a semiotic approach to conceptual modellingfurtado/semiotic_approach.pdf · dynamic schema events...
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A Semiotic Approach to Conceptual Modelling
Antonio L. Furtado
Departamento de Informática
Pontifícia Universidade Católica do Rio de Janeiro
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People make history
Charles W. Bachman“the programmer as navigator”IDS, CODASYL, pointers, machines, files
Edgar F. Codd“the casual user”logic, algebra, tables as abstract data types
Peter P. Chen“modeling the things in the real world”diagrams, pictograms, concepts
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Our project at PUC-Rio
� from databases to information systems
� logic programming formalism
� prototype tools
� Theory, Linked Data: Marco A. Casanova
� Big Data: Karin K. Breitman
� Human-Computer Interaction: Simone D. J. Barbosa
� Digital Entertainment: Bruno Feijó, Angelo E. M. Ciarlini, Cesar Pozzer
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Colleagues
Marco Casanova
Simone Barbosa
Karin Breitman
Bruno Feijó
Angelo Ciarlini
Cesar Pozzer
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Main aspects
• Three-schemata specifications
• The plan-recognition / plan-generation paradigm
• Application domains and narrative genres
• Semiotic completeness
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Three-schemata specifications
� static schemafacts – entities existing in a given state of the world and their properties (attributes, relationships)
� dynamic schemaevents – state transformations caused by the execution of operations defined on their pre-/post-conditions (the STRIPS method)
� behavioural schemaagents – who execute operations in order to reach states wherein their goals are satisfied (agent profiles, goal-inference rules)
Basis: the Entity-Relationship model for facts and everything else –pre- / post-conditions, and goals are expressed in terms of facts
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Plan-recognition / plan-generation paradigm
� decision-making at each state:how agents evaluate current risks or opportunities – drives (choice of goals), attitudes (choice of plans), emotions (commitment or not)
� multi-agent environments:positive and negative goal and plan interferences, competition, cooperation and negotiation (cf. R. Willensky)
� plan generation algorithm:pre-conditions of operation O1 fulfilled by post-conditions of operation O2 –recursive backward-chaining process to generate sequences of operations to achieve the agents’ goals
� simulation:through the use of the planner, the three-schemata specifications become executable
� the reuse alternative:plan recognition algorithm to match observed actions against a library of plan patterns – recognition and adaptation as a form of case-based reasoning
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Application domains and narrative genres
� Business information systems – application domains with a predefined repertoire of operations (e.g. banking)
– The IDB prototype – 1. Prolog, 2. Prolog + Oracle via ODBC, 3. running Oracle environment (operations compiled into stored procedures)
� Digital entertainment – narrative genres limited by conventions and a finite number of typical agents and events (Vladimir Propp –characterization of folktales via 7 dramatis personae and 31 functions)
– The Logtell prototypes – operational specification of genres –
interactively generated plans ⇒ narrative plots
dramatization of the generated plots: via natural language, animation, video-based composition, etc.
the reuse alternative: plan-recognition working on types and motifs (cf. Aarne-Thompson’s Index)
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Revisiting the ANSI/SPARC
proposal• conceptual modelling also at
the external (users’) level
• two reminders from Semiotics:
- communication: Jakobson’s
message encoding/decoding
- representation: Peirce’s
interpretant
• from semantic to pragmatic: cooperative query-response interfaces with access to user profiles and plan-recognition
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The Web era: all of us as navigators
Tim Berners-Lee
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Recall x Precision
or: The Dangers of Navigation
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Recall x Precision
or: The Dangers of Navigation
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Our quest for “completeness”
� Opportunities and risks at the Web era: recall x precision
� Focusing on one starting point (e.g. an entity instance), in what direction(s) should we usefully go to find more
about it?
� Charting the information space to obtain some navigation guidelines
� Completeness – are we missing something?
A word of caution: completeness is relative – world models are by
definition simplifications – ours give an operational definition, aiming
to mirror some real world application domain (or narrative genre)
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Computational completeness- power equivalent to a Turing machine -
LISP – basic functions
� constructor: cons
� projections: car, cdr
� predicates: eq, atom
LISP – data structure
� list – of atoms and/or lists
to represent both sequences and sets
and also: graphs, hypergraphs ...
Böhm-Jacopini theorem –
3 control structures are enough:
• sequence
• selection
• iteration
control in LISP
� function composition
� cond
� recursion
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Relational completeness- enough to translate first-order logic expressions -
relational algebra operations
� product
� join
� projection
� union
� difference
� intersection
� selection
� division
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Relational completeness- enough to translate first-order logic expressions -
relational algebra operations
� product
� join
� projection
� union
� difference
� intersection
� selection
� division
the five basic operations
� product
� projection
� union
� selection
� difference
join, intersection, division can be
defined in terms of the basic
operations
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Relational completeness - intuitively: enough for handling tables -
colums = sequence of domains (horizontal axis)
. product
. projection
rows = set of tuples (vertical axis)
. union
. selection
what else? – removal of a given set of tuples (topological bounds)(serving to achieve the effects of intersection and division, and to perform deletion)
. difference
_________________________________________________________
Extension: N2F2 tables:
cells = structured values (depth axis)
. nest
. unnest
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Peter Chen: logic level (values with no semantics)
⇒ conceptual level
columns ⇒ entity or relationship class attributes horizontal axis
rows ⇒ instances of the same class vertical axis
structured values ⇒ semantic hierarchies depth axis
removal of tuples ⇒ consistent world state maintenance topological bounds
(integrity constraints, business rules, conventions)
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The information space – semiotic relations
horizontal axis connectivity – syntagmatic relations
vertical axis similarity – paradigmatic relations
depth axis hierarchy – meronymic relations
topological bounds negation – antithetic relations
� Saussure - Cours de Linguistique Générale (posthumous publication in 1916)
� Winston, Chaffin and Herrmann – A Taxonomy of Part-Whole Relations
� Horn – A Natural History of Negation
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Connectivity: RDF diagrams
"…RDF can be viewed as a member of the Entity-Relationship model family"[Chen, P.P. "Entity-Relationship Modeling: Historical Events, Future Trends, and Lessons Learned". Software
pioneers. Springer, 2002].
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On the relevance of the other relations
as navigation guidelines
� similarity – comparison with alternatives, classification criteria, typical instances (Lakoff), similarity measures, clustering, inter-domain analogy, adaptation and reuse
� hierarchy – zooming in and out, detailed description versus summarization, recognition (gestalt perception), modular design
� negation – disambiguation, what is not wanted, counter examples, near miss (Winston),opposition, contrary values: Boolean or in a multi-graded scale, conflict, blend (Turner), different opinions, inconsistency, integrity violation, “things that should not be but nevertheless are”
⇒⇒⇒⇒ plentiful recall, with more precision: “if” and “only if”
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An aside: theorem-proving methods
by inference connectivity syntagmatic
by analogy similarity paradigmatic
by case analysis hierarchy meronymic
by contradiction negation antithetic
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Semiotic completeness - the four master tropes -
relation meaning operator trope
syntagmatic connectivity and metonymy
paradigmatic similarity or metaphor
meronymic hierarchy part-of synecdoche
antithetic negation not irony
� Quintilian, Ramus, Vico, Kenneth Burke, Hayden White, ...
� Jonathan Culler: “... a system, indeed the system, by which the mind
comes to grasp the world conceptually in language”
� Jean François Champollion – Grammaire égyptienne, 1836
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Synecdoche
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Metonymy
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Metaphor
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Enigma
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Events and the four relations(plots: post-conditions → pre-conditions)
relation meaning trope
syntagmatic coherence metonymy
paradigmatic alternatives metaphor
meronymic detailed action synecdoche
antithetic disruption irony
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Syntagmatic relations
abduct rescue
elope capture
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Paradigmatic relations
abduct rescue
elope capture
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Antithetic relations
abduct rescue
elope capture
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Meronymic relations
abduct
capture
ride defeat seize carry
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Meronymic relations
rescue
elope
ride defeat entreat carry
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Agents and the four relations(goal & plan positive and negative interferences)
relation meaning trope
syntagmatic collaborating, helper metonymy
paradigmatic parallel, peer metaphor
meronymic collective, fellowship synecdoche
antithetic competing, villain irony
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Next step: semiotic diachronic completeness
Facts + (events, agents, plans, plots) ⇒⇒⇒⇒ temporal dimension
� Provide a narrative viewpoint – plots as entity property
� Revisit the past – log with time-stamped records of events
� Add near future forecast – scheduled events also in the log
� Watch for evil attempts – recognition from observed actions
� Find what is achievable, and how to get there – plan trials to reach possible (and supposedly impossible / illegal!!!) goals
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Concluding remarks
� Conceptual modelling in the large and in the small:
- from the closed-world of databases to the open-world of the Web- the mini-world of each of us, under a flurry of portable devices
� Goals and plans: towards pragmatic user-centered
conceptual modelling
� Contribution of Semiotics
� Contribution of Human-Computer Interaction (HCI)