the context of research and other activities in many domain sciences have brought out several major challenging problems that have motivated and inspired much data management research. Through the years there have been a very large number of related research papers and keynote presentations in all major database conferences and journals, many significant contributions that have pushed the state of the art in various directions, several dedicated funding programs around the world, and numerous specialized and generic software systems that have been developed targeting scientific data management. Scientists from the biological, medical, physical, natural, and other sciences, as well as the arts and the humanities have worked closely together with data management researchers to obtain solutions to critical problems. All these activities have created a solid body of work that is now considered part of the data management research mainstream, on topics ranging, for example, from the traditional indexing and query processing to the more specialized data mining, real-time streaming, and provenance. Scientific data management is an area of great importance with a long history that will continue to be at the forefront of many interesting developments in the field.

Keywords

Data Management Query Processing Database Management Domain Science Important Branch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yannis Ioannidis
    • 1
    • 2
  1. 1.Dept. of Informatics & Telecommunications, MaDgIK LabUniversity of AthensAthensGreece
  2. 2.“Athena” Research CenterAthensGreece

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