Dataspaces: A New Abstraction for Information Management

  • Alon Y. Halevy
  • Michael J. Franklin
  • David Maier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3882)

Abstract

Most data management scenarios today rarely have a situation in which all the data that needs to be managed can fit nicely into a conventional relational DBMS, or into any other single data model or system. Instead, we see a set of loosely connected data sources, typically with the following recurring challenges:

– Users want be able to search the entire collection without having knowledge of individual sources, their schemas or interfaces. In some cases, they merely want to know where the information exists as a starting point to further exploration.

– An organization may want to enforce certain rules, integrity constraints, or conventions (e.g., on naming entities) across the entire collection, or track flow and lineage between systems. Furthermore, the organization needs to create a coherent external view of the data.

– The administrators may want to impose a single “support system” in terms of recovery, availability, and redundancy, as well as uniform security and access controls.

– Users and administrators need to manage the evolution of the data, both in terms of content and schemas, in particular as new data sources get added (e.g., as a result of mergers or new partnerships).

References

  1. 1.
    Franklin, M., Halevy, A., Maier, D.: From Databases to Dataspaces: a new abstraction for information management. SIGMOD Record 34(4), 27–33 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alon Y. Halevy
    • 1
  • Michael J. Franklin
    • 2
  • David Maier
    • 3
  1. 1.Google Inc.USA
  2. 2.University of California at BerkeleyUSA
  3. 3.Portland State UniversityUSA

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