HOW TO CREATE AND
MAINTAIN CONCEPROCITY
CAPRICE AND CAPRILOPE
MODELS
Mark Gregory
Based on the earlier work by LICEF
Version 2.1 18/10/2013
Left and Right Brain?
The concept of right brain and left brain thinking
developed from late 1960s research of psychobiologist Roger W Sperry, who discovered that
human brain has two very different ways of
thinking:
 Right brain is visual and processes information in an
intuitive and simultaneous way, looking first at the whole
picture then the details
 Left brain is verbal and processes information in an
analytical and sequential way, looking first at the pieces
then putting them together to get the whole
Illustrating Concepts
Concepts may be held both visually and
linguistically
 Mind Maps –Tony Buzan (Buzan & Buzan 1996)
 Concept maps – Joseph Novak and collaborators (Novak & Cañas
2008) following David Ausubel (Ausubel 1963) and (Ausubel 2000)
 Concept maps with typed concepts and relationships: LICEF
(Paquette 2010; Basque 2013)
 Concept <-> Process maps: Conceprocity: Mark Gregory
(www.markrogergregory.net)
Using both the visual and the linguistic (written
and spoken language) stimulates better
understanding of a situation and – later – better
learning
Here is a Wading bird
Tony Buzan’s Mind Maps are
highly visual. However, their
insistence on a single centre is
unnecessarily restrictive and
their strict hierarchy prevents
conceptual cross-linking
between branches of the tree
Conceprocity: An Introduction
Conceprocity – concept <-> process
reciprocity – is a visual and textual language
and toolset intended for capturing, expressing,
communicating and co-creating models of topic
areas of domain knowledge by domain experts
or learners
You decide the vocabulary
Very simple grammar rules
CAPRICE
Within Conceprocity there is a beginners’ profile “Simple
concept mapping for beginners”, in which the only available
relationship between concepts is association
 This simple concept mapping for beginners usage profile is
called CAPRICE: Concepts Actors Procedures
Relationships Images Conditions Events
 Strong emphasis on the use of sketches, icons and images
to stimulate right brain involvement
There are other usage profiles which are not
mentioned further in the first part of this presentation
 They make use of a further notion – principles; of typed
relationships; and they distinguish instances from classes
An example Conceprocity model and how it has been
created - 1
Start with a simple English
sentence: “The cat sat on the mat”
 Give a specific instance: “The cat called
Kat sat on the mat in my lounge”
 A concrete Conceprocity map is as right
Identify concepts, any static
relationships and any activities
Create a specific and a more
general model using the metaconcepts (Conceprocity notions) of
concept, procedure and relationship
 Consider concrete and abstract
representations
An example Conceprocity model and how it has
been created - 2
Observe, maybe discuss and then refine the
resulting map
 Here we choose to remove the concrete and retain
the abstract elements in a conceptual model of the
general situation of creatures acting in a
geographical context
The model that results depends upon the
viewpoint and the purpose of the modeller
 A cat specialist (and a cat lover!) will take a different
view from an expert in cognitive science applied to
animals
 But the process of dialogue and of mutual
understanding can be aided by visual concept
mapping and by dialogue around the models
Conceprocity CAPRICE: Fundamentals
•
Paquette’s G-MOT and Conceprocity distinguish between types (classes) of objects:
Concepts - things, ideas, etc.; these are usable and (sometimes)
decidable classes of knowledge or data
Actors - people, organisations, external systems
Procedures - the means of enacting knowledge in the form of specific
activities, repeatable actions and processes – the latter being
templates for repeated actions
Relationships: concepts are related by relationships or relationship
instances (links). In CAPRICE the only available type of relationship is an
association; this should be given a name
Images: images illustrate concepts or any other notion.
Conditions: logical operators XOR, OR or AND.
Events: EITHER occurrences in time that change the state of a class of
objects OR named states of class of objects
Principles: constraints, rules or complex conditions. Not used in
CAPRICE.
CAPRICE fundamentals
Conceprocity CAPRICE: Representation
Abstract
Abstract knowledge
knowledge
WHAT?
Concepts
Conceptual K
HOW?
Procedures
Procedural K
Actors
WHO?
K wielders
Representing CAPRICE relationships
Different kinds of arrow are used:
Symbol
Meaning
Association. This needs a text label,
such as is-a, is-composed-of, etc.
Flow of control or of data
Is instantiated as
Regulates. An actor or principle
controls or governs a concept or
procedure
Commentary concerning the
diagram
Images: Conceprocity for the Right Brain
Conceprocity makes it easy to include visual
elements. Beyond Conceprocity’s own
symbols, we can include images and icons.
You can either locate these for yourself, or
you can use Google Images search, or they
may be sketches made using apps such as
ArtRage, or they may be sketches (e.g.
fragments of rich pictures) drawn freehand on
paper and then photographed and uploaded.
Sketches – less formal diagrams – frequently
have a role, particularly in the early
development or the informal presentation of a
model (especially during whiteboard
sessions). You may even include a complete
rich picture (Checkland 1981; Checkland &
Tsouvalis 1997) or elements of a rich picture.
14
Modelling businesses using rich pictures
• Use few
words
• Use lots
of
pictures
15
Making rich pictures





Rich pictures (situation summaries) are used to depict
complicated situations
Encapsulate the real situation through a no-holds-barred,
cartoon representation of layout, connections, relationships,
influences, cause-and-effect etc. - objective notions
Should try to depict subjective elements such as character and
characteristics, points of view and prejudices, spirit and human
nature
If possible, ask the actors themselves rather than focusing on
your own interpretation of the situation
Allow competing pictures; don’t “reconcile”; perhaps
“accommodate”?
Begin to build a model
• What is the question or topic area that you are addressing?
• What are the top five or so concepts?
• Are there any direct relationships (associations) between these
concepts?
• E.g.: is-a-kind-of, consists-of…
• Otherwise: what processes link or transform the concepts?
• Make lists of likely concepts and procedures
• Perhaps later keep these lists in a formal Conceprocity dictionary?
• Sketch out an initial CAPRICE model – on a large sheet of
paper or on a whiteboard – preserve this using a smartphone
picture
• Include rich picture elements on the CAPRICE map
How to get started with a CAPRICE model
• Identify and make lists of concepts and their “obvious” structural
links / associations
• Example: beech is-a-kind-of tree
• Take care to distinguish concepts as classes (often
distinguished by an indefinite article in natural language) and
instances of concepts (often distinguished by the definite article
or evidently proper names)
• In English and in French, but not in German, the distinction is often
made clear by the use of Capitals (instances) and lower-case (concepts)
• The difference is often that between abstract concepts and concrete
facts
• Identify processes which link concepts where one needs to be
changed or transformed in some way which goes beyond a
structural association
• Cow gives-birth-to calf
• (Better models are possible…)
Modelling a marketing campaign
• Your task: to create a simple CAPRICE model of
the general principles of an e-marketing
campaign
• Over to you:
• Twenty minutes as separate teams
• Present, compare, contrast, reject, synthesise for five
minutes
• Tell / show us your tentative conclusions on the
flipboard
Full-fat Conceprocity: CAPRILOPE
CAPRILOPE: Concepts Actors Procedures Relationships
Images Logical Operators Principles Events
More emphasis on principles
Fully typed relationships
CAPRILOPE fundamentals
The correct way to install Google Drive
and Lucidchart
You must install and use the Google Chrome browser and
use it when setting up or changing Google Drive and
Lucidchart accounts
 Subsequently it’s OK to use Firefox etc.
You must ensure that BOTH your Google Drive email
account AND your Lucidchart account are set to be your
ESC Rennes username – that is, something like
pierre.martin@esc-rennes.fr
Start from Google Drive
First: connect to and learn to use Google Drive
To do this, use the address
https://drive.google.com/a/esc-rennes.fr/#my-drive
Although it is not essential to do so, you are advised to
Install Google Drive for PC, Mac or Android as
appropriate
This permits you to move files between your computer
and Google Drive very easily using your file manager (e.g.
Windows Explorer, Mac Finder)
Go on to install Lucidchart
To install Lucidchart, use Google Chrome. Disconnect
from any other Google Account. Connect to your ESC
Rennes address.
From your Drive homepage Create > More > Get more
apps and search 'Lucidchart’
Once the app is installed, you will see Lucidchart listed
under Create → More in Google Drive
You can use this feature to create new Lucidchart
documents, in the same way that you start new Google
documents or spreadsheets – BUT use our templates
For other questions, please see the Lucidchart Google
Drive documentation
Check that you’ve set things up correctly
When connected to Lucidchart, click on Account and
check that the Username and the Email are BOTH set to
be your ESC Rennes user name
Problems? See Mark Gregory, room 338
Most common problem: you have downloaded and
installed Lucidchart while connected to another Google
account, not your ESC Rennes one!
 PLEASE ONLY install Lucidchart while connected to your ESC
Rennes free account
 If you have NOT done this, see Mark in room 338
Sharing files with your teacher
We advise you to set up a folder for files that you want to
share with your module student colleagues and with your
module teacher
Please make sure that the name that you choose
contains the name of your team – e.g. team 7 in group 02
is team G1T07 on module IS505E PEC; therefore call
your folder something like IS505E PEC team G2T07
NEVER FORGET
Work with your ESC Rennes username and password
when you want to create documents that teachers can
access!
 You have a free educational account with Lucidchart
 But to use it, you MUST ALWAYS connect using your ESC Rennes
username
Use Google Chrome to install Lucidchart
 Lucidchart has to be installed when you are using the Google
Chrome browser, and generally works best with that browser
How to synchronise Drive and Lucidchart
If you want to sync your files between your Lucidchart
account and Drive you can select, from the Lucidchart
editor, File > Google Drive Preferences, and choose what
you would like
You can learn more about integration by visiting the
tutorial section on Google Drive
Syncing Lucidchart files with Google Drive
Google Drive Preferences are accessible
through the editor as well as your Account page
 Allows you to modify the way you sync and secure your
files to your Drive account and local backup
In Editor: File > Google Drive Preferences
 Synchronization: Choose to automatically sync
documents you create in Lucidchart to your Drive
account
 Automatic Backup: Lucidchart with Google Drive allows
you to have all of your Lucidchart documents backed up
daily or weekly to your Google Drive Account
Syncing - 2
1. Make sure you're logged into the Google account you'd
like to link with Lucidchart in this browser
2. In Lucidchart, Go to
Account / Documents / Google
Drive to link Lucidchart to that account.
1.
To get to Account, you can click on the Lucidchart logo top left of
the screen
Getting to know Lucidchart
How Lucidchart works
 Lucidchart is an online diagramming software-as-aservice. It is a chargeable service but is made available
free to educational institutions, including ESC Rennes
School of Business.
Getting started with Lucidchart
 Follow the tutorial which you will find at
https://www.lucidchart.com/pages/tutorials
 Start with “Create a new document” and carry on until
you get bored. Then come back to this document and
keep reading and working from it!
YOU MUST USE these Lucidchart templates
• PLEASE use the Lucidchart templates linked to from the latest version
of those slides (and from the table which follows). On the page which
then opens in your browser, click on Use as template
Item
Template
Use case diagram UCD
https://www.lucidchart.com/community/examples/view/49042264-50bd807f-8bbd-5a850a442276
Event process chain EPC
https://www.lucidchart.com/community/examples/view/4572ba14-5288fba4-bf49-10050a008fdc
Conceprocity CAPRICE
and CAPRILOPE
https://www.lucidchart.com/community/examples/view/42d877d0-52b93213-9de6-29ca0a009f85
Conceprocity CAPRICE Notions
Processes
Concepts
E.g. see The Hobbit
Instance of object or idea E.g. the ball bowled One-off
actions
Relationshipsby bowler Smith
Events and logical connectors
Activities:
E.g. go to the cinema
Association which captured
Book is the
associated
with knowledge
Eventwicket of batsmanE.g. repeated
book returned toperiodically
library
Instantiation
A123 Jemimah is a (specific) student
Jones at Lords on
similar
actionswith a logical
Compound event
Event
associated
15/06/2015
connector
Processes:
E.g. plan and
Concept: named class of E.g. red, hard,
activityOR: exactlyundertake
personal
Logical connector:
Exclusive
one of two
or
similar things or ideas,
bounces in
XOR
moretemplates
outcomes may cultural
occur inimprovement
a given
sometimes characterised (somewhat)
and diversion each
instance
by facts and
controllable fashion,
week
Logical
connector:
Inclusive
OR:
one
or
more possible
measurements
used in cricket – a
outcomes may occur – represent
associated with specificOR cricket ball
zeroActors:
with nullIntelligent
process Agents
instances of things; these
are named properties of
Knowledge-wielding
E.g.occur
students,
Logical connector:
All the
possible outcomes will
the concept
persons
teachers,
AND
in parallel
andininroles
no defined
administrators
sequence
Super-concepts and sub- E.g. ball and cricket
concepts
ball
Knowledge-wielding E.g. aircraft
intelligent agents
flight control
systems
Conceprocity Usage Profiles - 1
A Usage Profile is a named usage of Conceprocity by a
defined group of model writers and readers
These various usage profiles require few or no extensions
to the Conceprocity basic notation which is richly expressive
It is possible and desirable to start with a beginners’
profile “Simple concept mapping for beginners”, in
which the only available relationship is association and no
use is made of principles, and only then to move on to typed
relationships and principles
 This is the simple concept mapping for beginners usage
profile CAPRICE: Concepts Actors Procedures
Relationships Images Conditions Events
 Strong emphasis on the use of sketches, icons and
images
Conceprocity Usage Profiles - 2
 Simple concept mapping for beginners: CAPRICE
• Concepts Actors Procedures Relationships Images
Conditions Events
 Knowledge mapping: CAPRILOPE
• Very general with the full range of Conceprocity objects, Concept / Actor /
Procedure / Relationship / Image / Logical Operator / Principle / Event
• Typical uses include: self-observation, research design, representing
knowledge as-is and as-ought, demonstrating understanding,
documenting a body of knowledge and design of teaching, learning and
evaluation
 Event-driven process chains
The Conceprocity CAPRICE Method – 1
Define a focus question to which your model will be a
(partial) answer, or at least delimit a clear topic area
Create a Google Drive directory (folder) to contain the
files that will constitute the model
Begin to build a Conceprocity dictionary (in Microsoft
Excel or in Microsoft Access) and glossary containing
initial lists of:
 Concepts (and specific instances: facts)
 Actors (and specific instances: e.g. named persons)
 Processes
The Conceprocity CAPRILOPE Method – 2
Create some examples for each notion
Think about the relationships between the concepts,
actors and processes
 Can you identify and name relationships – associations - between
concepts?
 Or are concepts related only by processes?
Start to sketch out the initial Conceprocity model
 It’s often necessary then to go back, reconsider and refine the initial
lists in the dictionary
 This stage also typically requires further research around the
original question
If you wish to do so, add events and logical operators to
the model
Create, refine and use the model in Lucidchart
STOP! GO NO FURTHER…
UNLESS YOU WANT TO
EXPERIENCE CAPRILOPE…
CAPRILOPE links and grammar
Different types of links (relationships):
 Association: simple connection
 Aggregation: is-a, is-made-of independent parts
 Composition: is-a, is-made-of dependent parts
 Specialisation / Generalisation: kind-of
 Regulation: controls, directs, influences…
 Precedence: comes-after, comes-before…
 Entrant-Product (Input-Output, Input-Product): is an input
to a procedure which yields output or product, causes, gives
rise to…
 Instantiation: is an example (instance) of…
Grammar Rules govern the valid types of links that
may join the knowledge types
Many of the grammar rules in Conceprocity closely
follow those of G-MOT – see (Paquette 2010)
Simple relationships: Aggregations
The Aggregation link ( G ) associates multiplicity – ordinality or
cardinality – with a relationship
Aggregation is an extension of the G-MOT model
It is essential in data modelling in accordance with the relational
model of (Codd 1970)
Link type
Aggregation link
(G)
Representation
Simple relationships: Associations,
Aggregations and Compositions
 The Association link ( A ) is simply an untyped connection between concepts. By untyped, we mean that the
modeller either does not yet know the type of the relationship or is not yet capable of deciding its more precise type.
 The Aggregation link ( G ) is a kind of association which says that one concept is part of another, together with
others of the same type, so that all the parts are together a group of parts which constitute a whole concept: a partwhole relationship. Aggregation is a special type of association used to model a "whole to its parts" relationship. In
basic aggregation relationships, the lifecycle of a part class is independent from the whole class's lifecycle.
 The Composition link ( C ) also connects a knowledge (object) with one of its constituents or its constitutive parts.
The composition aggregation relationship is just another form of the aggregation relationship, but the child class's
instance lifecycle is dependent on the parent class's instance lifecycle.
Link type
Association link
(untyped)
Aggregation link (
G)
Composition link (
C)
Representation
The difference between aggregation and
composition - 1– Composition
In a composition, the existence of the parts is dependent on
the ongoing existence of the parent
Example: in the human body, we can inter alia distinguish a
cardiovascular subsystem. That itself consists of a heart and
two lungs. Normally, it is meaningless to talk about the ongoing
existence of a heart after the body of which it forms a part has
died.
Similarly, for most purposes, we regard an engine as part of a
car
The key phrase is “is part of”, as in “An engine is part of a car”,
or “is composed of” or “consists of“” – example: A body is
composed of a heart and two lungs“
Composition is indicated in Conceprocity (as in UML) by a filled
lozenge
 For inspiration, see:
http://www.c-sharpcorner.com/UploadFile/pcurnow/compagg07272007062838AM/compagg.aspx
The difference between aggregation and
composition – 2 - Aggregation
In an aggregation, the existence of the components is independent of the
ongoing existence of the parent
Aggregation gives us a 'has-a' relationship
Within aggregation, the lifetime of the part is not managed by the whole
Thus, in a situation in which we wish to model households, neither the
persons who currently constitute a household nor the address at which
they live depend for their ongoing existence on the household
A child might be part of the household of his parents at one moment but
will continue to exist when that household no longer does
Similarly, the address at which a household lives is a building whose
existence is independent of that of the households who currently inhabit it
However, reversing the argument, a household consists of the persons
who currently inhabit an address
This whole discussion is reminiscent of the distinction between strong and
weak entities in the work of Peter Chen
Aggregation is indicated in Conceprocity (as in UML) by an open lozenge
Inheritance, generalisation and
specialisation
There are many instances when a general concept gives
rise to two or more specialisations
In each case, the specialisation shares certain properties
with the more general concept but also possesses
properties which are distinct from other specialisations
We say that each specialisation inherits the properties of
its parent but also has its own distinct properties
In a University library, we have the generalisation Member
and the specialisations Academic (Faculty) and Student
 Faculty can borrow more books for longer than can Students
In Conceprocity (as in UML) generalisation-specialisation
is represented using an open arrowhead
Multiplicities, cardinality and ordinality
We can ascribe a multiplicity to either end of an association, an
aggregation or a composition
This multiplicity can be:
 An exact number
 A range of numbers, separated by two dots
 An arbitrary unspecified number represented as an asterisk *
Example multiplicities:
1
1..1
0..1
1..*
0..*
3..4 – e.g. number of legs on a stool
0..0 – this means that there is NO relationship
Cardinality specifies the maximum number in relationships and
ordinality specifies the absolute minimum number in relationships.
When the minimum number is zero, the relationship is usually called
optional and when the minimum number is one or more, the relationship
is usually called mandatory.
Representation of links - 1
Link type
Generalisation /
Specialisation link
(G)
Regulation link (R)
Representation
Representation of links - 2
Link type
Precedence link (P)
Representation
Representation of links - 3
Link type
Sequence (EntrantProduct, InputOutput link) (I/P)
Instantiation link (I)
Representation
Type of links: some examples
Characteristics
Examples
The attributes or components of an
abstracted knowledge
• A « table » is composed of «
legs » and of a « flat surface ».
S
From specific to general
• « Table » is a sort of « furniture »
P
From the precedent to the next
C
An entrant or an output of a procedure
I/P
R
I
A principle defines a concept by
constraints to be satisfied or establishes
a law or a relation between several
concepts. The principle typically
controls from the outside the execution
of a procedure or the selection of other
principles.
Instances of concepts, procedures or
principles
• «Prepare an outline » precedes
«Write a text»
• «Outline » is an entrant of «Write
a text»
• «Text» is the product of «Write a
text»
• «Editing text norms» regulates «Text»
• «Air traffic control rules »
regulates «Take off the plane»
• «Project management rules»
regulates «Instructional design of a
telelearning system»
• «Robert’s car» is an instance of
«Volkswagen cars»
Representing Conceprocity relationships
Conceprocity relationships very broadly follow UML class
diagram conventions rather than G-MOT ones
This is because the UML conventions are more visually
expressive than the letters used in G-MOT and can be
made more semantically precise
The meta-syntax is:
Symbol
Meaning
Flow of control or of data
Influences, governs, directs…
Is instantiated as
Commentary concerning the
diagram
Principles and the regulation link
In Conceprocity, it is possible to link knowledge objects to
each other
The links are represented by different kinds of arrow,
indicating the type of links.
• The regulation link exists to enable links from Principles to
be expressed:
• In conjunction with CONCEPTs: Here the principle defines some
constraints that must be satisfied or establishes a law or a relation
between two or more concepts
• In conjunction with a PROCEDURE OR ANOTHER PRINCIPLE:
Here the principle controls or governs the execution of a procedure
or the selection of other principles
Labelling relationships
Conceprocity permits relationships to be labelled, but it
doesn’t insist that this be the case
In CAPRICE: YES, label the relationships because there
is no other way to give meaning to the relationship
In CAPRILOPE, if concepts, procedures and principles
are well named, there is usually no additional value in
labelling relationships
 A possible exception: multiplicities should perhaps be labelled
when modelling data structures, since a relationship between
classes or entity types is bi-directional and may require two labels
in order more fully to express its meaning
Conceprocity CAPRILOPE Notions
Concepts
Processes
E.g. see The Hobbit
Instance of object or idea E.g. the ball bowled One-off
actions
Relationships
by bowler Smith
Events
and logical connectors
which
the with
Activities:
Association
Book captured
is associated
knowledge E.g. go to the cinema
Eventwicket of batsmanE.g. repeated
book returned to library
Generalisation /
Book is a kind of media (medium!) periodically
Jones at Lords on
similar
actionswith a logical
Event
associated
specialisation Compound event
15/06/2015
connector
Processes:
Composition
A human is composed
of head and E.g. plan and
Concept: named class of E.g. red, hard,
personal
Logical
connector:
one of two
or
four
limbs and a Exclusive
torsoactivityOR: exactlyundertake
similar things or ideas,
bounces in
XOR
moretemplates
outcomes may cultural
occur inimprovement
a given
Regulation
Accountancy principles regulate
Principles:
Rules and Constraints
sometimes
characterised
(somewhat)
and diversion each
instance
accountancy
practice
byGeneral
facts and
controllable
fashion,
week
rules, permissions
,
Logical
connector:
Inclusive
OR:
one
or
more possible
measurements
used
in
cricket
–
a
Precedence
Birth
comes
before
life
comes
before
constraints
and logic that
OR cricket
outcomes may occur – represent
associated with specific
ball
death
surround and
sometimes
zeroActors:
with nullIntelligent
process Agents
instances of things;
these
govern
or
regulate
the
Input-Output (GHops + barley are brewed to make
are named properties
of
Knowledge-wielding
E.g.occur
students,
Logical
connector:
All the
possible outcomes will
concepts beer
MOT: Intrantthe concept
persons
teachers,
AND
in parallel
andininroles
no defined
Product) computer programs Programs
administrators
sequence
Super-concepts concrete
and sub- expressions
E.g. ball and
cricket
of
Instantiation
A123 Jemimah is a (specific) student
concepts
ball
Knowledge-wielding E.g. aircraft
algorithms and an encoding
intelligent agents
flight control
by programmers of
systems
knowledge
Grammar Rules
Grammar Rules govern the valid types of links that may
join the knowledge types
CAPRILOPE Grammar Rules - 1
CAPRILOPE Grammar Rules - 2
Conceprocity
event rules
Events must be
preceded and
followed by
EITHER a
procedure OR a
logical connector
Swim Lanes in Conceprocity
Business process models realised in BPMN or as Event
Process Chain EPC diagrams frequently make use of the
concept of swim lanes (or swimlanes) to show ownership
or responsibility for aspects of a process
The usual way to show such ownership or responsibility
(or simply participation) in a Conceprocity model is to
show an actor class or instance linked by a regulation link
to a concept or process
Conceprocity models can include swimlanes but
Conceprocity does not mandate their use
An exception occurs in the Conceprocity Event Process
Chain EPC model type where swimlanes should normally
be used for major actors
The Conceprocity CAPRILOPE Method – 1
Define a focus question to which your model will be a (partial)
answer, or at least delimit a clear topic area
Decide the type of model which you wish to build




Conceptual
Procedural
Prescriptive
Methods and processes
Decide the usage profile which is appropriate to you and to the
situation you are modelling
Create a Google Drive directory (folder) to contain the files that
will constitute the model
Begin to build a Conceprocity dictionary and glossary
containing initial lists of:
 Concepts (and specific instances: facts)
 Actors (and specific instances: e.g. named persons)
 Processes
The Conceprocity CAPRILOPE Method – 2
Create some examples for each notion
Think about the relationships between the concepts, actors
and processes
 Can you identify structural relationships between concepts? See
next slide…
 Or are concepts related only by processes?
Can you identify principles (rules) which affect the modelled
situation? Include constraints
Start to sketch out the initial Conceprocity model
 It’s often necessary then to go back, reconsider and refine the initial
lists in the dictionary
 This stage also typically requires further research around the original
question
Add principles, events and logical operators to the model
Create, refine and use the model in Lucidchart
Identifying structural relationships
between concepts
Relationship
Type
Association
English statement
is-associated-with
Try to avoid this very general relationship, in favour of:
Aggregation
is-a, is-made-of independent parts
Composition
Specialisation /
generalisation
Precedence
Input-Output
is-a, is-made-of dependent parts
kind-of
Regulation
Instantiation
comes-after, comes-before
is-input-to, causes, gives-rise-to; an input
to a procedure which yields output
controls, directs, influences
is-an-instance-of
Why Conceprocity is important
Conceprocity is a semi-formal visual knowledge
representation language which enables and encourages
the modeller to be more precise in defining, bounding and
relating conceptual and procedural knowledge
It’s a way to constrain and enhance natural language
expression
 to increase the precision of the meaning which the
modeller needs to express
To the extent to which two modellers can agree upon a
Conceprocity model, it is also a means to establish and to
verify communication of ideas and concepts
Student use of Conceprocity
PEC students use it to map the content and meaning of a
research article as their individual project
IBIS students use it in their individual project: active and
reflective learning journal
MIS students use Conceprocity in their individual project:
use a tool to improve the ways in which you get things
done and keeps found things found and progressively
enhance a Conceprocity map which shows how you use
ICT to live and work more effectively
Please ALWAYS use the Conceprocity template:
https://www.lucidchart.com/community/examples/view/42d
8-77d0-52b93213-9de6-29ca0a009f85
The Conceprocity template
If you use the correct template and if you are a part of the
ESC Rennes Lucidchart team, you should be able to see
the Conceprocity shape libraries which look like this:
References
• Ausubel, D.P., 2000. The acquisition and
retention of knowledge: A cognitive view,
Kluwer Academic Pub.
• Ausubel, D.P., 1963. The psychology of
meaningful verbal learning. Available at:
http://psycnet.apa.org/psycinfo/196410399-000 [Accessed September 19,
2013].
• Basque, J., 2013. La modélisation des
connaissances en milieu
organisationnel. Available at:
https://oraprdnt.uqtr.uquebec.ca/pls/publ
ic/docs/FWG/GSC/Publication/1518/93/1
924/1/52315/13/F2080926314_UQTR_
midi_p_dago_27mars13_VFF.pdf
[Accessed April 16, 2013].
• Buzan, T. & Buzan, B., 1996. The mind
map book: how to use radiant thinking to
maximize your brain’s untapped
potential, Plume Books.
• Checkland, P., 1981. Systems thinking,
systems practice, Chichester: Wiley.
• Checkland, P. & Tsouvalis, C., 1997.
Reflecting on SSM: The Link Between
Root Definitions and Conceptual
Models. Syst. Res. Behav. Sci., 14(3),
pp.153–168.
• Novak, J.D. & Cañas, A.J., 2008. The
theory underlying concept maps and
how to construct and use them. Florida
Institute for Human and Machine
Cognition Pensacola Fl, www. ihmc.
us.[http://cmap. ihmc.
us/Publications/ResearchPapers/T
heoryCmaps/TheoryUnderlyingConcept
Maps. htm].
• Paquette, G., 2010. Visual Knowledge
and Competency Modeling - From
Informal Learning Models to Semantic
Web Ontologies., Hershey, PA: IGI
Global.