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“Funes the Memorious”. Issues in long term knowledge retention in engineering Chris Rusbridge. Contents. DCC Last year? Funes, and the cobbler Knowledge, engineering, information, longevity Next… . Mission.

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funes the memorious

“Funes the Memorious”

Issues in long term knowledge retention in engineering

Chris Rusbridge

contents
Contents
  • DCC
  • Last year?
  • Funes, and the cobbler
  • Knowledge, engineering, information, longevity
  • Next…
mission
Mission

“The over-riding purpose of the DCC is to support and promote continuing improvement in the quality of data curation, and of associated digital preservation”

goals
Goals
  • Strategic leadership in digital curation
  • Influence and inform policy
  • Provide advocacy and expert advice
  • Provide resources and tools
  • Raise levels of awareness and expertise
  • Strengthen the community
  • Continue links with leading edge research
status of dcc
Status of DCC
  • Phase 2 funded 3/2007 to 2/2010
  • Associated project DCC SCARP to 4/2009
    • Includes immersive case study approach including engineering/architecture at Bath
    • Just starting!
last year at ltkr
Last year at LTKR…
  • Established importance of problem
  • Critical standards exist (STEP, OAIS)… helpful but not sufficient?
  • Identified some issues & limitations
  • Wanted engineering information in (format) registries
  • Identified some archiving problems
  • Listed some requirements
funes the memorious7
“Funes the Memorious”
  • Story by Jorge Luis Borges [1]
    • Funes remembers everything
    • 70,000 memories a day… how to classify?
    • Puzzled why “the dog at 3:14 (seen from the side) should have the same name as the dog at 3:15 (seen from the front)”
    • “I suspect, however, that he was not very capable of thought. To think is to forget differences, generalize, make abstractions. In the teeming world of Funes, there were only details, almost immediate in their presence.”
the cobbler
The cobbler?

People

Organisation

Processes

Knowledge

All in one person!

Un-scalable, and mortal

abstraction and domain areas
Abstraction and domain areas

Peak, Lubell,

Srinivasan &

Waterbury,

JCISE 2004 [2]

scalability bring on the m names
Scalability: bring on the “M” names?
  • ILM?
    • Digital curation? No, 3rd party storage management
  • KM?
    • Integrate processes and agents through shared knowledge?
      • With added requirements for long-term?
    • “death/autism of KM?”
    • Cultural change barriers: knowledge sharing still…
      • Person to person
      • Just in time (if you’re lucky)
      • Problem-oriented
  • PLM?
    • Proprietary 3rd party? “Trust me…”
    • Standards-based…
what s going on
What’s going on?

Complianceperiod

archival

Economic period

Product database

Curation

begins

here!

Soft transition

Retain

After life

Maintain

during life

Design

Build

Product information repository

Completeness, accuracy,

versions, process, efficiency

+ provenance,

longevity

Continuing interpretability

archive repository
Archive/repository
  • Preserves “information” (OAIS)
  • For a Designated Community
  • Receives Submission Information Packages (SIPs)
    • Negotiated
    • Data in files
    • Metadata
    • Context & provenance, etc
designated community
Designated Community
  • An identified group of potential Consumers who should be able to “understand” a particular set of information
  • Here: future engineers (and accident investigators!)
  • Will 22nd century engineering concept set & vocabulary be superset of today’s?
    • No! Gradual concept drift…
    • But likely discoverable by determined investigator.
slippery words
Slippery words
  • “Polysemantic concepts such as information can be fruitfully analysed only in relation to well-specified contexts of application” Floridi [3]
    • Understand
    • Knowledge
      • Knowing that, knowing how
    • Information
      • Factual, instructional, process
    • Data
      • “difference that makes a difference”
    • Files
files databases packets
Files, databases, packets
  • No naked data
    • In any independent existence the data are always packaged in some way
    • Encoded serialisation of data representing information linked to an information model and/or conceptual schema?
    • Packaging adds extraneous “information”
    • Confuses the archivist! (Most digital preservation discussions relate to preserving “files” or at best “digital objects”)
information
Information
  • “Standard definition of information” Floridi
    • Comprises data that
    • … is well-formed
    • … and meaningful
  • OAIS definition
    • “Any type of knowledge that can be exchanged. In an exchange, it is represented by data.”
representation information
Representation information
  • Heavy load!
  • “Representation Information accompanying a digital object, or sequence of bits, is used to provide additional meaning. It typically maps the bits into commonly recognized data types such as character, integer, and real and into groups of these data types. It associates these with higher-level meanings that can have complex inter-relationships that are also described.”
interpreted using
Interpreted using…
  • Today: software tools
    • (although OAIS implies RepInfo often a text description…)
  • Tomorrow:
    • Same software running on a VM (emulation)?
    • Different software specially built using the RepInfo?
    • Maybe tool to “interpret” RepInfo eg in EAST?
    • Maybe new software implementing legacy forms?
    • Maybe transform old data for new software (migration)?
  • Outcomes enhanced if information in widely-used standards-based form!
oais a reference model
OAIS a Reference Model…
  • Not a design
  • Not an architecture
  • There need be no element labeled RepInfo
  • … but the CONCEPT of RepInfo should exist!
  • Ie explicit relationship between data/files and information according to a recorded information model
engineering repinfo
Engineering RepInfo?
  • Do you have an underlying engineering information model?
  • What would representation information be for engineering information (say encoded in STEP)?
    • Definitions of appropriate STEP elements (eg the standard)
    • Additional refinements added by the tools used
    • +???
  • What about what cannot be encoded in STEP?
  • Or… what information would an engineer need who had never used STEP or your analysis tools?
final questions
Final questions
  • What else makes your encoded product information fragile?
  • What can you do to make it more robust?
  • What further tools, techniques, training and infrastructures do you need to do a better job?
references
References
  • [1] Borges, Jorge Luis. (1962) Labyrinths, Selected Stories & Other Writings. Penguin Books
  • [2] Peak, R., Lubell, J., Srinivasan, V., Waterbury, S. (2004). STEP, XML, and UML: Complementary Technologies.Journal of Computing and Information Science in Engineering4 (4), 379-90
  • [3] Floridi, L. (2005). Is Semantic Information Meaningful Data? Philosophy and Phenomenological Research, Vol. LXX, No. 2