Data Bases in Brahms Analysis

  1. Purpose.
    1. Persistent storage of data.
    2. Data exchange between programs.
    3. Data sharing between colaborators.
    4. Documentation of the analysis process.
  2. What data needs persistent storage?
    1. Describe analysis scenarios.
    2. Make data flow diagrams.
    3. HPSS resident data.
    4. CVS repositories.
    5. Other data bases.
    6. Run organized data.
    7. Detector organized data.
    8. Organization of calibration data.
    9. BRAHMSROOT.
  3. Analysis step (working style).
    1. Programs used.
    2. Data used.
    3. Temporary results.
    4. Committing the final result.
  4. Documentation of Analysis.
    1. Data dependensies and analysis steps.
    2. Authorization of data.
  5. Location of data bases.
    1. One server many clients.
    2. Growing data bases.
    3. Readonly data bses.
    4. Local copies of data bases.
    5. Committing to the master data base.
    6. Data base identification.
    7. Moving data bases.
  6. What functionality (API).
    1. Relational or Object oriented.
    2. Open and Create Data base.
    3. Put, Get and Remove entity.
    4. Replace and Update entity.
    5. Check entity.
    6. Iterate entities.
    7. Select and iterate entities.
  7. Choice of data base machinery.
    1. Complexity of use.
    2. Functionality needed.
    3. Data security.
    4. Objectivity.
    5. MySql.
    6. Root.
    7. gdbm.
  8. Dbase, a small API using gdbm.
    1. Separation of application.
    2. Interface methods.
    3. DbaseEntity.
    4. DbaseVersionedEntity
    5. Demo programs.