issues in long-term knowledge retention in engineering

a centre of expertise in data curation and preservation

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“Funes the Memorious”

Issues in long term knowledge retention in engineering

Chris Rusbridge


Atlantic Workshop on LKTR 2

Contents• DCC• Last year?• Funes, and the cobbler• Knowledge, engineering, information,

longevity• Next…



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• 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• 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…• 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 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?

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

•Organisation

•People

•Knowledge •Processes•All in one person!

•Un-scalable, and mortal



Abstraction and domain

areas

•Peak, Lubell,•Srinivasan &•Waterbury, •JCISE 2004 [2]



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?

•Design •Build•Maintain •during life

•Retain •After life

•Economic period

•Product database

•Compliance period

•archival

•Product information repository

•Continuing interpretability

•Completeness, accuracy, Completeness, accuracy, •versions, process, efficiencyversions, process, efficiency

•+ provenance, •longevity



Archive/repository• Preserves “information” (OAIS)• For a Designated Community• Receives Submission Information Packages

(SIPs)• Negotiated• Data in files• Metadata • Context & provenance, etc



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 • “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• 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”)



ISO 19101 model

•ISO 19101



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• 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…• 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…• 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?• 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• 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• [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 Engineering 4 (4), 379-90

• [3] Floridi, L. (2005). Is Semantic Information Meaningful Data? Philosophy and Phenomenological Research, Vol. LXX, No. 2

issues in long-term knowledge retention in engineering

Technology

quality of data curation

centre of expertise

naked data

requirements atlantic

process data difference

digital curation influence

mortalatlantic workshop

preservation files