Long Term Sustainment of Digital Information for Engineering Design: Model Driven Approach

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Long Term Sustainment of Digital Information for
Engineering Design Model Driven Approach

• Sudarsan Rachuri
• National Institute of Standards and Technology/
• George Washington University
• USA
• sudarsan_at_nist.gov

2
Acknowledgements

• Joshua Lubell
• Mahesh Mani
• Sub
• DPG Group

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Overview

• Digital Preservation
• OAIS
• 2006 LTKR Workshop Report
• Product Model
• Beyond Geometry NIST CPM/OAM
• Annotations for Archiving
• Standards and Semantic Interoperability
• Sustainment of Digital Information for Science
  and Engineering Requirements
• Conclusions

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Digital Preservation A Status check

• Terry Kuny 1 listed various issues of archiving
  in his 1997 paper
• Increasing loss of digital information
• Information explosion
• Proliferation of digital formats with hardware
  and software dependencies.
• Decrease of Financial resources available for
  libraries and archives
• Increasingly restrictive IPRs
• Increasing privatization of archiving
• Standards will not emerge to solve fundamental
  issues with respect to digital information.

1A Digital Dark Ages? Challenges in the
Preservation of Electronic Information 63RD IFLA
Council and General Conference
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Digital Preservation

• Goal
• To identify challenges, research, and
  implementation issues in digital preservation of
  information with an emphasis on design and
  manufacturing.
• Focus on policies of digital preservation and
  applying promising technologies to solve
  preservation problems in product design,
  engineering, and manufacturing in particular,
  with possible extensions to include chemistry,
  biology, and other disciplines where critical
  information must be "future-proofed.
• Three main methods of digital preservation
  technology preservation technology emulation
  information migration.

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LTKR NIST WORKSHOP 2006

• Main themes
• a view of LTKR as an archiving process
• an emphasis on business case development.
• Main Issues
• lack of support understanding of LTKR in the
  engineering community
• An economic model to rationalize archiving
• lack of formal methods and standards for long
  term retention of engineering knowledge
• uncertainty in the utility of the archived data,
  inefficient archival procedures
• Clear Policy guidelines and cost-benefit models

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A Mind Map for LTKR
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OAIS ENVIRONMENT
Environment Model of an OAIS
Obtaining Information from Data

• Producer is the role played by those persons, or
  client systems, who provide the information to be
  preserved
• Management is the role played by those who set
  overall OAIS policy as one component in a broader
  policy domain
• Consumer is the role played by those persons, or
  client systems, who interact with OAIS services
  to find and acquire preserved information of
  interest

OAIS Archive External Data
Information Package Concepts Relationships
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Reference Model for OAIS

• It addresses the following preservation functions
  
• Ingest
• Archival storage
• Data management
• Access
• Dissemination
• Migration to new media and forms
• Data models
• Role of software in information preservation
• Exchange among archives
• The OAIS Reference Model is designed as a
  conceptual framework in which to discuss and
  compare archives.

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OAIS Functional Entities

• Ingest functions include receiving SIPs,
  performing quality assurance on SIPs, generating
  an Archival Information Package (AIP) which
  complies with the archives data formatting and
  documentation standards, extracting Descriptive
  Information from the AIPs for inclusion in the
  archive database, and coordinating updates to
  Archival Storage and Data Management.
• Archival Storage provides the services and
  functions for the storage, maintenance and
  retrieval of AIPs. Its functions include
  receiving AIPs from Ingest and adding them to
  permanent storage, managing the storage
  hierarchy, refreshing the media on which archive
  holdings are stored, performing routine and
  special error checking, providing disaster
  recovery capabilities, and providing AIPs to
  Access to fulfill orders.
• Data Management This entity provides the
  services and functions for populating,
  maintaining, and accessing both Descriptive
  Information which identifies and documents
  archive holdings and administrative data used to
  manage the archive.
• Administration This entity provides the services
  and functions for the overall operation of the
  archive system.
• Preservation Planning This entity provides the
  services and functions for monitoring the
  environment of the OAIS and providing
  recommendations to ensure that the information
  stored in the OAIS remains accessible to the
  Designated User Community over the long term,
  even if the original computing environment
  becomes obsolete.
• Access This entity provides the services and
  functions that support Consumers in determining
  the existence, description, location and
  availability of information stored in the OAIS,
  and allowing Consumers to request and receive
  information products.

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OAIS Six Functional Entities
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OAIS Agents based Approach
Preservation Planning Agent
P R O D U C E R
C O N S U M E R
Data Management
queries
Access Agent
result sets
SIP Agent
Ingest Agent
SIP
orders
Archival Storage
DIP
DIP Agent
AIP Agent
Administration Agent
MANAGEMENT
SIP Submission Information Package
AIP Archival Information Package
DIP Dissemination Information Package
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Overview

• Digital Preservation
• OAIS
• Product Model
• Beyond Geometry NIST CPM/OAM
• Annotations for Archiving
• Standards and Semantic Interoperability
• Sustainment of Digital Information for Science
  and Engineering Requirements
• Conclusions

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Knowledge Representation Beyond Geometry
Artifact
Function
Form
Geometry
Behavior
Material
Relationships
Specifications Rationale Requirements
Assembly,...
Design Function dictates Form Manufacturing
Form dictates Function
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Core Product Model

• Objective base-level product model that is
• generic
• extensible
• independent of any one product development
  process
• capable of capturing full engineering context
• Key feature explicit representation of
• Function Form - Behavior
• (in contrast to STEP AP 209 that essentially
  represents only form )

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CPM Four categories of classes

• Classes that provide supporting information for
  the objects (abstract classes) for storing common
  information
• CoreProductModel, CommonCoreObject,
  CommonCoreRelationship
• CoreEntity, CoreProperty
• Classes of physical or conceptual objects
• Artifact, Feature, Port, Specification,
  Requirement
• Function, TransferFunction, Flow, Behavior
• From, Geometry, Material
• Classes that describe relationships among
  objects, they are derived from CommonCoreRelations
  hip
• Constraint, Usage, Trace, EntityAssociation
• Classes that are commonly used by other classes.
• Information, ProcessInformation, Rational

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CPM Three kinds of associations

• All object classes have their own separate,
  independent decomposition hierarchies by
  attributes such as subArtifacts/subArtifactOf for
  the Artifact class.
• there are associations between
• a Specification and the Artifact that results
  from it
• a Flow and its source and destination Artifacts
  and its input and output Functions
• an Artifact and its Features.
• Four aggregations are fundamental to the CPM
• Function, Form and Behavior aggregate into
  Artifact
• Function and Form aggregate into Feature
• Geometry and Material aggregate into Form
• Requirement aggregates into Specification.

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Core Product Model
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Open Assembly Model
Open Assembly Model
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Extensions to CPM

• Design-Analysis Integration Model - Objectives
• support tighter design-analysis integration than
  is possible today
• support broad range of discipline-specific
  functional analyses
• make analysis-driven design (function-to- form
  reasoning) more practical
• eventually support opportunistic analysis
• Key feature two models and two one-way
  associations
• Product Family Evolution Model -Objectives
• represent the evolution of product families and
  of the rationale for the changes
• Key features
• keeps track of product component series
  versions configuration relationship ties them
  together
• keeps track of what, how and why of all changes
  between versions/series

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Use of Annotations

• The research issues in annotations
• Management of annotations
• Structure and type of annotation
• Formal languages for annotation
• Ontology based annotations
• Human in the loop and Semi-automatic annotation
  generation
• How to add non-geometry information to CAD/PLM
  information?
• Annotations could be a good mechanism
• Feature based annotation
• Annotations as information handles for archiving

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Overview

• Introduction
• Digital Preservation
• OAIS
• Product Model
• Geometry
• Beyond Geometry NIST CPM/OAM
• Annotations for Archiving
• Standards and Semantic Interoperability
• Sustainment of Digital Information for Science
  and Engineering Requirements
• Conclusions

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Product Ontology A Work in Progress

• Currently evaluating CPM/OAM as possible ontology
  for product and for annotations
• Representation of CPM/OAM in
• OWL representation and Inferencing and Reasoning
• UML 2.0 and SysML
• Extracting information models from STEP AP
  203/214, AP 233, AP 239

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Ontology and Languages for Representation
XML, XML Schema
RDF, RDF Schema
OWL

• Tools for Ontology and Reasoning
• Protégé
• ontology editor and knowledge base framework
• Racer Pro
• a reasoner/inference server for the Semantic Web
• Semantic Web Rule Language Plug-in
• to write rules
• Jess Engine
• to make rules work
• Jess Bridge
• to connect OWL, SWRL and Jess Engine

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A Model of Communication between Agents
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Content, Language, Expressivity
Programming
Content Creators/Users
Formal
Information Modeling
Informal
Designers
Representational Needs
Language Features
Visual Modeling
Manufacturers
Language
Expressivity
Engineers
Logic Based
Suppliers
Query
Represented by
Marketing/Sales
Content
Mathematics
Maintenance
Stakeholders
Recyclers
Natural Language
Product Lifecycle Information
Geometry information
Design Information
Lifecycle information
Behavior
Requirements
2D/3D models
Features
Change Mgt
Processes
Surface Model
Material
Tests Maintenance
Function
Constraints/Relationships
Recycle Disposal
Topology
Standards Incomplete
Standards Evolving
Standards STEP
Designers
Manufacturers
Suppliers
Marketing/Sales
Engineers
Operations/ Maintenance
Recyclers
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Overview

• Introduction
• Digital Preservation
• OAIS
• Product Model
• Geometry
• Beyond Geometry NIST CPM/OAM
• Annotations for Archiving
• Canonical Representation
• Standards and Semantic Interoperability
• Sustainment of Digital Information for Science
  and Engineering Requirements
• Conclusions

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General requirements

• User Acceptance and Requirements
• Suitable retrieval-techniques
• Minimize workflow expenses for archiving
• Legal demand
• Ability to verify the conformity of a part with
  its documentation
• The system has to enable the user to assure the
  provisions of a law regarding data security and
  protection of data privacy over the life cycle of
  the archives.
• Possibility to audit the processes of archiving
  and retrieval
• Security

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Requirements Product Data Archiving

• Legal
• accident investigation, failure analysis
• customer delivery requirements
• Merger and acquisition
• Patent infringements
• Operational and support
• Historical data to provide lifecycle support
  (maintenance, spares, recycling and disposal)
• Product development management
• Effectivity tracing design rationale in cases
  of failure
• Design re-use (used in multiple products or
  models)
• Engineering change proposals/analysis
• Reverse engineering
• Comparison with new work, test beds, validation
  suites

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Requirements Product Data Archiving

• Content
• What is to be archived beyond geometry
  information? How is this information to be
  represented?
• Is STEP a starting point for content information?
• How to scale from part level to system level
  information?
• What are the Access points (for retrieval) for
  product data? Is there a role for generic
  features and contextual indexing?
• How to progress from Content representation to
  reasoning and inferencing?
• How to incorporate tolerance information? What is
  in AP 203 Edition 2 for tolerance semantics?
• Observations
• OAIS RM forms the necessary basis for world-class
  archive.
• OAIS RM is not sufficient. Need domain specific
  standards for
• understanding what information must be preserved
• understanding what constitutes proper and
  complete descriptive information (metadata
  standards)

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Requirements Product Data Archiving

• Representation
• What constitutes a canonical representation for
  archiving? Can we exploit CPM to define such a
  representation?
• Representation space - What is it and what does
  it look like?
• How to compress data and develop data reduction
  schemes?
• Archiving processes
• What is the initial requirement (draft) for
  Preservation Description Information (PDI) for
  product data?
• How to convert SIP to AIP and how to create DIP
  taking a holistic view of information package?
  This is essential to avoid fragmentation of
  creation, storage, and retrieval.

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Requirements Product Data Archiving

• Broader issues
• How to authenticate the archived information?
• Is there a larger community for digital archiving
  for product data?
• How to manage interoperability among different
  archival systems?
• What is the role of standards in information
  packages? How to develop standard schemas for
  submission information package, archival
  information package, dissemination information
  package, and Producer-Archive Interface
  Methodology Standard?
• Observations
• OAIS RM forms the necessary basis for world-class
  archive.
• OAIS RM is not sufficient. Need domain specific
  standards for
• understanding what information must be preserved
• understanding what constitutes proper and
  complete descriptive information (metadata
  standards)

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Conclusions

• Archiving of engineering informatics is very
  critical in this information age in order to
  fulfill legal, business, and product quality and 
  liability obligations.
• Engineering informatics is the discipline of
  creating, codifying (structure and behavior that
  is syntax and semantics), exchanging
  (interactions and sharing), processing (decision
  making), storing and retrieving (archive and
  access) the digital objects that characterize the
  cross-disciplinary domains of engineering
  discourse.
• The main difficulty lies in maintaining digital
  information intact, while providing access to
  this information in a usage context that is
  subjected to change.
• Kuny coined the term preservation nexus to mean
  the relationship between hardware, software and
  humanware and can be maintained, then digital
  object can be preserved forever.
• It is the contents that must be preserved not
  conserved. Unlike conservation practices where an
  item can often be treated, stored and essentially
  forgotten for some period of time, digital
  objects will require frequent refreshing and
  recopying to new storage media. Keeping the
  original digital artifact is not important.

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LTKR NIST WORKSHOP 2007

• Long Term Sustainment of Digital Information for
  Science and Engineering Putting the Pieces
  TogetherTuesday- Wednesday, April 24-25NIST,
  Gaithersburg, MD 20899, USA
• http//www.mel.nist.gov/div826/msid/sima/interopw
  eek/meetings.htm
• Abstract Researchers at universities, in
  industry, and in government are developing tools
  and standards for archiving and preserving the
  ever-increasing volume of digital information
  humankind produces. Meanwhile, records managers
  are grappling with maintaining their
  organizations' data assets and responding to
  requests for electronic information from
  regulators, legal investigations, and other
  sources. Scientists and engineers, in addition to
  the aforementioned issues, want the digital
  models and systems they build today to be
  extensible and reusable for subsequent
  generations of technologists. Our discussion, a
  sequel to last year's highly successful Long Term
  Knowledge Retention workshop, will focus on
  policies of digital preservation and applying
  promising technologies to solve preservation
  problems in product design, engineering, and
  manufacturing in particular, with possible
  extensions to include chemistry, biology, and
  other disciplines where critical information must
  be "future-proofed."

Please visit http//digitalpreservation.wikispaces
.com/
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Summary
Language Theory
Representation Theory
Domain Theory