A Semiotic Approach to Conceptual Modelling

Antonio L. Furtado

Departamento de Informática

Pontifícia Universidade Católica do Rio de Janeiro

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

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

Colleagues

Marco Casanova

Simone Barbosa

Karin Breitman

Bruno Feijó

Angelo Ciarlini

Cesar Pozzer

Main aspects

• Three-schemata specifications

• The plan-recognition / plan-generation paradigm

• Application domains and narrative genres

• Semiotic completeness

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

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

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)

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

The Web era: all of us as navigators

Tim Berners-Lee

Recall x Precision

or: The Dangers of Navigation

Recall x Precision

or: The Dangers of Navigation

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)

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

Relational completeness- enough to translate first-order logic expressions -

relational algebra operations

� product

� join

� projection

� union

� difference

� intersection

� selection

� division

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

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

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)

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

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].

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”

An aside: theorem-proving methods

by inference connectivity syntagmatic

by analogy similarity paradigmatic

by case analysis hierarchy meronymic

by contradiction negation antithetic

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

Synecdoche

Metonymy

Metaphor

Enigma

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

Syntagmatic relations

abduct rescue

elope capture

Paradigmatic relations

abduct rescue

elope capture

Antithetic relations

abduct rescue

elope capture

Meronymic relations

abduct

capture

ride defeat seize carry

Meronymic relations

rescue

elope

ride defeat entreat carry

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

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

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)