methodology ontology
who identifies who?
how?
how to structure input of research?
D2.1 Nabeth 2004
 ontology in computer sciences:
‘explicit specification of a
conceptualisation’
 ontology (what is)
 epistemology (what can we know)
 methodology (how can we produce
knowledge)
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2nd WP2 Workshop @ INSEAD
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 ontology in computer science is an
instrument to clarify and share the
use of terms (pragmatic approach)
 better not get into a discussion on
‘real meaning’ or ‘true identity’
 better see the difference between 1st
and 3rd person perspective or self
and same
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identity concept
modeling
(mix of 1st/3rd p. perspective)
 I, me and self (Mead)
 true identity, assigned identity, abstracted
identity (Durand)
 identities and territories (contexts,
Nabeth?)
 relational and dynamic concept of identity
as nexus of different roles, evershifting
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2nd WP2 Workshop @ INSEAD
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identification concept
3rd person perspective
 risks, mechanisms, protection
against, management
importance 1st person perspective
 (organisations, national state)
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2nd WP2 Workshop @ INSEAD
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Inventory of terms and
some categorisation
 definitions, illustrations and
references, relations between terms
 beginnings of the construction of a
semantic network:
 lexical (syntactic, definitions that
relate a term to other terms)
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2nd WP2 Workshop @ INSEAD
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Canhoto Backhouse
 categorization theory and semiotics
case-study:
 EU-directive to combat money
laundering
 objective the same in all MS’s
 wide variation in submission levels
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2nd WP2 Workshop @ INSEAD
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Suspicious Transaction
Report
 STR to Financial Intelligence Unit
 trade off between false negatives and
false positives, reporting institution is
stimulated to over-report, law
enforcement agents should minimize
false positives
 over-reporting creates backlog
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2nd WP2 Workshop @ INSEAD
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 how to reduce false negatives and
false positives:
 how to expand knowledge to refine
the identification of suspicious
financial transactions
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2nd WP2 Workshop @ INSEAD
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 role of automatic monitoring
 role of intuition (practical wisdom,
experience, refined judgement)
 traditional methodology too much
oriented towards technological design
and legal regulation, plea for
incorporation of semiotics
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2nd WP2 Workshop @ INSEAD
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semiotics I
 physical level
records of actions and users
 empirical level
aggregation of data at client level
 syntactical level
automatic monitoring systems
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2nd WP2 Workshop @ INSEAD
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semiotics II
 semantic level
legal landscape, differentiation MS’s
 pragmatic level
cognitive prototype developed by
professionals with significant
experience
 social level
formal/informal norms, cultural
context
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2nd WP2 Workshop @ INSEAD
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profiling/categorisation
 how to generate profiles that yield few false
negatives and few false positives (balance
between the two will depend per context)
 this is a matter of both privacy and security
 but privacy/security is also about not being
profiled
(anonymity, pseudonymity,
unlinkability)
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refinement of
identification
 syntactical level:
develop intelligent automatic monitoring
systems
 pragmatic level:
learning theory: interpretation of
automatically generated profiles, how to
generate/recognise new patterns
 social level:
diversity of socio-cultural norms
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2nd WP2 Workshop @ INSEAD
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semiotics
 recognition of intersubjective perspective in
objectification:
 beyond reification of ontologies
 beyond reductive interpretations of identity
 challenge: how to further refine profiling
technologies while protecting indeterminate
identity (freedom to (re)define yourself)
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