Modelo Dimensional

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Workshop on Database Preservation Data
warehouses in the path from databases to
archives
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Context

• Organizations are increasingly relying on
  databases as the main component of their record
  keeping systems.
• More information, more risk of loosing it in data
  repositories turned unreadable.
• When the current technology gets obsolete
• Hardware
• Operating systems
• Database management systems
• Applications.
• The paperless office increases the risk of losing
  significant chunks of organizational memory and
  thus harming the cultural heritage.

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Previous research

• Preserve the technology
• Preserve specimens of the machines, system
  software and applications, in all their main
  versions, so that the backups of every
  significant system could be used whenever needed
• Simulation
• Simulating the older hardware in newer machines
• Migration
• Up-to-date DBMS
• New DBMS, deep reengineering
• Open neutral format
• Conversion of database contents into XML dialect.

technical
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Preserving digital information

• General problem preserving the wealth of
  information that is being generated in digital
  form or converted to it
• Several projects
• Fundamental models for integrating preservation
  into the management of current records
• From the beginning of IS development
• Added to a previously existing IS
• Solutions to concrete problems that arise in
  specialized domains

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Operational system football data
One fact One record
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Star Event
Largely denormalized
Rich dimensions (authority files)
Basic facts
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Star GameResult
Sum of events of type Goal, including self-goals
from the opponent team
3 points for win 1 point for tie and 0 for defeat
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Parallel attitude

• Data warehouse designer
• Approach a database-centred operational
  information system (IS) to specify a data
  warehouse (DW)
• Integrated model of the organization
• Merge information from a diversity of sources,
  systems and technologies
• Process-centric methodology
• Specify data marts
• Long-term validity and integrity requirements
• Evaluation attitude
• leave out irrelevant details in the data
• Stable monotonic archive
• Expose information contents in a simple and
  systematic way.

• Archivist
• Analyse a document-centred organizational IS to
  specify an archiving policy and system
• Integrated model of the organization
• Merge information from a diversity of sources,
  systems and technologies
• Process-centric methodology
• Classify related series of documents
• Long-term validity and integrity requirements
• Evaluation attitude
• leave out irrelevant details in the documents
• Stable monotonic archive
• Expose information contents in a simple and
  systematic way.

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Differences

• Data warehouse designer
• Answer the information needs of the management
• Decision support
• Monitoring
• Trend analysis and forecast

• Archivist
• preserve the memory of the organization and its
  processes, for future generations

• Goals are different
• Concrete decisions on evaluation and elimination
  procedures may differ
• Different details on metadata

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Research proposal

• Explore the adequateness of the DW approach as a
  target vehicle to perform, with respect to a
  given IS, the functions considered essential from
  an archivist viewpoint like appraisal,
  classification, elimination, description, and
  access while respecting properties like
  authenticity and integrity.
• i. e. How to preserve the information in a
  database
• Not taking the DB as a single digital object
• DB is a complex representation of the facts
  produced by a set of processes

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Three relevant research areas

• Description of documents to render them available
  for retrieval, across the frontiers of domain
  modelling, document nature and storage technology
• grown along with the Web
• Concerns of archivists with the fragility and
  opacity of digital materials
• broader research agenda fuelled by the needs of
  organizations and increased awareness of the need
  for new approaches
• Data Warehouse construction techniques
• transform complex structures in operational DB to
  simple stars

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One solution for DB preservation

• Serialize the database into a single archiving
  model
• Store the data dictionary
• Table names
• Column names
• Integrity constraints
• Store the actual values of each column in each
  table line.

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Why it is not enough

• Data is just part of the problem in a database
  system
• Most real information systems are structured in
  three layers data business rules
  presentation
• The presentation layer may contain not too much
  knowledge
• The data and the business rules layers keep their
  own part of the semantics of the data
• In certain cases, the values are meaningless
  without the code that discloses their
  interpretation

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Database layers

• presentation

business rules
F1
archive
F2
data
F1, F2
data warehouse
operational DB
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Idea

• Perform a previous step of eliciting implicit
  knowledge in the application code and storing it
  as explicit columns in the new data model.
• This operation is a typical step in a DW design
  process.
• Investigate
• Transformation rules from typical structures in
  operational systems into simple star DW
  structures
• XML version for exchange and archive
• Metadata needs technical, semantic, authenticity