the alter-nativa book for knowledge representation

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I The ALTER-NATIVA book for Knowledge Representation João Sarraipa Catarina Lucena Ricardo Jardim Gonçalves Universidade Nova de Lisboa Silvia Baldiris Ramon Fabregat Universidad Nacional de Girona Silvana Aciar Universidad Nacional de San Juan

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I

The ALTER-NATIVA book for Knowledge Representation

João Sarraipa

Catarina Lucena

Ricardo Jardim Gonçalves

Universidade Nova de Lisboa

Silvia Baldiris

Ramon Fabregat

Universidad Nacional de Girona

Silvana Aciar

Universidad Nacional de San Juan

The ALTER-NATIVA book for Knowledge Representation

II

The ALTER-NATIVA book for Knowledge Representation

III

Acknowledgements

Authors have taken efforts in this project. However, it

would not have been possible without the kind support

and help of many other individuals and organizations of

the same project. We would like to extend our sincere

thanks to all of them.

We are highly indebted to CALE, CAM and CAC

communities for their contributions in the thesaurus

building.

We also would like to express our gratitude to

UNINOVA for its kind co-operation in producing and

publishing this booklet.

The research leading to these results has received

funding from the European Union under grant

agreement: ALTER-NATIVA Project

(DCIALA/19.09.01/10/21526/245-575/ALFA III (2010)

88).

The ALTER-NATIVA book for Knowledge Representation

IV

The ALTER-NATIVA book for Knowledge Representation

V

Executive Summary

In general, formal knowledge representation enables

computers characterize relevant information related to

determined process elements and actors in a domain

for specific advanced reasoning. In the eLearning

domain, several mechanisms of knowledge

representation have been proposed, such as standards,

technological specifications and ontologies. Both

ontologies and specifications play an important role in

eLearning systems because they offer an explicit

conceptualisation allowing key concepts and terms

relevant to a given domain to be identified and defined

in a structure able to facilitate reasoning, use and

exchange knowledge between the components and

users of its systems and by that, to contribute to the

increase of its computational intelligence. In this paper

we introduce the importance of the knowledge

representation mechanisms to support the generation

of adaptable eLearning services for all.

The ALTER-NATIVA book for Knowledge Representation

VI

The ALTER-NATIVA book for Knowledge Representation

VII

Table of contents

ACKNOWLEDGEMENTS ...................................................... III

EXECUTIVE SUMMARY ........................................................ V

LIST OF FIGURES .................................................................. X

LIST OF TABLES ................................................................ XIII

ACRONYMS LIST ................................................................ XV

1 INTRODUCTION .......................................................... 1

2 KNOWLEDGE MODELLING APPROACH FOLLOWED IN

ALTER-NATIVA .................................................................... 3

2.1 TERMINOLOGY .......................................................... 5

2.2 DOMAIN DICTIONARY ................................................. 5

2.3 GLOSSARY ................................................................ 6

2.4 TAXONOMY .............................................................. 7

2.5 THESAURUS .............................................................. 8

2.6 ONTOLOGY ............................................................. 10

2.7 KNOWLEDGE BASE ................................................... 11

3 ALTER-NATIVA’S KNOWLEDGE BASE ......................... 12

3.1 ONTOLOGY ............................................................. 14

3.2 THESAURUS ............................................................ 20

3.3 KNOWLEDGE BASE MANAGEMENT INTERFACE ................ 20

3.3.1 Create class on Webprotégé ........................... 24

3.3.2 Create Property on WebProtégé ..................... 25

3.3.3 Create Instance on WebProtégé ..................... 27

The ALTER-NATIVA book for Knowledge Representation

VIII

4 THESAURUS OF ALTER-NATIVA PROJECT .................. 29

4.1 ALTER-NATIVA PROCESS FOLLOWED ......................... 30

4.2 THESAURUS INTERFACE ............................................. 34

4.2.1 Bot user ........................................................... 37

4.2.2 Administrator user .......................................... 38 4.2.2.1 Create a new concept.................................... 39 4.2.2.2 Edit concept .................................................. 41 4.2.2.3 Delete concept .............................................. 42

4.2.3 Bureaucratic user ............................................ 43

4.3 THESAURUS SYNCHRONIZATION .................................. 48

4.3.1 Delete concept ................................................ 49

4.3.2 Create concept ................................................ 50

4.3.3 Edit concept .................................................... 55

5 KB’S SERVICES OF THE PROJECT ................................ 57

5.1 KNOWLEDGE MANAGEMENT SERVICES ......................... 57

5.2 RECOMMENDATION SERVICES ..................................... 64

5.2.1 Recommendation of Users .............................. 65

5.2.2 Recommendation of VLOs .............................. 76

6 CONCLUSIONS .......................................................... 81

6.1 FUTURE WORK FEATURES .......................................... 82

7 REFERENCES ............................................................. 83

8 ANNEXES .................................................................. 86

8.1 EXCERPT OF LOM METADATA REPRESENTED IN ALTERNATIVA

KB 86

The ALTER-NATIVA book for Knowledge Representation

IX

8.2 EXCERPT OF DRD METADATA REPRESENTED IN ALTER-

NATIVA KB ........................................................................ 90

8.3 USER MODEL ........................................................... 92

8.4 WIKI TREE OF MATHEMATICS THESAURUS .................. 111

8.5 WIKI TREE OF LITERATURE THESAURUS ...................... 114

8.6 WIKI TREE OF TEACHING THESAURUS ........................ 116

8.7 WIKI TREE OF SCIENCE THESAURUS ........................... 117

The ALTER-NATIVA book for Knowledge Representation

X

List of Figures

Figure 1 – KREs Relations in the taxis path to build

knowledge ...................................................................... 4

Figure 2 - Extract of a domain dictionary ....................... 6

Figure 3 – Example of Glossary ...................................... 9

Figure 4 - A part of the ALTER-NATIVA Knowledge Base

...................................................................................... 13

Figure 5- Knowledge base management interface ...... 21

Figure 6 - ALTER-NATIVA WebProtégé ......................... 23

Figure 7 - Create class option ....................................... 24

Figure 8 - Form to select a new class name ................. 24

Figure 9 - New class created ........................................ 25

Figure 10 - Create Property .......................................... 26

Figure 11 - New property form .................................... 26

Figure 12 - Create instance .......................................... 27

Figure 13 – New individual form .................................. 27

Figure 14 - Property value attribution ......................... 28

Figure 15 - Taxonomic structure illustration of the

ALTER-NATIVA Thesaurus............................................. 29

The ALTER-NATIVA book for Knowledge Representation

XI

Figure 16 - Thesaurus Building methodology [3] ........ 31

Figure 17 – Hierarchical representation of concepts ... 35

Figure 18 - Wiki front page options.............................. 36

Figure 19 - Wiki concept page example ....................... 38

Figure 20 – Steps to create a new concept .................. 41

Figure 21 – Steps to edit a concept .............................. 42

Figure 22 - Delete concept ........................................... 43

Figure 23 - Access the User Merge and Delete option. 44

Figure 24 - Delete user from database ......................... 46

Figure 25 – Change user rights ..................................... 47

Figure 26 - Synchronization architecture ..................... 48

Figure 27 - Delete concept with children associated ... 50

Figure 28 - Creation of a concept that points to an

existing master concept ............................................... 52

Figure 29 - Creation of a concept that points to a non-

existing master concept ............................................... 53

Figure 30 - The creates concept is referred as a master

concept ......................................................................... 54

Figure 31- Knowledge Management services .............. 59

The ALTER-NATIVA book for Knowledge Representation

XII

Figure 32 - Recommendation of services architecture 65

Figure 33 - Algorithm to obtain the most similar VLOs 80

The ALTER-NATIVA book for Knowledge Representation

XIII

List of Tables

Table 1 - Support Tools description ............................. 17

Table 2 - Use case of concept creation ........................ 55

Table 3 - Summary of Knowledge Management services

...................................................................................... 61

Table 4 - Recommendation of services with similar

teaching experience ..................................................... 70

Table 5 - Recommendation of users with specific similar

profile characteristics ................................................... 72

Table 6 –Recommendation of users based on the

number of interactions ................................................ 74

Table 7 - Recommendation of users based on the

number of similar characteristics ................................. 74

Table 8 –Recommendation of users based on a

combination of number of interactions with common

profile users .................................................................. 75

Table 9 - Historical information associated to a VLO ... 76

Table 10 - Recommendation of VLO based on rating .. 77

Table 11 - Recommendation of VLO based on the

number of times consulted .......................................... 77

The ALTER-NATIVA book for Knowledge Representation

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Table 12 - Recommendation of the most similar VLO . 78

Table 13 - Combined recommendation of VLOs .......... 78

Table 14 - LOM metadata ............................................. 86

Table 15 - DRD metadata ............................................. 90

Table 16 - User Model General Profile ......................... 92

Table 17 - User model access to information

preferences .................................................................. 93

Table 18 - User Model ALTER-NATIVA Profile .............. 94

Table 19 - User Model Accessibility Profile ................ 103

Table 20 - User Model access preferences ................ 108

The ALTER-NATIVA book for Knowledge Representation

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Acronyms list

DB Data Base

DRD Digital resource Description

LOM Learning Object Metadata

KB Knowledge Base

KRE Knowledge Representation System

VLO Virtual Learning Object

1

1 Introduction

Currently is observed a great need for the development

or generation of services or mechanisms of adaptive

and intelligent E-learning content. E-learning is the use

of Internet technologies to enhance knowledge transfer

and performance in education and training. This

technologies offer learners control over content,

learning sequence, pace of learning, time, and often

media, allowing them to tailor their experiences to

meet their personal learning objectives [1].

Virtual education services should be accessible to

everyone (teachers and students). For that reason is

necessary to consider the specific needs of each user,

and consequently adapt the process to solve those

needs in a dynamic way. This can be done trough the

formal representation of knowledge that can be used

to support adaptive e-Learning services, even when it is

considered diversity characteristics.

This knowledge must be available and maintained by all

the involved community members on an e-learning

organization. In align to this, inside ALTER-NATIVA

community it was identified the need of organizing the

knowledge in such way that it could support the e-

learning infrastructures as described before. Thus it

was implemented the ALTER-NATIVA Knowledge Base

(KB) supported by web services and special graphic

The ALTER-NATIVA book for Knowledge Representation

2

interfaces to facilitate the insertion, edition or

elimination of the knowledge necessary for the

adaptive e-Learning creation using the e-Learning

ALTER-NATIVA platform elements, such as Atutor,

Colabora and Repository.

The ALTER-NATIVA book for Knowledge Representation

3

2 Knowledge Modelling approach

followed in ALTER-NATIVA

A Knowledge Representation Element (KRE) is an

element that facilitates the formal representation of

the knowledge in a specific domain. In the following

will be presented and explained some examples of

those elements: Dictionary; Glossary; Taxonomy;

Thesaurus; and KB.

The diagram of the Figure 1 represents the taxis path to

build knowledge of a specific domain. “Taxis” comes

from the Greek and means arrangement and to place in

order [2], which in this specific case represents a

specific arrangement, structured, of the lexicon to build

knowledge.

The ALTER-NATIVA book for Knowledge Representation

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Figure 1 – KREs Relations in the taxis path to build knowledge

In order to have a KB it is need to gather the knowledge

in a explicit way composed by, terminology, glossary,

thesaurus and ontologies supported by taxonomies,

domain dictionaries and human tacit knowledge. To

build a KB it is needed to build all the KRE presented in

Figure 1. First it starts to have a terminology to then

build a glossary followed by a thesaurus and finally the

ontology, which when populated becomes the KB in a

domain. The approach followed in ALTER-NATIVA is

based on MENTOR (methodology for enterprise

reference ontology development) [3]. Each one of

these components is explained in the following

The ALTER-NATIVA book for Knowledge Representation

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subsections. And latter on section 4.1 a more detailed

description of the knowledge gathering is described.

2.1 Terminology

Terminology is the study of terms and their use. Terms

are words that are used in specific contexts.

Terminology therefore denotes a more formal

discipline which systematically studies the labelling of

concepts particular to one or more concept fields or

domain of human activity, though research and analysis

of terms in context, for the purpose of documenting

and promoting correct usage [4].

2.2 Domain Dictionary

A dictionary is a book of alphabetically words in a

specific language, with definitions, etymologies,

pronunciations, and other information; or a book of

alphabetically listed words in one language with their

equivalents in another, also known as a lexicon.

A domain dictionary has been found to be one of the

most useful tools for a domain analysis. The dictionary

lessens a great deal of miscommunication by providing

users with information: 1) in a central location to look

for terms and abbreviations that are completely new;

The ALTER-NATIVA book for Knowledge Representation

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2) where definitions of terms are used differently or in

a very specific way within the domain [5]. Figure 2

illustrates an example of an extract of a domain

dictionary.

Figure 2 - Extract of a domain dictionary

2.3 Glossary

Glossary is a list of specialized terms, mostly in

alphabetic order, that sometimes are unique to a

specific concept. Each term is composed by its

corresponding description. It includes descriptive

comments and explanatory notes, such as definitions,

synonyms, references, etc.

The ALTER-NATIVA book for Knowledge Representation

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A glossary can be used when communicating

information in order to unify knowledge sharing. A

glossary is understood as a set of terms and their

definitions, and is bound to the source document or

domain where these definitions are set Figure 3.

2.4 Taxonomy

It has become fashionable in certain circles to apply the

term in a wider, more general sense, where it may refer

to a classification of things or concepts, as well as to

the principles underlying such a classification [6].

A taxonomy is a classification system that categorizes

all the information in a class/subclass relationship,

representing a simple tree structure. At the top of this

structure is a single classification, the root node that

applies to all objects. The root node represents most

general category of all things that the domain is related

to. Nodes below this root are more specific

classifications that apply to subsets of the total set of

classified objects [6]. For any category, each

subcategory is a taxonomy.

Each child is a subset of the parent. The intersection of

each pair of children, in same level, is empty. Any path

The ALTER-NATIVA book for Knowledge Representation

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from the root to a leaf is called a branch. Since

taxonomies are transitive, child nodes aggregate

parents’ categories by heritage.

2.5 Thesaurus

A thesaurus is a structure that manages the

complexities of terminology and provides conceptual

relationships, ideally through an embedded

classification. A classification is a structure that

organizes concepts into a hierarchy, possibly in a

scheme of facets. A monolingual thesaurus has terms

from one language, a multilingual thesaurus from two

or more languages [7].

associated meanings about a domain in a semantic

related structure. A thesaurus is like taxonomy of

domain concepts composed by its reference meanings.

The thesaurus can be then represented by a set of

classes representing domain reference concepts with

The ALTER-NATIVA book for Knowledge Representation

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Figure 3 – Example of Glossary

The ALTER-NATIVA book for Knowledge Representation

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2.6 Ontology

Gruber stated in 1993 one of the most well known

description about what is an ontology: An ontology is a

formal, explicit specification of a shared

conceptualization [8]. Taking the example of the

taxonomy presented before, ontology is like the

enrichment of such structure, with properties and rules

that relates its concepts with the purpose of

representing a segment of the reality following the

view of a determined group.

Recently, it has been seen an explosion of interest in

ontologies as artefacts to represent human knowledge

and as critical components in knowledge management,

the Semantic Web, business-to-knowledge applications,

and several other application areas. Ontologies are now

being recognized as important components of

information systems and information processing. In the

areas of Knowledge representation and reasoning and

of conceptual modelling, it has long been recognised

that conceptualising a domain is a prerequisite for

understand the domain and processing information

about the domain, especially in the case of large, non-

trivial domains [9].

The ALTER-NATIVA book for Knowledge Representation

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2.7 Knowledge Base

Ontologies aggregate semantics, rules and

characteristics able to classify and represent a segment

of the reality. An ontology is the (unspecified)

conceptual system, which underlies a particular KB

[10]. By other words, ontologies provide some

structure for development of KBs, serving to define its

models [11]. When ontologies are associated with real

instances/individuals it becomes a KB. A KB composed

by ontologies and thesaurus structured by a similar

taxonomy that aggregates a glossary of terms in a

specific domain can represent such semantic organized

structure establishing in this way the lexicon of a

specific domain Figure 1 [12].

The ALTER-NATIVA book for Knowledge Representation

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3 ALTER-NATIVA’s Knowledge Base

The establishment of a KB for ALTERNATIVA arises from

the need to represent all the knowledge related with

the project. Its main objective is to facilitate knowledge

management, which the community members would

be able to use, but also actively participate in its

maintenance. By this, ALTER-NATIVA’s KB will be in a

constant updating, thus keeping alive. The ALTER-

NATIVA’s KB is split in two distinct parts: the

“Ontology” and the “Thesaurus” (Figure 4).

The ALTER-NATIVA book for Knowledge Representation

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ALTER-NATIVA Knowledge Base

Thesaurus

Thesaurus of

support tools

Thesaurus of

Areas

Ontology

Performance

Support tools

User profile

Virtual learning

objects (VLO)

Alternativa

technologies

Users

Metadata

Preferences

Recommendations

General profile

Accessibility profile

Alternativa profile

Participation

Performance scenarios

Participation in

performance scenario

DRD

LOM

Has DRD metadata

User to recommend

Had participation

Has keywords

VLO consulting

User interactivity

Interaction with user

Has LOM metadataHad consulted VLO

Has alternativa profileHas accessibility profile

Has general profile

Thesaurus of science

Thesaurus of mathematics

Thesaurus of literacture

Thesaurus of teaching

Has keywords

Relation of type:

Is a

Other type

Figure 4 - A part of the ALTER-NATIVA Knowledge Base

The Ontology is dedicated to represent the Knowledge

of the platform. It has three main objectives, the first is

to enable professors to establish cooperation’s through

COLABORA tool; the second is related to possibility to

create Virtual Learning Objects (VLOs), thus they need

to be saved and categorized using a common

The ALTER-NATIVA book for Knowledge Representation

14

vocabulary understood by all the community; the third

is related to the searching of information namely VLOs

or users related to specific characteristics.

The Thesaurus is dedicated to represent the lexicon of

ALTER-NATIVA. Thus its main purpose is to have a set of

reference concepts and meanings about its domain. It

is from this set of concepts that VLO are characterized,

and is also using a specific wiki that the thesaurus is

updated enabling, as described before, to maintain this

community knowledge alive.

Consequently the further sectors of this chapter

present in detail these two KB main sectors (see Figure

4), the Ontology and the Thesaurus.

3.1 Ontology

An ontology provides a vocabulary that describes a

domain of interest and a specification of the meaning

of terms used in the vocabulary. By defining shared and

common domain theories, ontologies help both people

and machines to communicate concisely, supporting

the exchange of semantics and not only syntax [13].

Considering this definition is to conclude that, an

ontology can represent not only the different classes,

The ALTER-NATIVA book for Knowledge Representation

15

but also their properties and relations in the scope of

the ALTER-NATIVA’s network. Therefore, it provides

support to the creation of virtual collaborative

communities and VLOs through recommendation

services, which uses user profiles and other information

as support learning tools or objectives to enhance

accessibility of trainees. It is also necessary to

understand how users and their profiles are related

with the Virtual learning Objects and what kind of tools

can be used to reduce the learning vulnerability

(diversity) of some users

The Ontology is composed by six main classes, where

the classes Users and Virtual Learning Objects are its

core, this because they are, directly or indirectly,

related to all the other classes (see Figure 4). The User

class represents all the users of the ALTER-NATIVA

platform, and the VLO class represents the Virtual

Learning Objects. In additional, all the

recommendations in the scope of the project are based

on the content of the information represented by these

both classes.

The User profile class is able to represents a user profile

characteristics. This is composed by three main profile

characteristic, namely: 1) General Profile; 2)

The ALTER-NATIVA book for Knowledge Representation

16

Accessibility Profile; and 3) Alternativa Profile (Annexes

8.3). The General Profile contains the general

information related to a user, in particular to the

communities, which a user belongs and also its level of

studies accomplished. The Accessibility profile contains

the Information related to the disabilities of a user

(visual, hearing, physical and cognitive). By the last, the

Alternativa Profile that encompasses the information

about the teaching profiles, namely the specialization

area, the investigation groups, which a user was

involved, the level of knowledge when leading with

some disability, etc...

The Support Tools class is designed to represent the

support tools and its characteristics. One example of

the characteristics represented is shown in Table 1. As

can be observed, it also contains the information

related to the kind of users for which a support tool is

designed to. This class is connected to the Thesaurus

through keywords (Palabras Clave) of the supporting

tool description.

The ALTER-NATIVA book for Knowledge Representation

17

Table 1 - Support Tools description

Camera Mouse (SG010)

Descripción: Permite controlar en

Windows el puntero del ratón

simplemente moviendo la cabeza, a

partir de la imagen tomada por una

webcam.

El primer paso consiste en calibrar

el programa, para que identifique

los movimientos de la cabeza, tras

lo cual el puntero responderá a

estos movimientos.

Para realizar los clics, sólo es

necesario dejar el puntero

relativamente quieto durante un

período de tiempo configurable.

También es posible hacer doble

clic.

Imagen

Ilustración 1 Configuración de

Camera Mouse

Autor/Fabricante/vendedor:

Boston College

URL: http://www.cameramouse.org

Área: Ciencias Lenguaje Matemáticas

Discapacidad: ☐ Auditiva

☐ Cognitiva

Física ☐ Visual

The ALTER-NATIVA book for Knowledge Representation

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Camera Mouse (SG010)

Vulnerabilidad: ☐ Étnica

Socio-Económica ☐ Violencia

Idioma: ☐No aplicable

Sólo

inglés

☐ Sólo

español

☐ Varios, incluido el

español

Sistema Operativo

Windows ☐Mac ☐GNU/Linux

☐Symbian

☐iPad ☐Android

☐Chrome ☐No Aplicable

Criterio del revisor

Palabras Clave: accesibilidad, diversidad, tecnología, emulador, ratón,

webcam

Recomendable

☐No recomendable

Notas adicionales:

La aplicación es fácil de instalar y de

configurar por el usuario. Al ser

software libre es apropiada para ser

integrada en el kit alternativa

The ALTER-NATIVA’s Technologies class is conceived to

represent the technologies of the platform. It

The ALTER-NATIVA book for Knowledge Representation

19

aggregates the representation of the VLO metadata

with the user’s preferences that are registered when

users access the information, which further on makes

possible some recommendations. The subclass

metadata of the ALTER-NATIVA’s Technologies class

represents excerpts of the LOM (Learning Object

Metadata) and DRD (Digital resource Description)

chosen to be the metadata of each VLO in ALTER-

NATIVA (see Annexes 8.1). In the Recommendations

class are represented the interactions between users,

namely the activities that they share. It’s also

represented which are the VLOs that a specific user

consulted. Finally, the Preferences class has the

information related with the way how users prefer to

access to the information (see Table 20 of Annexes).

Finally, the Performance class represents all the

performance scenarios of the platform and the user’s

participations at these performance scenarios. This

information is represented accordingly with the

information represented in the first section of Table 18

at C in the annexes.

The ALTER-NATIVA book for Knowledge Representation

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3.2 Thesaurus

Thesaurus is like a taxonomy of domain concepts

composed by its reference meanings. In what concerns

the ALTER-NATIVA project, the Thesaurus contains

definitions that make possible a common

understanding about the disabilities that affect the

platform users, the different kinds of possible available

help and its characteristics. Thesaurus also contains

definitions to accomplish the understanding of VLO,

and then it gives a brief definition about his concepts

and sub-concepts.

The Thesaurus is related to the Ontology through

keywords used in tools guides and in metadata content

of VLOs. A better explanation of the Thesaurus is

presented with more detail in section 4.

3.3 Knowledge base management

Interface

The ALTER-NATIVA Knowledge Base can be managed in

two different ways: 1) by an ontology manager who can

directly edit the KB offline and upload the OWL file into

the repository folder using SSH (Secure Shell)

accordingly to the Webprotégé server specifications: 2)

The ALTER-NATIVA book for Knowledge Representation

21

by various community users that can edit online the KB

trough an ontology editor web interface (Figure 5).

Ontology manager

KB repository

Webprótegé

ALTER-NATIVA Knowledge Base

Thesaurus

Thesaurus of

support tools

Thesaurus of

Areas

Ontology

Performance

Support tools

User profile

Virtual learning objects (VLO)

Alternativa technologies

Users

MetadataPreferences

Recommendations

General profile

Accessibility profileAlternativa profile

Participation

Performance scenarios

Participation in performance scenario

DRDLOM

Has DRD metadata

User to recommend

Had participation

Has keywords

VLO consultingUser interactivity

Interaction with user

Has LOM metadataHad consulted VLO

Has alternativa profileHas accessibility profile

Has general profile

Thesaurus of scienceThesaurus of mathematics

Thesaurus of literactureThesaurus of teaching

Has keywords

Relation of type:

Is a

Other type

Protégé

Apache TomcatSSH

Community Users

Figure 5- Knowledge base management interface

An ontology editor needs a graphical visualization of

ontologies. Such representation can be accomplished

by means of directed or nested graphs, topic maps or

other techniques. However it isn’t an easy operation to

accomplish, because ontologies are more than just a

hierarchy of concepts [14]. They are the sum of various

relations and attributes between classes and entities,

and in turn, these can have a wide number of instances,

so it can be difficult to represent or visualize ontologies

effectively.

The ontology visualization tool used was Webprotégé

which is a Collaborative Ontology Editor and Knowledge

The ALTER-NATIVA book for Knowledge Representation

22

Acquisition Tool for the Web. WebProtégé includes a

set of predefined tabs, which contain the most popular

functionality in the protégé desktop editor [15]. For

example, the predefined Classes Tab enables users to

browse and edit the class hierarchy and the properties

of classes. The Properties Tab provides access to the

details of the properties in the ontology. The

Individuals Tab contains forms for acquiring instances

of classes [16]. Concluding, WebProtégé currently

supports the full-fledged editing of classes, properties

and individuals [16].

ALTER-NATIVA’s ontology was developed with Protégé

3.4.8, thus it uses OWL 1.0, RDF(S), and Frames

formats. That formats are supported by Webprotégé.

The Knowledge Base is available online at the URL

http://arale.udg.edu:8080/webprotege (Figure 6).

The ALTER-NATIVA book for Knowledge Representation

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Figure 6 - ALTER-NATIVA WebProtégé

ALTER-NATIVA’s KB can be edited through Webprotégé

by a logged in user. This user can create, delete or edit

classes, properties and individuals. The steps to take in

each on the mentioned actions are explained in more

detail in the following subsections. Although the user

can change the Thesaurus but he/she must be aware

that those changes will not be reflected in the wiki

thesaurus. That is because the synchronization from

The ALTER-NATIVA book for Knowledge Representation

24

the ontology to the wiki is not implemented, it is only

implemented in the other way.

3.3.1 Create class on Webprotégé

To create a new class, the user must select the class

that will be the master (parent) of the new class

created and then press create, as is shown in Figure 7.

Figure 7 - Create class option

After that, will appear a form, so the user can choose

the name of the new class.

Figure 8 - Form to select a new class name

The ALTER-NATIVA book for Knowledge Representation

25

Then, the new class will appear in the specified father

class with the chosen name (Figure 9).

Figure 9 - New class created

3.3.2 Create Property on WebProtégé

In order to create a new property, the user needs to

select the tab Properties and then select “create” from

the various available actions to take (Figure 10).

The ALTER-NATIVA book for Knowledge Representation

26

Figure 10 - Create Property

Then will appear a form, where the user can enter the

name of the property and the property type to create

(Figure 11).

Figure 11 - New property form

The ALTER-NATIVA book for Knowledge Representation

27

3.3.3 Create Instance on WebProtégé

A new individual is created through the selection of the

“create” option in the individuals tab (Figure 12).

Figure 12 - Create instance

As in the previous cases, it will appear a form where

the user can fill with the name of the instance to be

created (Figure 13)

Figure 13 – New individual form

The ALTER-NATIVA book for Knowledge Representation

28

After that, is possible to fill in the properties values to

that instance (Figure 14).

Figure 14 - Property value attribution

The ALTER-NATIVA book for Knowledge Representation

29

4 Thesaurus of ALTER-NATIVA

project

The ALTER-NATIVA Thesaurus represents the

information related to the concepts of four distinct

areas, namely Literature, Mathematics, Science and

Teaching. This information is composed by the

definition of each concept (keyword), the creation or

agreement date and the author/authors.

Mathematics

· Definition

· Creation data

· Author of the concept

Literature

· Definition

· Creation data

· Author of the concept

Teaching

· Definition

· Creation data

· Author of the concept

Science

· Definition

· Creation data

· Author of the concept

Areas

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Thesaurus

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Concept

· Definition

· Creation data

· Author of the concept

Figure 15 - Taxonomic structure illustration of the ALTER-NATIVA Thesaurus

The ALTER-NATIVA book for Knowledge Representation

30

4.1 ALTER-NATIVA process followed

The process followed for the thesaurus building has,

three steps: (1) terminology gathering; (2) glossary

building; and (3) thesaurus building (Figure 16). These

steps were defined based on the MENTOR, which

defines a set of workflows that also establishes a

thesaurus for the domain before starting the ontology

building [3].

The terminology gathering step (step 1) concerns the

process of collecting all relevant terms or concepts in a

specific domain previously defined. All the participants

in the process should give their inputs. There is no rule

from where the terms should come, since they are

related to the domain established. Concerning the

ALTER-NATIVA specific Thesaurus building case, was

asked to several professors of each area to collect

terms/concepts that may be used as keywords to

characterize Virtual Learning Objects that they think

they could intend to build in their future work.

All the concepts provided from contributors are

acceptable in this step, as nobody has authority at the

moment to erase another’s participant term. Thus, the

terms should be collected with reference to the

The ALTER-NATIVA book for Knowledge Representation

31

contributor, in order to enable each contributor to

provide term’s definitions during the next step.

No

Domain Defined

Domain related terms

collection

Annotations

attribution to the

terms

Terms revision

Agreement?

Taxonomic structure

definition

Terms classification

in the defined

structure

Agreement?

Yes

Thesaurus

Yes

Te

rmin

olo

gy

Ga

the

rin

gG

los

sa

ry

Bu

ild

ing

Th

es

au

rus

Bu

ildin

g

Figure 16 - Thesaurus Building methodology [3]

The Glossary building step builds a glossary in the

domain defined. It starts with annotations attribution

to the terms collected in the step before (Terminology

gathering). Then, each professor should provide the

The ALTER-NATIVA book for Knowledge Representation

32

annotations for his/her own terms. After having all the

terms provided with annotations, it proceeds to the

terms revision cycle to reach a reference definition. The

process for revision of terms can have four mismatches

cases:

· Existence of two syntactically different terms

with the same meaning description – the action

is to adopt one of the terms for being the

reference in such semantics meaning.

· Existence of two syntactical equal terms with

the same meaning description – the action is to

erase one of them.

· Existence of syntactically different terms with

two different meaning descriptions – no action

needed, both must be kept.

· Existence of two syntactically equal terms with

two different meaning descriptions – the action

is to consolidate all the provided descriptions

together in one of them and erase the other. In

such a case, a new term could be proposed to

the list if there is no agreement in the

conjunction of the input descriptions and if the

term to be born is not present in the

terminology list.

The ALTER-NATIVA book for Knowledge Representation

33

After a careful revision of all the terms with a successful

agreement in their meaning consolidation, the glossary

is defined from the terminology list in the domain

specified.

The thesaurus-building step is composed of a cycle

where the knowledge engineers and the domain

experts define a taxonomic structure from the glossary

terms, establishing some as thesaurus node terms (see

Figure 15). Afterwards, the other terms are classified

into semantic proper paths in the existent taxonomic

structure, into reaching the thesaurus leafs. If there is

an agreement in the structure and in the terms

classified, the thesaurus is defined. If not, the cycle

starts again.

The thesaurus tree developed for each area is, available

in the annexes:

1. Thesaurus of Mathematics : Annexes 8.4; 2. Thesaurus of Sciences : Annexes 8.7;

3. Thesaurus of Literature : Annexes 8.5;

4. Thesaurus of Teaching : Annexes 8.6;

The ALTER-NATIVA book for Knowledge Representation

34

4.2 Thesaurus Interface

Since a Thesaurus is like a taxonomy of domain

concepts composed by its reference meanings, it was

used Wikimedia1 as a front-end to enable

communication and knowledge gathering from the

ALTER-NATIVA professor’s community. Together with

the wiki extension CategoryTree2 it was possible to

represent a hierarchical representation of the concepts

used in taxonomies (see Figure 17).

1 MediaWiki is a free software open source wiki package

written in PHP, originally for use on Wikipedia. It is now also used by several other projects of the non-profit Wikimedia Foundation and by many other wikis, including this website, the home of MediaWiki. 2 The CategoryTree extension provides a dynamic view of the

wiki's category structure as a tree. It uses AJAX to load parts of the tree on demand. CategoryTree was originally written by Daniel Kinzler as an external tool, but was later integrated into the MediaWiki software with the help of Tim Starling.

The ALTER-NATIVA book for Knowledge Representation

35

Hierarchical representation of

Concepts

Figure 17 – Hierarchical representation of concepts

It was developed four different wiki Thesaurus that are

respectively available at:

5. Thesaurus of Mathematics : http://arale.udg.edu/alternativa/matematic

a/?title=P%C3%A1gina_principal

6. Thesaurus of Sciences :

http://arale.udg.edu/alternativa/ciencia/?title=P%C3%A1gina_principal

7. Thesaurus of Literature :

http://arale.udg.edu/alternativa/ciencia/?title=P%C3%A1gina_principal

8. Thesaurus of Teaching :

The ALTER-NATIVA book for Knowledge Representation

36

http://arale.udg.edu/alternativa/didatic

a/?title=P%C3%A1gina_principal

Through each one of the wiki Thesaurus main page is

possible to access the other wiki thesaurus, as can be

seen in (Figure 18).

Access to other wiki Thesaurus

Access to subject children

Figure 18 - Wiki front page options

The Thesaurus wiki was configured to have three kinds

of users:

1. Bot – Only consulting privileges;

2. Administrator – wiki knowledge administration.

3. Bureaucratic – User administration privileges.

The ALTER-NATIVA book for Knowledge Representation

37

Any user can create his own account in “crear una

cuenta” at the right top corner of the wiki. By default

its account will be of the bot kind. The process to

change it is explained in the 4.2.3 bureaucratic

subsection.

4.2.1 Bot user

For a common bot user of Thesaurus wiki (without

admin privileges), is only possible to consult

information, namely

1. He/she can navigate through hierarchical

structure of the concepts that compose the

thesaurus and, by clicking on [+], he/she is able

to access to a concept children (Figure 18);

2. In additional, he/she can see the concept

definition, creation date and authors of each

concept (Figure 19). In such concepts definition

pages the user can go directly to its master

(parent) or children concepts (Figure 19).

The ALTER-NATIVA book for Knowledge Representation

38

Figure 19 - Wiki concept page example

4.2.2 Administrator user

The Thesaurus wiki administrator is able to manage the

information represented in the Thesaurus. There are

three main actions that the administrator can do to

keep the thesaurus updated: 1) Create a new concept;

2) Edit a concept; and 3) Delete a concept. Firstly the

user needs to login with his credentials. The login is

available in “iniciar sesión” at the right top corner of

the wiki ( Figure 19).

The ALTER-NATIVA book for Knowledge Representation

39

4.2.2.1 Create a new concept

There is various ways of creating a new concept. In the

following it is presented the easier way to do that. The

user must follow three steps to create a new concept,

as is illustrated in Figure 20. At first, the user needs to

search for the name of the new concept. The user has

to write in the searching form “category:” followed by

the new concept name (e.g. “category: new concept”

(see step 1 of Figure 20)). It is a new concept, thus it

shouldn’t exist in the thesaurus. If it exists will appear a

window like the one presented in Figure 19 but related

to the inserted concept. Thus, in this case the user does

not need to create it. If he/she inserted a real new

concept name, it will appear in the page the “Search

Results” as presented in the second step of Figure 20.

In this case, the user only needs to click on “categoria:

new concept”. By the last, a user must fill the form

illustrated of the step 3 with the required information

and press save.

If it is not inserted correctly the word “category:” the

wiki creates a wiki page instead of a wiki category. In

this case, it is necessary to eliminate the created page

and insert the concept in the wiki again. To find the

page badly created, it is a matter to go to the concept

The ALTER-NATIVA book for Knowledge Representation

40

father page if inserted correctly and see its children

concepts. Thus, the following step is to access to it and

then delete it. For this, it is only a matter to follow the

instructions to delete a concept (see “delete a concept”

on section 4.2.2.3). However if the badly created page

didn’t receive a concept father, then this page should

be searched directly in the overall list of pages created

in the wiki. Finally, is a matter to access to it and then

delete it as explained before.

In step 3 of Figure 20, the master concept (Concepto

Padre) of the form must be filled with a concept that

already exists in the Thesaurus tree. If the master

concept is filled incorrectly, the new concept will be

“lost” in the wiki. The admin can recover from this

situation searching this specific page, directly in the

overall list of pages created in the wiki. Then the user

should access to it, to then edit the concept and fill the

master concept with a valid name.

The ALTER-NATIVA book for Knowledge Representation

41

2

1

3

Figure 20 – Steps to create a new concept

4.2.2.2 Edit concept

The user can edit an existing concept of the Thesaurus

by pressing “Edit” in the corresponding page of the

concept to be edited (step 1 of Figure 21). Then will

appear a Form where the user can change the master

concept (Concepto Padre), the concept definition,

creation date and authors (step 2 of Figure 21).

As in the create concept section, if the master concept

is not filled correctly, the concept will be lost in the

The ALTER-NATIVA book for Knowledge Representation

42

wiki. In this case it is necessary to do the procedure

also presented in the mentioned subsection to recover

that situation.

1

2

Figure 21 – Steps to edit a concept

4.2.2.3 Delete concept

The user needs to press “Delete” in the concept

corresponding page to delete it (Figure 22) and then

confirm this action. If the eliminated concept has

children concepts, those concepts will be lost in the

wiki. They will be positioned at the root of the

Thesaurus. Thus they could be “moved” from there

The ALTER-NATIVA book for Knowledge Representation

43

simply by editing the master (parent) concept form of

those concepts.

1

2

Figure 22 - Delete concept

4.2.3 Bureaucratic user

The bureaucratic user can execute two different

actions: 1) Delete a user from the user database; and 2)

Promote a user to admin.

Delete a user from DB

The user elimination from the Data Base (DB) is

possible thanks to the installation of the wiki extension

The ALTER-NATIVA book for Knowledge Representation

44

“User Merge and Delete”3. After the installation of that

extension, in the wiki Special Pages appears the option

“User Merge and Delete”. The steps to access the

mentioned option are illustrated on Figure 23.

2

1

Figure 23 - Access the User Merge and Delete option

The bureaucratic user can delete another existing user

of the wiki by pressing “Merge and delete users” in the

Users and rights section of the special pages (see Figure

23 and Figure 24). Then will appear a Form where the

user can fill with the name of the user to delete (Old

3 User Merge and Delete extension allows wiki users with

the user merge permission (Bureaucrat by default) to merge one Wiki user's account with another Wiki user's account. (http://www.mediawiki.org/wiki/Extension:User_Merge_and_Delete)

The ALTER-NATIVA book for Knowledge Representation

45

user) and select the check point who says “Delete old

user” (step 2 of Figure 21).

Promote a user to admin

The bureaucratic user can manage the wiki privacy by

editing the users’ rights. This user can change another

user’s rights by pressing “User rights management” in

the “Users and rights” section of the special pages.

Then will appear a form to fill with the name of the

user whose rights will be changed. By the last, it is

necessary to fill the check box with the group where

the user will belong (step 2 of Figure 25).

The ALTER-NATIVA book for Knowledge Representation

46

1

2

Figure 24 - Delete user from database

The ALTER-NATIVA book for Knowledge Representation

47

Figure 25 – Change user rights

The ALTER-NATIVA book for Knowledge Representation

48

4.3 Thesaurus Synchronization

A general overview of the Thesaurus synchronization

architecture is shown in Figure 26. This architecture is

composed of four main components:

· The Thesaurus Wiki where the knowledge of

the professor’s community is gathered;

· The Thesaurus Wiki Data Base (DB) that

contains all the contents/concepts of the

Thesaurus Wiki and means of detecting any

changes that may occur;

· The ALTER-NATIVA KB Knowledge that contains

the ontology and also the Thesaurus;

· The Synchronization module, that serves as a

user interface to the synchronization process

between the wiki and the ALTER-NATIVA KB.

Thesaurus wiki

Wiki DBALTER-

NATIVA KB

Synchronization

module

JDBCProtegé

OWL API

Update changes

Figure 26 - Synchronization architecture

The ALTER-NATIVA book for Knowledge Representation

49

This architecture uses the wiki DB to detect any

changes that have occurred in the wiki since it was last

run and then updates the Knowledge base’s Thesaurus

accordingly. In the previous section was explained the

different action that an Admin user can execute in the

wiki Thesaurus. In this section will be explained how

the synchronization module handles these changes to

have a correct representation of the wiki knowledge

updated in the entire platform. At the following

subsections are explained in detail the three actions,

which represent the mentioned changes: 1) delete

concept; 2) create concept; and 3) edit concept.

4.3.1 Delete concept

The elimination of a concept directly affects the

structure of the Thesaurus tree. If the deleted concept

that have children associated, is just removed from the

Thesaurus tree. But if the deleted concept had children

associated it is necessary to take some actions to

reflect the wiki status. In this case, the children are

positioned in the Knowledge Base Thesaurus root. in

Figure 27 is illustrated the initial and final status of the

Thesaurus tree after the deletion of a concept with

children. As can be seen, the action is related to the

deletion of the “Concept b”, which in the initial

The ALTER-NATIVA book for Knowledge Representation

50

thesaurus tree had the children “Concept c” and

“Concept b”. In the final state is possible to see that

these concepts are shifted to the root (Thing).

Initial Thesaurus Tree

Concept b

· Master concept: Thesaurus

Concept deleted

Concept f

· Master concept: Concept y

Thing

·

Concept g

· Master concept: Concept x

Thesaurus

· Thing

Concept a

· Master concept: Thesaurus

Concept b

· Master concept: Thesaurus

Concept c

· Master concept: Concept b

Concept d

· Master concept: Concept b

Concept e

· Master concept: Thesaurus

Final Thesaurus Tree

Concept f

· Master concept: Concept y

Thing

·

Concept g

· Master concept: Concept x

Thesaurus

· Thing

Concept a

· Master concept: Thesaurus

Concept c

· Master concept: Concept b

Concept d

· Master concept: Concept b

Concept e

· Master concept: Thesaurus

Figure 27 - Delete concept with children associated

4.3.2 Create concept

As the delete concept action, the creation of a concept

will directly affect the structure of the Thesaurus tree.

So it is necessary to rearrange the three to handle the

The ALTER-NATIVA book for Knowledge Representation

51

three special cases that will be explained at the

following.

The Figure 28 illustrates the case where the inserted

concepts referrers another existing concept as a master

concept. As can be seen, the concept to insert in the

Thesaurus points at the concept “Concept b” as is

master concept. Since the “Concept b” exists in the

initial state of the thesaurus tree, the action to take is

to insert the “Concept h” has child of “Concept b”.

The Figure 29 illustrates the case where the inserted

concepts referrers a non- existing concept as a master

concept. As can be seen, the concept to insert in the

Thesaurus points at the concept “Concept z” as is

master concept. Since the “Concept z” does not exist in

the initial state of the thesaurus tree, the action to take

is to insert the “Concept h” has child of “Thing”, that

means, place the new concept in the root.

The ALTER-NATIVA book for Knowledge Representation

52

Initial Thesaurus Tree

Concept h

· Master concept: Concept b

New concept inserted

Concept f

· Master concept: Concept y

Thing

·

Concept g

· Master concept: Concept x

Thesaurus

· Thing

Concept a

· Master concept: Thesaurus

Concept b

· Master concept: Thesaurus

Concept c

· Master concept: Concept b

Concept d

· Master concept: Concept b

Concept e

· Master concept: Thesaurus

Concept f

· Master concept: Concept y

Thing

·

Concept g

· Master concept: Concept x

Thesaurus

· Thing

Concept a

· Master concept: Thesaurus

Concept b

· Master concept: Thesaurus

Concept c

· Master concept: Concept b

Concept d

· Master concept: Concept b

Concept e

· Master concept: Thesaurus

Final Thesaurus Tree

Concept h

· Master concept: Concept b

Figure 28 - Creation of a concept that points to an existing master concept

The ALTER-NATIVA book for Knowledge Representation

53

Initial Thesaurus Tree

Concept h

· Master concept: Concept z

New concept inserted

Concept f

· Master concept: Concept y

Thing

·

Concept g

· Master concept: Concept x

Thesaurus

· Thing

Concept a

· Master concept: Thesaurus

Concept b

· Master concept: Thesaurus

Concept c

· Master concept: Concept b

Concept d

· Master concept: Concept b

Concept e

· Master concept: Thesaurus

Final Thesaurus Tree

Concept f

· Master concept: Concept y

Thing

·

Concept g

· Master concept: Concept x

Thesaurus

· Thing

Concept a

· Master concept: Thesaurus

Concept b

· Master concept: Thesaurus

Concept c

· Master concept: Concept b

Concept d

· Master concept: Concept b

Concept e

· Master concept: Thesaurus

Concept h

· Master concept: Concept z

Figure 29 - Creation of a concept that points to a non-existing master concept

It is also possible to occur the case where the inserted

concept is referred as master concept by some of the

concepts placed in the root. Figure 30 illustrates the

mentioned case. As can be seen the “Concept y” is

pointed as master concept of “Concept f”. When the

new concept is inserted in the tree, “concept f” will be

placed bellow it.

The ALTER-NATIVA book for Knowledge Representation

54

Initial Thesaurus Tree

Concept y

· Master concept: Concept b

New concept inserted

Concept f

· Master concept: Concept y

Thing

·

Concept g

· Master concept: Concept x

Thesaurus

· Thing

Concept a

· Master concept: Thesaurus

Concept b

· Master concept: Thesaurus

Concept c

· Master concept: Concept b

Concept d

· Master concept: Concept b

Concept e

· Master concept: Thesaurus

Concept f

· Master concept: Concept y

Thing

·

Concept g

· Master concept: Concept x

Thesaurus

· Thing

Concept a

· Master concept: Thesaurus

Concept b

· Master concept: Thesaurus

Concept c

· Master concept: Concept b

Concept d

· Master concept: Concept b

Concept e

· Master concept: Thesaurus

Final Thesaurus Tree

Concept y

· Master concept: Concept b

Figure 30 - The creates concept is referred as a master concept

Figure 30 also illustrates that some of the mentioned

atomic cases can occur simultaneously. Table 2

contains a summary explanation of all the possible

conjugations of the mentioned atomic situations and

which are the steps to execute by the synchronization

module.

The ALTER-NATIVA book for Knowledge Representation

55

Table 2 - Use case of concept creation

Inserted master concept exists?

Any concept in the "Thing" who

reference the new concept as master

Action

Yes Yes · Put new concept below the class referred as master concept.

· Put the class tree of the concepts that are in the class Thing and refer the new concept as master concept below them.

No · Put new concept below the concept referred as master concept.

No Yes · Put new concept below the class Thing.

· Put the class tree of the concepts that are in the class Thing and refer the new concept as master concept below them.

No · Put new concept below the class Thing.

4.3.3 Edit concept

When a concept is edited, if the master concept field of

the form (see Figure 21) is not changed, it is only

necessary to save (update) the new information in the

Knowledge Base Thesaurus. If the master concept is

changed, may occur two situations: 1) the new master

concept does not exist in the Thesaurus tree, so is

necessary to execute the steps illustrated on Figure 29;

The ALTER-NATIVA book for Knowledge Representation

56

or 2) the new master concept exists in the tree and is

necessary to execute the steps illustrated on Figure 28.

The ALTER-NATIVA book for Knowledge Representation

57

5 KB’s services of the Project

The Implemented Web Services are responsible for

giving worldwide users the mechanism of Knowledge

Management and reasoning trough the Web (those

Web Services can be accessed on

http://arale.udg.edu:8080/axis2/services/listServices).

This services use JENA libraries, a java API for OWL, to

edit and query the Knowledge Base. The available

services are divided in two groups: Knowledge

Management services and Recommendation services. A

better description of those will be given in the following

subsections.

5.1 Knowledge Management services

Knowledge Management services are essentially

divided in two groups (see Figure 31): 1) Knowledge

Editing services, the ones related to the knowledge

edition; 2) Knowledge Query services, that are the ones

related to the knowledge consultation.

All these services are related to the VLO, VLO

consulted, User Model (profiles), Performance

scenarios, Thesaurus and users interactions.

The ALTER-NATIVA book for Knowledge Representation

58

59

Knowledge Management Services

· User Model creation

· User Model edition

· User Model elimination

Virtual Learning Objects

· VLO creation

· VLO edition

· VLO elimination

Knowledge Editing services

· LOM metadata edition

· DRD metadata edition

· LOM metadata creation

· DRD metadata creation

· ALTER-NATIVA profile creation

· General profile creation

· Accessibility profile creation

· ALTER-NATIVA profile edition

· General profile edition

· Accessibility profile edition

User Model

· Interactivite activity creation

· Interactive activity edition

· Interactive activity elimination

· Set activity name

· Set user collection

· Edit activity name

· Add user to activity

· Delete user from activity

VLOs consulted

· Add consulting information

· Edit consulting information

· VLO consulting Elimination

Users' interactions

· Performance scenario creation

· Performance scenario edition

· Performance scenario

elimination

· Add participation in scenario

· Edit participacion in scenario

· Elimination os participation in

scenario

Performance scenarios

· Set rating of VLO

· Set usuario who consulted the

VLO

· Edit VLO rating

· Increment number of times

Virtual Learning Objects

· Return of all VLOs’ identifiers

· Return of VLO metadata

Knowledge Query services

· Return LOM metadata

· Return DRD metadata

User Model

· User Interactivite activity

consulting· Consult activity

· Consult users’s collection

VLOs consulted

· User consulting information

Users' interactions

· Performance scenario

consulting

· User participation in scenario

consulting

Performance scenarios

· Rating over VLO consulted

· Number of times consulted

· Return of all users’ identifiers

· Return of users profiles· Return ALTER-NATIVA profile

· Return General profile

· Return Accessibility profile

· Return Thesaurus

ThesaurusThesaurus

· Return Mathematics Thesaurus

· Return Science Thesaurus

· Return Literature Thesaurus

· Return Teaching Thesaurus

· Thesaurus synchronization

· Synchronize Mathematics

Thesaurus

· Synchronize Science Thesaurus

· Synchronize Literature

Thesaurus

· SynchronizeTeaching

Thesaurus

Colabora RepositorioWeb ThesaurusATutor

Platform elements

Figure 31- Knowledge Management services

60

The user interactions and the VLO consulted are a kind

of log of the system which then are mainly used to

perform recommendations. Figure 31 also presents

how the Knowledge Management are responsible by

the integration of the ALTER-NATIVA KB with the other

elements of the platform. The blue colour represents

the connection between the platform element ATutor

and the Knowledge Base of the project. As can be

observed, the blue colour helps to clarify the services

that ATutor uses to enable its own access to insert/edit

and consult the information related with the VLOs and

keywords (those are provided from the Thesaurus).

The orange colour represents the connection between

the platform element Repositorio and the necessary

services to be able to upload the metadata information

of the VLOs into the Knowledge base.

The red colour represents which services the platform

element Colabora can use to manage the information

related to the users and their profiles. Is also

represented in red colour the services to manage the

interactions between the users and their participations

in performance scenarios.

The red colour connects the Web Thesaurus with the

service responsible by its the synchronization with the

Knowledge Base

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61

A summary list of all Knowledge Management services

and a brief description can be consulted on Table 3. The

First column of the table consists in a direct relation

with the explanation made for the Figure 31. The

second column represents the name of the Web service

group that can be consulted on the URL:

http://arale.udg.edu:8080/axis2/services/listServices.

Table 3 - Summary of Knowledge Management services

Knowledge Management service

Service Group

Service name Service description

Thesaurus

synchro synchro

This service makes the synchronization between the wiki Thesaurus and the Knowledge Base

User Model

Modelo_Usuario

create_Usuario

Creates a User and the associated profiles (ALTER-NATIVA; General and Accessibility)

delete_Usuario

Deletes a User and the associated profiles (ALTER-NATIVA; General and Accessibility)

Id_todos_usuarios Returns the identifiers of all the user in the Knowledge Base

delete_perfil_alternativa

Deletes the ALTER-NATIVA's profile of a user

delete_perfil_general

Deletes the General profile of a user

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62

delete_perfil_accesibilidade_a_tecnologia_de_interaccion_y_comunicacion

Delete the Accessibility profile of a user

Virtual Learning Objects

OVAs_Servicios

get_OVA_by_id

Gets the metadata of a VLO giving the VLO's identifier as input (accordingly with Table 14 and Table 15 )

upload_OVA_by_id

Uploads the metadata of a VLO giving the VLO's identifier and the metadata as input (accordingly with Table 14 and Table 15 )

get_OVAs_Ids Returns the identifiers of all the VLOs in the Knowledge Base

create_OVA Creates a VLO and the metadata associated

delete_OVA_by_id Deletes a VLO and the metadata associated

Performance

scenarios

Escenario

get_all_escenarios Returns the identifiers of all the Performance scenarios

create_escenario Creates a performance scenario

upload_escenario_desempeno

Uploads the information of a Performance scenario (accordingly with desempeño of Table 18)

Get_escenario

Gets the information of a performance scenarios given by a unique identifier (accordingly with desempeño of Table 18)

Thesaurus of

Mathematics

Thesaurus

create_tree_matematicas

Returns the Thesaurus of Mathematics concepts tree

create_tree_ciencias

Returns the Thesaurus of Sciences concepts tree

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63

create_tree_didaticas

Returns the Thesaurus of Teaching concepts tree

create_tree_lenguaje

Returns the Thesaurus of Literature concepts tree

User Model

Perfil_General

Upload_perfil_general

Uploads the General profile information related to a user given by a unique identifier (see Table 16)

Get_perfil_general

Gets the general profile information related to a user given by a unique identifier (see Table 16)

create_perfil_general

Creates a General profile for a user given by a unique identifier

User Model

Preferences

Upload_preferencias

Upload a user access preferences (see Table 20)

Create_preferencias

Create a user access preferences

Get_preferencias Get a user access preferences (see Table 20)

Delete_preferences Delete a user access preferences

User Model

Perfil_alternativa

Upload_perfil_alternativa

Upload a user ALTER-NATIVA's profile (accordingly with Table 18)

insercion_de_escenario_de_desempeno

Add a user participation in a performance scenario (accordingly with Table 18)

delete_participacion_por_id_usuario_y_nombre_escenario

Delete a user participation in a performance scenario

create_perfil_alternativa

Create an ALTER-NATIVA profile to a user

get_perfil_alternativa

Get a user ALTER-NATIVA profile (accordingly with Table 18)

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User Model

Perfil_de_accesibilidad

Upload_Perfil_accesibilidad

Upload a user accessibility (see Table 19)

Create_Perfil_accesibilidad

Create a user accessibility profile

Get_Perfil_accesibilidad

Delete a user accessibility profile (see Table 19)

5.2 Recommendation services

The recommendation services have as goal the support

in searching VLOs, which could be related to various

characteristics as for specific necessities (diversity) of

the trainees. It also has the goal to help on searching

professors related to specific profiles or teaching

experiences. The recommendations are essentially

done based on the User Model (profile), VLOs

metadata, historical information of the consulted VLO

by a user and users’ interactions. This information will

feed the ontology and make possible the

recommendation of items based on some existing

patterns (see Figure 32).

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65

UserVLO

Recommended items

Ontology

User

Interactions

Consulted

VLO

User

ModelVLO

Recommendation Services

Similar teaching experience

Recommendation of Users

Specific similar profile

characteristics

Number of interactions

Number of common

characteristics

Combination of number of interactions with common

profile users

Recommendation of VLOs

Similar VLOs (keywords)

More used VLOs

VLOs with higher rating

Combined recommendation of

VLOs

Recommendation System

Figure 32 - Recommendation of services architecture

In additional, the output of the recommender system

will be a user to interact or a VLO to consult,

respectively in the scope of Colabora or ATutor (Figure

32).

5.2.1 Recommendation of Users

Recommendation of users concerns the automatic

presentation of users to interact based on: 1) similar

teaching experience; 2) a specific similar profile

characteristics; 3) number of interactions between two

determined users; 4) number of common profile

characteristics between two users; and also 5) a

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combination of number of interactions with common

profile users.

When the recommendations deal with more than one

characteristic, the process of choosing the most

appropriated item is by calculating the one that has

more similarities to the set of chosen target

characteristics. Thus it was developed a function to be

used in such process, which calculates the strength of

each item with potential to be recommended. A

pseudocode example of a function that calculates the

item with “strength” in relation to a set of

characteristics is presented in the following.

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List_strength{

User_identifier;

Strength;

}

Function: Get users with similar expertise at creating

Input: User_identifier, maximum number of users

Begin

List_aux = Get list of users with the

same expertise creating

learning objects;

List_strength = [List; ones(0:

List_aux.size-1)];

List_aux = Get list of users with the

same expertise creating

didactical sequences;

List_strength =

List_aggregation(List_stren

gth, List_aux);

List_aux = Get list of users with the

same expertise creating

didactical sequences;

List_strength =

List_aggregation(List_stren

gth, List_aux);

List_strength =

Order_DESC(List_strength.st

rength);

End

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Output: List_strength(0: maximum number of users – 1);

End

Function: List_aggregation

Input: List_strength, List_aux

Begin

For i=0 to List aux.size() -1

If

(List_strength.User_identifier.contains(List_aux(i))

List_strength.strength =

List_strength.strength +1;

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Else

List_strength.Add(user_i

dentifier=List_aux(i);

strength = 1);

strength=1);

EndIf

EndFor

End

Output: List_strength;

End

The first user recommendation is based on users

teaching experience similarities. In Table 4 are

presented the services of recommendation of users

based on similar characteristics, together with a brief

description and the identification of the inputs and

outputs of the services.

There are two services from the following list, which

are in the gray lines that represent the aggregation of

the three previous services (in white lines). The

characteristics handled by these services are related to

the user profiles mainly presented at annexes 8.3

(Table 18).

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Table 4 - Recommendation of services with similar teaching experience

WEB SERVICE

DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns the users with experience in the same kind of disabilities which the user has experience to teach

Usuarios_que_tienem_mesma_Experiencia_en_su_trabajo_docente

User identifier

Serialized ArrayList of users

Returns the users with experience in the same level of education which the user has experience to teach

Usuarios_que_tienem_mesma_Experiencia_docente

User identifier

Serialized ArrayList of users

Returns the users with the same expertise creating learning objects

Usuarios_que_tienem_mesma_experticia_en_Creacion_de_Objetos_de_Aprendizaje

User identifier

Serialized ArrayList of users

Returns the users with the same expertise creating

Usuarios_que_tienem_mesma_experticia_en_Creacion_de_Secuencias_didaticas

User identifier

Serialized ArrayList of users

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didactical sequences

Returns the users with the same expertise creating didactical unities

Usuarios_que_tienem_mesma_experticia_en_Creacion_de_unidades_didaticas

User identifier

Serialized ArrayList of users

Returns the users with the most similar expertise creating learning objects, didactical sequences and didactical unities.

Usuarios_con_mesma_experticia

User identifier; maximum number of users

Serialized ArrayList of users

Returns the users with the same expertise with virtual scenarios

Usuarios_que_tienem_mesmo_manejo_de_escenarios_virtuales

User identifier

Serialized ArrayList of users

Returns the users with the same expertise with digital networks

Usuarios_que_tienem_mesmo_manejo_de_escenarios_redes_digitales

User identifier

Serialized ArrayList of users

Returns the users with the same expertise with

Usuarios_que_tienem_mesmo_manejo_de_escenarios_presenciales

User identifier

Serialized ArrayList of users

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classroom scenarios

Returns the users with the most similar expertise with virtual scenarios, digital networks and classroom scenarios

Usuarios_con_manejo_de_escenarios_mas_similares

User identifier

Serialized ArrayList of users

Other type of user recommendations is done based on

a specific similar profile characteristic mainly related to

professors’ formation. This recommendation is done by

searching for other users with some profile

characteristics based on the User Model profile defined

in ALTER-NATIVA and that is represented on Annexes

8.3. In Table 5 are described the Web Services of

recommendation developed concerning some specific

users’ profile characteristics.

Table 5 - Recommendation of users with specific similar profile characteristics

WEB SERVICE DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns the users Usuarios_que_tiene User Serialized

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with the same level of knowledge about the theories of sciences professors formation

m_mesmo_Grado_de_conocimiento_de_Las_teorias_sobre_la_formacion_de_profesores_de_ciencias

identifier ArrayList of users

Returns the users with the same level of knowledge about the theories of literatures professors formation

Usuarios_que_tienem_mesmo_Grado_de_conocimiento_de_Las_teorias_sobre_la_formacion_de_profesores_de_lenguaje

User identifier

Serialized ArrayList of users

Returns the users with the same level of knowledge about the theories of mathematics professors formation

Usuarios_que_tienem_mesmo_Grado_de_conocimiento_de_Las_teorias_sobre_la_formacion_de_profesores_de_matematicas

User identifier

Serialized ArrayList of users

Returns the users with the same development area

Usuarios_que_Pertenecem_a_mesmo_Camo_o_area_de_desarrollo

User identifier

Serialized ArrayList of users

Returns the users of the same virtual community

Usuarios_que_Pertenecem_a_mesma_comunidad_virtual

User identifier

Serialized ArrayList of users

The recommendation of users can also be done based

on the number of times that a user interacts with

another one. The Web Service is presented in the

following table.

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74

Table 6 –Recommendation of users based on the number of interactions

WEB SERVICE DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns the users with the higher number of interactions with one given user

return_usuarios_con_mas_interacciones

User identifier

Serialized ArrayList of users

The recommendation of users based on the number of

common profile characteristics has as goal to return the

user with the most similar profile comparatively to

another user. For that, is made a search of a user with

the higher number of similar profile characteristics

from the entire User Model (see Annexes 8.3). The

characteristics taken into account are the specialization

field, professional development field, first and second

languages. The Web services is presented in the

following table.

Table 7 - Recommendation of users based on the number of similar characteristics

WEB SERVICE DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns the users with the most similar

get_usuarios_similares User identifier

Serialized ArrayList

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characteristics from specialization field, professional development field, first and second languajes

of users

By the last, a recommendation service based on the

combination of number of interactions with common

profile users is presented. This is an aggregation of the

two previous presented services. This service is

presented in the following table.

Table 8 –Recommendation of users based on a combination of number of interactions with common profile users

WEB SERVICE DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns the users with the higher strength based on the most similar characteristics from specialization field, professional development field, first

get_usuarios_similares

User identifier

Serialized ArrayList of users

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and second languages and number of interactions with another user.

5.2.2 Recommendation of VLOs

The services of recommendation of VLOs are divided in

four groups, the recommendation based on: 1) higher

rating; 2) most used; 3) number of similarities with

other VLOs consulted by the user; and 4) combination

of the previous properties.

To automatically recommend VLO is necessary to have

a historical representation of the consulted VLO.

Historical information is represented by a table (Table

9), which has the VLO and the user identifier, the

number of times the user consulted the VLO and its

associated rating (1- Good or 0 - Bad).

Table 9 - Historical information associated to a VLO

VLO identifier User identifier Number of times consulted Rating

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77

The recommendation of VLO based on the rating (Table

10) and the number of times consulted (Table 11) can

be done directly through the previous table.

Table 10 - Recommendation of VLO based on rating

WEB SERVICE DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns the VLO with the higher rating

return_OVAs_mas_gustadas User identifier

Serialized ArrayList of VLO

Table 11 - Recommendation of VLO based on the number of times consulted

WEB SERVICE

DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns the most consulted VLO.

return_usuarios_con_mas_interacciones

User identifier

Serialized ArrayList of VLO

The recommendation of similar VLOs is done by

searching the ones that have the higher number of

keywords in common with other that the user

consulted before (see Table 12).

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Table 12 - Recommendation of the most similar VLO

WEB SERVICE DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns most similar VLOs Ovas_similares User identifier

Serialized ArrayList of VLO

The combined recommendation of VLOs is done based

on all the previous described recommendation services

for VLO. This service is presented in the following table,

and its algorithm steps are illustrated in Figure 33.

Table 13 - Combined recommendation of VLOs

WEB SERVICE DESCRIPTION

SERVICE NAME INPUT OUTPUT

Returns the VLO with the higher strength based on the number of times consulted, rating and number of similarities

Recomendacion_OVAs User identifier

Serialized ArrayList of VLO

In the top left of Figure 33, it is shown how the

algorithm starts, which is by collecting the identifiers of

all the VLO consulted by a user. Then, are collected the

keywords of those VLOs (top right). After this, as can be

observed in the middle left of the figure, it is generated

a new table without the VLO consulted by the user. It is

The ALTER-NATIVA book for Knowledge Representation

79

used to collect the VLO with equal keywords to be then

counted the number of keywords in common. Finally,

the recommendation result is represented by the

bottom table, which presents the VLO with common

keywords, ordered by the high number of keywords in

common.

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80

User identifier VLO identifier

1 1

1 3

2 1

VLO identifier Keywords

1Keyword 1

keyword 4

2

Keyword 1

Keyword 2

Keyword 3

3 Keyword 5

4Keyword 4

Keyword 5

5Keyword 8

Keyword 3

6Keyword 6

Keyword 5

7

Keyword 1

Keyword 4

Keyword 5

VLO identifier Keywords

2

Keyword 1

Keyword 2

Keyword 3

4Keyword 4

Keyword 5

5Keyword 8

Keyword 3

6Keyword 6

Keyword 5

7

Keyword 1

Keyword 4

Keyword 5

VLO identifierNumber of

similar keywords

7 3

4 2

2 1

6 1

Figure 33 - Algorithm to obtain the most similar VLOs

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81

6 Conclusions

In this document report it is presented the KB

developed to represent the ALTER-NATIVA’s

knowledge. It includes all the metadata needed to

characterize the various e-learning elements (e.g.

courses) and users. This document also describes this

KB related services, which make possible the

Knowledge edition and query, as also the generation of

recommendations for users and VLO.

In additional it is also shown the Wiki Thesaurus and its

functionalities to represent the lexicon of the ALTER-

NATIVA’s community. This wiki Thesaurus has as goal

the: 1) Classification of the e-learning elements; 2)

representation of concepts and reference descriptions;

and enables 3) the constant update of the lexicon

information by the community. This lexicon is reflected

in the ALTER-NATIVA’s KB due to a synchronization

service. Such process enables a harmonization of the

related community e-learning elements

characterization but also the knowledge handled by the

developed ALTER-NATIVA platform.

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6.1 Future Work features

As a future work, it is intended to provide some further

developments and respectively instructions to support

other Thesaurus area inclusion in the platform. This can

be done through the installation of a Wikimedia with

the same features of the wikis described in this

document. It is also necessary to create a new

ramification of the Thesaurus new area in the KB, and

then add to the synchronization service the necessary

access to the related owl file and wiki.

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7 References

[1] J. G. Ruiz, M. J. Mintzer, and R. M. Leipzig, “The impact of E-learning in medical education.,” Academic medicine : journal of the Association of American Medical Colleges, vol. 81, no. 3, pp. 207–212, 2006.

[2] “taxis @ www.thefreedictionary.com.” .

[3] J. Sarraipa, R. Jardim-Gonçalves, and A. Steiger-Garção, “MENTOR: an enabler for interoperable intelligent systems.,” Int. J. General Systems, vol. 39, no. 5, pp. 557–573, 2010.

[4] “Terminology @ en.wikipedia.org.” [Online]. Available: http://en.wikipedia.org/wiki/Terminology#Typology.

[5] R. Jardim-Goncalves, J. Sarraipa, C. Agostinho, and H. Panetto, “Knowledge framework for intelligent manufacturing systems,” J. Intell. Manuf., vol. 22, no. 5, pp. 725–735, 2011.

[6] “Taxonomy @ en.wikipedia.org.” [Online]. Available: http://en.wikipedia.org/wiki/Taxonomy.

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[7] D. Soergel, Thesauri and ontologies in digital libraries: tutorial. dsoergel.com, 2002.

[8] T. R. Gruber, “A translation approach to portable ontology specifications,” Knowl. Acquis., vol. 5, no. 2, pp. 199–220, 1993.

[9] D. Estival, C. Nowak, and A. Zschorn, “Towards ontology-based natural language processing,” in Proceeedings of the Workshop on NLP and XML (NLPXML-2004): RDF/RDFS and OWL in Language Technology, 2004, pp. 59–66.

[10] N. Guarino and P. Giaretta, “Ontologies and Knowledge Bases: Towards a Terminological Clarification,” Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing, pp. 25–32, 1995.

[11] D. E. O’Leary, “Using AI in knowledge management: knowledge bases and ontologies,” Intelligent Systems and their Applications, IEEE, vol. 13, no. 3, pp. 34–39, 1998.

[12] J. Sarraipa, J. Silva, R. Jardim-Goncalves, and A. Monteiro, “MENTOR—A methodology for enterprise reference ontology development,” 4th International IEEE Conference on Intelligent Systems, pp. 6-32 – 6-40, 2008.

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[13] A. Maedche and S. Staab, “Ontology Learning for the Semantic Web,” IEEE Intelligent Systems, vol. 16, no. 2, pp. 72–79, 2001.

[14] J. Psarras, “‘ Envisioning , Supporting and Promoting Future Internet Enterprise Systems Research through Scientific Collaboration ’ EISB Models & Tools Report,” 2009.

[15] N. F. Noy, M. Sintek, S. Decker, M. Crubézy, R. W. Fergerson, and M. A. Musen, “Creating Semantic Web Contents with Protégé-2000,” 2000.

[16] T. Tudorache, C. Nyulas, N. F. Noy, and M. A. Musen, “WebProtégé : A Collaborative Ontology Editor and Knowledge Acquisition Tool for the Web,” vol. 165, pp. 1–11, 2011.

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8 Annexes

8.1 Excerpt of LOM metadata

represented in Alternativa KB Table 14 - LOM metadata

LOM MRSchema

Atributo name (elementNames.xsd)

1. General general

Identificador identifier

Catálogo catalog

Entrada entry

Título title

Idioma language

Descripción description

Palabra Clave keyword

Cobertura coverage

Estructura structure

Nivel de agregación aggregationLevel

2. Ciclo de vida lifeCycle

Versión version

Estado status

Contribución contribute

Tipo role

Entidad entity

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Fecha date

3. Meta-metadatos metaMetadata

Identificador identifier

Catálogo catalog

Entrada entry

Contribución contribute

Tipo role

Entidad entity

Fecha date

Esquema deMetadatos metadataSchema

Idioma language

4. Técnica technical

Formato format

Tamaño size

Localización location

Requisitos requirement

AgregadorOR orComposite

--Tipo type

--Nombre name

--Versión Mínima minimumVersion

--Versión Máxima maximumVersion

Pautas deInstalación installationRemarks

OtrosRequisitos de Plataforma otherPlatformRequirements

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Duración duration

5. Uso educativo educational

Tipo de interactividad interactivityType

Tipo deRecurso Educativo learningResourceType

Nivel de interactividad interactivityLevel

Densidad semántica semanticDensity

Destinatario intendedEndUserRole

Contexto [Nivel educativo] context

Rango Típicode Edad typicalAgeRange

Dificultad difficulty

Tiempo Típico de Aprendizaje typicalLearningTime

Descripción description

Idioma language

6. Derechos rights

Coste cost

Derechos deAutor y otras Restricciones copyrightAndOtherRestrictions

Descripción description

7. Relación [con otros recursos] relation

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Tipo [naturaleza de la relación con el recurso principal] kind

Recurso [recurso principal al que se refiere esta relación] resource

Identificador identifier

--Catálogo catalog

--Entrada entry

--Descripción description

8. Anotación annotation

Entidad entity

Fecha date

Descripción description

9. Clasificación classification

Propósito purpose

RutaTaxonómica taxonPath

Fuente source

Taxón taxon

--Identificador identifier

--Entrada entry

Descripción description

Palabras clave keyword

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8.2 Excerpt of DRD metadata

represented in ALTER-NATIVA KB Table 15 - DRD metadata

DRD type

Atributo

6.1.

Access For All Digital Resource Description

access mode statement

DRD

control flexibility

ISO_AFA_VOCAB

has control flexibility statement

ISO_AFA_VOCAB

control_flexibility_vocabulary = state ( full_keyboard_control, full_mouse_control )

display transformability

( font_size, font_face, foreground_colour, background_colour, cursor_presentation, highlight_presentation, layout, structure_presentation )

has display transformability statement

colour coding ecore:Eboolean

Hazard ISO_AFA_VOCAB

hazard_vocabulary = state ( flashing, sound, olfactory, motion_simulation )

has adaptation

ISO_AFA_VOCAB

has part ISO_AFA_VOC

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91

AB

is adaptation DRD

is display transformability statement of

ISO_AFA_VOCAB

is control flexibility statement of

ISO_AFA_VOCAB

is part of ISO_AFA_VOCAB

adaptation statement

DRD

support tool ISO_AFA_VOCAB

support_tool_vocabulary = state ( dictionary, calculator, note_taking, peer_interaction, abacus, thesaurus, spell_checker, homophone_checker, mind_mapping_software, outline_tool )

6.2. Access Mode Statement

original access mode

ISO_AFA_VOCAB

access_mode_vocabulary = state ( visual, textual, auditory, tactile, olfactory )

access mode usage

ISO_AFA_VOCAB

access_mode_usage_vocabulary = state ( informative, ornamental )

6.4. Adaptation Statement

adaptation type

ISO_AFA_VOCAB

adaptation_type_vocabulary = state ( audio_representation, visual_representation, text_representation, tactile_representation, caption, audio_description, Braille, digital_talking_book, electronic_book )

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original access mode

ISO_AFA_VOCAB

access_mode_vocabulary = state ( visual, textual, auditory, tactile, olfactory )

Extent ISO_AFA_VOCAB

extent_vocabulary = state ( part, all )

representation form

ISO_AFA_VOCAB

representation_form_vocabulary = state ( enhanced, verbatim, real-time, transcript, alternative text, long description, sign language, image-based, symbolic, recorded, synthesized, haptic )

language ISO_AFA_VOCAB

reading rate ecore:Eint

education level

ecore:Estring

6.3. Is Adaptation

is adaptation of

ISO_AFA_VOCAB

Extent ISO_AFA_VOCAB

extent_vocabulary = state ( part, all )

8.3 User model Table 16 - User Model General Profile

A. PERFIL GENERAL Possible values

Pertenece alguna comunidad

Area Matematicas, Ciencias, Lenguaje

Nivel de Estudios alcanzado

Primaria, Secundaria, Tecnica-Tecnológica, Universitaria, Pos-gradual

Nivel de conocimiento en accesibilidad Web Experto, Principiante

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Nivel de conocimiento en tecnologias asistivas Experto, Principiante

Aplicacion de TIC

Capacidad de diferenciar navegadores y de identificar ventajas para el trabajo didáctico

Alta, media, baja

Conocimiento de programas básicos para el trabajo académico:

Alta, media, baja

Conocimiento y capacidad de búsqueda y de comparación y de selección de opciones de procesadores de textos.

Alta, media, baja

Capacidad de acceder en la web a sitios para el trabajo académico

Alta, media, baja

Table 17 - User model access to information preferences

B. Preferencias para el acceso a la información

Dieciseis combinaciones de Felder con su puntuación

Entrada

Verbal [1,11]

Visual [1,11]

Procesamiento

Activo [1,11]

Reflexivo [1,11]

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Entendimiento

Global [1,11]

Secuencial [1,11]

Percepción

Intuitivo [1,11]

Sensitivo [1,11]

Table 18 - User Model ALTER-NATIVA Profile

C. Perfil ALTER-NATIVA Possible values

DESEMPEÑO

Escenarios de desempeño

Ministerios de Educación, Secretarías de educación, Institutos asesores en educación, Universidades, Colegios, Normales, Instituciones no gubernamentales, otro

Participaciones en el escenario de desempeño

Estudiantes en proceos de formación, Funcionarios gubernamentales o no gubernamentales, Formadores de profesores y Funcionarios Directivos, coordinadores o diseñadores de programas o currículos, Dirección, Administración, Coordinación, Planeación, Docencia, Investigación , formación.

Tipo de escenario Gubernamental, no gubernamental

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Nombre del escenario

Cargo que desempeña en el escenario

Ministro, Secretario de educación, Director de departamento, asesor, funcionario, Rector, Vicerector, Decano, Director de programa, coordinador de programa, profesor, estudiante

Tipo de dedicación en el escenario Tiempo completo, medio tiempo, tiempo parcial

ESPECIALIZACIÓN EN EDUCACIÓN

Perfil General

Campo o área de desarrollo profesional en educación

Administrativa, Educación, Tecnología, Educación en ciencias, Educación en lenguaje, Educación en Ciencias

Campo de especialización

Educación , Tecnología, Educación mat, Educación Leng. Educación Ciencias Educación y tecnología, Educación mat y tecnología, Educación Leng y tecnología, Educación Ciencias y tecnología

Nivel de especialización principiante, novato, experto

Manejo de Poblacion diversa Si

En el manejo de escenarios Manejo

Virtuales

Presenciales

Redes digitales

Manejo de recursos tecnologicos en el aula

Alta

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Computador

Pantallas digitales

Video Bin

equipo y software de acceso a la información para discapacidad visual

Experticia en la creación de unidades didácticas

Alta, media, baja

Experticia en la creación de secuencias didácticas Alta, media, baja

Experticia en Creación de Objetos de Aprendizaje Alta, media, baja

Trabajos previos en comunidades de práctica ambientes colaborativos … innovaciones grupales

Si, NO

Conocimiento o interés por conocer herramientas Tic como editores, procesos de diseño de blogs, diseño de páginas web, para el diseño didáctico.

Alta, media, baja

Conocimiento y uso de páginas y sitios web para el trabajo interactivo en educación: con textos, con testimonios, con fotografías y videos, con materiales multimedia.

Alta, media, baja

Ha participado en:

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Proyectos de innovación curricular en el área de (matemáticas, ciencias y leanguaje) Si, NO

Proyectos de innovación curricular en formación de profesores de (matemáticas, ciencias y leanguaje) Si, NO

Proyectos de investigación en el aula en el área de (matemáticas, ciencias y leanguaje)

Si, NO

Proyectos de investigación en el aula en formación de profesores de (matemáticas, ciencias y leanguaje) Si, NO

Proyectos de incorporación de tecnologías digitales en el área de (matemáticas, ciencias y leanguaje) Si, NO

Proyectos de incorporación de tecnologías digitales en formación de profesores de (matemáticas, ciencias y leanguaje) Si, NO

Proyectos relacionados con la inclusión educativa en el área de (matemáticas, ciencias y leanguaje) Si, NO

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Proyectos relacionados con la inclusión educativa en formación de profesores de (matemáticas, ciencias y leanguaje) Si, NO

Grado de conocimiento de:

Las teorías sobre la formación de profesores de (matemáticas, ciencias y lenguaje)

Alta, media, baja

Las bases teóricas de la didáctica de las (matemáticas, ciencias y leanguaje)

Alta, media, baja

Las teorías sobre la incorporación de la tecnología en las aulas de formación de profesores de (matemáticas, ciencias y leanguaje)

Alta, media, baja

Manejo práctico de las TIC Alta, media, baja

Uso educativo de las TIC Alta, media, baja

De las siguientes poblaciones, indique con cual (es) ha tenido experiencia en su trabajo docente:

Ciegos Si, NO

Sordos Si, NO

Población vulnerable económicamente Si, NO

Indígenas en educación multilingüe Si, NO

Indígenas en educación en lengua materna Si, NO

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Ha participado en:

Redes de colaboración docente Si, NO

Redes virtuales de colaboración docente Si, NO

Grupos de trabajo docente y de trabajo académico en general

Si, NO

Grupos de investigación en educación matemática, en el campo de la pedagogía y la didáctica del lenguaje y la comunicación o educación en ciencias)

Si, NO

Trabajo en equipo, en colaboración y producción conjunta de propuestas didácticas

Si, NO

Tiene experiencia en

Elaboración y presentación de ponencias en eventos especializados de (matemática, ciencias o del lenguaje y la comunicación)

Alta, media, baja

Produce artículos y materiales relacionados con la pedagogía y la didáctica de (matemática, ciencias o del lenguaje y la comunicación)

Alta, media, baja

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Elaboración de textos escolares para (matemática, ciencias o lenguaje)

Alta, media, baja

Elaboración de textos para la formación de profesores de (matemática, ciencias o lenguaje)

Alta, media, baja

Su experiencia docente es fundamentalmente con

Escolares de la educación primaria Alta, media, baja

Escolares de la educación secundaria Alta, media, baja

Estudiantes para profesor de (matemática, ciencias o lenguaje) Alta, media, baja

Perfil CAC

El docente de las facultades de ciencia:

Entiende la ciencia como una actividad cultural

SI - NO

Entiende el conocimiento como provisional

SI - NO

Reconoce la importancia de la experimentación

SI - NO

Interpreta modelos de fenómenos complejos

SI - NO

Aplica diversas habilidades del pensamiento

SI - NO

Usa aritmética y álgebra básica SI - NO

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Experticia de un docente en un con dispositivos didáctico Alta, media, baja

Tipos de dispositivos en ciencias diagramas de ciclos, redes de conceptos, diagramas jerárquizados

Experticia de un docente en: Alta, media, baja

Instrumentos para resolver diagramas Alta, media, baja

Reconocimiento de conceptos Alta, media, baja

Reconocimeinto de las relaciones causa-efecto Alta, media, baja

Argumentación Alta, media, baja

Aplicación de modelos Alta, media, baja

Reconstrucción de modelos Alta, media, baja

Aplicación a nuevas situaciones Alta, media, baja

El docente de ciencias reconoce el papel de la ciencia en la sociedad

Alto, medio, bajo

Reconoce las repercusiones de la ciencia en la vida humana

Alto, medio, bajo

Reconoce la importancia de los vínculos con el desarrollo tecnológico

Alto, medio, bajo

Reconoce la importancia de la alfabetización científica de la sociedad

Alto, medio, bajo

Perfil CALE

Epistemología del lenguaje y la comunicación Alto, medio, bajo

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Referentes Curriculares del Lenguaje y Comunicación Alto, medio, bajo

Teorías de la adquisición y el desarrollo de las lenguas en contextos diversos Alto, medio, bajo

Conocimiento de entornos semióticos y comunicativos Alto, medio, bajo

Diversidad, educación y lenguaje Alto, medio, bajo

Enfoques teóricos y políticos de la diversidad Alto, medio, bajo

Poblaciones diversas y acceso educativo en lenguaje. Alto, medio, bajo

Mediaciones para la experiencia del lenguaje Alto, medio, bajo

Dominio de fuentes bibliográficas del área del lenguaje Alto, medio, bajo

Observación de las diferencias en el desarrollo del lenguaje Alto, medio, bajo

Diversidades en el acceso a la lectura Alto, medio, bajo

Dispositivos didácticos y lenguaje Alto, medio, bajo

Fundamentos teóricos y metodológicos de dispositivos didácticos

Alto, medio, bajo

Dispositivos didácticos y desarrollo del lenguaje Alto, medio, bajo

Criterios para seleccionar dispositivos para el desarrollo del lenguaje

Alto, medio, bajo

TIC para el desarrollo de lenguaje Alto, medio, bajo

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Análisis curricular y didáctico para el desarrollo del lenguaje Alto, medio, bajo

Capacidad crítica en el uso de TIC y lenguaje Alto, medio, bajo

Tic y campos estructurantes del área de lenguaje Alto, medio, bajo

Aspectos técnicos, semióticos y culturales de las TIC Alto, medio, bajo

TIC, otras tecnologías y desarrollo del lenguaje en diversidad. Alto, medio, bajo

Perfil CAM

Experiencias curriculares para la formación matemática y didáctica

experiencia= 0-1 años, 2-5, 6 - 10, de 11 en adelantes

Experiencias en la formación de una didáctica de la didáctica de las matemáticas de educadores matemáticas

experiencia= 0-1 años, 2-5, 6 - 10, de 11 en adelantes

Experiencias en ambientes de aprendizaje interculturales y pluritecnológicos en la educación matemáticas.

experiencia= 0-1 años, 2-5, 6 - 10, de 11 en adelantes

Table 19 - User Model Accessibility Profile

D. PERFIL DE ACCESIBILIDAD A TECNOLOGIA DE INTERACCIÓN Y COMUNICACIÓN.

Possible values

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CONDICIÓN SENSORIAL(percepción, (**** operación y comprensión de la información) ****

ATENCIÓN

Rendimiento cognitivo Muy bajo

Bajo

Medio

Alto

Muy alto

Capacidad de Reconocimiento de emociones Si

No

Capacidad para Regular emociones Emociones positivas o neutro

Emociones negativas

Capacidad para manejar la conducta Si

No

Trastorno por deficit de Atención e Hiperactividad (TDAH)

Si TDAH + alteraciones emocionales

Si TDAH

No TDAH

AUDICIÓN

NIVEL DE AUDICIÓN Hipoacusia leve o ligera

Hipoacusia media o moderada

Hipoacusia severa

Hipoacusia profunda o sordera

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Cofosis o anacusia

Momento de perdida de la audición Prelocutivo

Poslocutivo

Manejo de ayudas Auditiva

Si ¿Cúal? • Ninguna • Prótesis auditivas • Sistema de amplificación • Implante coclear

No

Forma de Comunicación Oral

Escrita

Visogestual

Situación de comunicación Bilingüe

Monolingüe

Dominio de una lengua Lengua oral (auditivo vocal

Lengua de señas

Nivel de dominio de dicha lengua (esta pregunta dependerá de la anterior)

Excelente, Bueno, Aceptable, Insuficiente

Dominio de la Lengua Escrita Excelente, Bueno, Aceptable, Insuficiente

acompañamiento de un intérprete de lengua de señas para

• Ninguna situación • Interacciones cara a cara con personas oyentes • La lectura de textos escritos

Miembro de alguna asociación de Sordos • Si • No

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Formación academica Integracion /Inclución

Colegios especialezados para sordos

VISIÓN

Tipo de limitación visual

Parcial **** no reconocemos (INCI) este nivel de limitación, reconocemos Total y baja visión ****

Total

Baja vision

**** con qué fin se hace esta clasificación? **** Congénita

**** con qué fin se hace esta clasificación? **** Adquirida

**** con qué fin se hace esta clasificación? **** Súbita

**** con qué fin se hace esta clasificación? **** Gradual

Manejo de ayuda Visuales Si ¿Cuál?

No

Mediaciones en el aprendizaje Braille

Abaco

Lector de pantalla ¿Cuál?

Calculadoras parlantes

Sistemas de

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reconocimiento de textos en tinta

Uso de libros hablados

textos convertidos en audio con voz artificial (sintetizada)

Móviles adaptados con lector de pantalla

insuficiencia motora de origen cerebral

Tipo de limitación Hemiplejía

Paraplejía

Cuadriplejía

Hipotonía

Grado de la disfunción Espastica

Atetosica

Ataxica

Momento en que se presenta la limitación Congénita

Adquirida

Manejo de ayudas Auditiva Si ¿Cúal?

No

CONDICIÓN LINGÜÍSTICA

Primera Lengua (L1) Español

Quechua

Aymara

Miskito

Zapoteco

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Mixteco

Lengua de Señas Colombiana

Lengua de Señas Méxicana

Lengua de Señas Nicaraguence

Segunda Lengua (L2) Español

Castellano Escrito

Quechua

Aymara

Miskito

Zapoteco

Mixteco

Nivel de conocimiento del Español Marco Europeo de clasificación

Nivel de conocimiento de la Primera Lengua (L1) Marco Europeo de clasificación

Otras lenguas Marco Europeo de clasificación

CONDICIÓN SOCIO-ECONOMICA

Fuentes de Ingreso Formal e Informal

Situación económica Pobreza y Pobreza Extrema

Table 20 - User Model access preferences

E. PREFERENCIAS DE ACCESO

Possible values

Text Settings

font face Serif, Sans Serif, Monospaced, Cursive, Fantasy

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font size (1.5X) , (2X), (2.5X), (3X)

foreground color Blanco, Negro, Rojo, Amarillo, Azul, Verde, Gris, Gris claro, Gris Oscuro, Rosa, Cyan, Magenta

background color Blanco, Negro, Rojo, Amarillo, Azul, Verde, Gris, Gris claro, Gris Oscuro, Rosa, Cyan, Magenta

highlight color Blanco, Negro, Rojo, Amarillo, Azul, Verde, Gris, Gris claro, Gris Oscuro, Rosa, Cyan, Magenta

Alternativas al contenido

Alternatives to text

use alternative to text yes, no

preferred alternative Audio, Visual, Sign Language

append to replace original content

Append, Replace

preferred language English - English, Spanish - Español

Alternatives to audio

use alternative to audio yes, no

preferred alternative Text, Visual, Sign Language

append to replace original content

Append, Replace

preferred language English - English, Spanish - Español

Alternatives to visual

use alternative to visual yes, no

preferred alternative Text, Audio, Sign Language

append to replace original content

Append, Replace

preferred language English - English, Spanish - Español

Ayudas al estudiante

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Learner tools

Learner tools Dictionary, Thesauros, Encyclopedia, Atlas, Note, Taking, Calculator, Abacus

Navigations

Show page Table of Contents yes, no

Show Next/Previous Navigation Buttons

yes, no

Show Breadcrumb Link Navigation

yes, no

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8.4 Wiki Tree of Mathematics Thesaurus

[−] Matemáticas

[−] Cantidad [−] Conceptos numéricos

[×] Funciones [×] Relaciones [×] Sistema de numeración [×] Sistemas numéricos [×] Sucesiones y series numéricas [×] Variable numérica

[−] Habilidades numéricas [×] Cálculo numérico [×] Estimación numérica [×] Identificación de patrones numéricos [×] Manejo de información numérica [×] Modelación numérica/algebraica

[−] Instrumentos para el aprendizaje numérico [×] Artefactos artísticos y de uso social [×] Calendarios [×] Juegos para el pensamiento numérico [×] Software para el pensamiento numérico [×] Ábaco

[−] Procesos numéricos [×] Aproximar numéricamente [×] Clasificar [×] Contar [×] Formulación y solución de ecuaciones [×] Operar [×] Ordenar

[−] Forma [−] Concepto geométrico

[×] Elementos y objetos de las geometrías [×] Espacios geométricos [×] Geometrías

[−] Habilidades geométricas [×] Diseñar geométricamente [×] Localización espacial [×] Orientación espacial

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[×] Uso de instrumentos para hacer geometría y razonar geométricamente [×] Visualización geométrica

[−] Instrumentos para el aprendizaje geométrico [×] Herramientas de trazo y construcción [×] Juego de geometría [×] Rompecabezas [×] Software para la geometría

[−] Procesos geométricos [×] Construir y trazar geométricamente [×] Operar geométricamente [×] Representación geométrica [×] Transformar geométricamente

[−] Magnitud [−] Conceptos relativos a la magnitud

[×] Magnitudes [×] Sistemas de unidades de medida [×] Unidades de medida no convencionales [×] Unidades de medidas convencionales

[−] Habilidades para la medición [×] Aplicación de algoritmos y fórmulas métricas [×] Componer y descomponer en la medición [×] Deducir fórmulas [×] Estimación de medidas [×] Relacionar magnitudes [×] Uso de instrumentos

[−] Instrumentos para el aprendizaje de la medición [×] Instrumentos de medición [×] Objetos informales para medir [×] Recipientes [×] Retículas

[−] Proceso de la medición [×] Comparación de magnitudes [×] Conversión de unidades [×] Medir [×] Operar con unidades de sistemas de unidades de

medidas [−] Procesos matemáticos transversales

[−] Jugar [×] Instrumentos de los juegos [×] Las reglas de los juegos

[−] Modelar

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[×] Construcción de modelos [×] Identificación de patrones [×] Predicción [×] Sistemas cotidianos y fenómenos físicos

[−] Razonar [×] Argumentar [×] Conjeturar [×] Probar y demonstar [×] Razonamientos abductivos [×] Razonamientos deductivos [×] Razonamientos inductivos

[−] Representar [×] Conversión de representaciones [×] Instrumentos para las representaciones [×] Sistemas de representación [×] Tratamiento de representaciones

[−] Resolver problemas [×] Estrategias para representar problemas [×] Estrategias para resolver problemas [×] Problemas y tipos

[×] Tecnologías y solución de problemas

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8.5 Wiki Tree of Literature Thesaurus

[−] Lenguaje [−] Dimensiones de análisis del lenguaje [×] Dimensión afectiva [×] Dimensión cognitiva [×] Dimensión social [−] Experiencia discursiva [−] Escriturabilidad y lecturabilidad [−] Aprendizaje de la escritura [−] Escritura alfabética [×] Procesos cognitivos de la escritura [×] Procesos perceptuales del signo escrito [−] Procesos socioculturales de la escritura [×] Diversidad textual/Géneros de la escritura [−] Aprendizaje de otros sistemas de representación gráfica [−] Sistemas no verbales [−] Sistemas autónomos [×] Icónicos [×] Simbólicos [×] Sistemas de signos paralingüísticos [−] Experiencia Narrativa [−] Género Discursivo [−] Formas Textuales [×] Macroestructura narrativa [×] Microestructura [×] Superestructura narrativa [−] Géneros por esfera social [×] Género artístico [×] Género científico [−] Hecho estético [−] Expresión estética [−] Forma y contenido [−] Literatura [×] Metonimia Sinécdoque [×] Metáfora Símil [×] Música [×] Pintura [−] Pensamiento narrativo [−] Narratividad [−] Acción narrativa

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[×] Actores personajes [×] Organización espacio/temporal [×] Conciencia narrativa [−] Oralidad/Lenguas orales y de señas [−] Procesos de apropiación lingüística [−] Adquisición de la lengua oral y de señas [×] Escuchar [×] Funciones del lenguaje [×] Hablar/Señar [×] Procesos cognitivos de la oralidad [×] Procesos de percepción oral y visogestual [×] Procesos metacognitivos [−] Desarrollo de las lenguas [−] Pragmática de las lenguas [−] Prácticas discursivas y situación social [×] Contextos de uso [−] Semiótica de las lenguas [×] Bilinguismo en la población sorda [×] Bilingüismo en la población indígena [×] L1 L2 L3 ... [×] Monolingüismo [×] Plurilingüismo [×] Silabario [×] Sistemas Braille

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8.6 Wiki Tree of Teaching Thesaurus

[−] Didáticas

[−] Conceptos didáticos [×] Contrato didáctico [×] Didáctica general y específica [×] Disopsitivos didácticos [×] Dispositivos didácticos [×] Secuencias didácticas [×] Situaciones didácticas [×] Unidades didácticas

[−] Habilidades didáticas [×] Reconocimiento de trayectorias de aprendizaje en estudiantes [×] Reflexión didáctica [×] Uso de recursos de aprendizaje de los estudiantes [×] Valoración de procesos de estudiantes

[−] Intrumentos didáticos [×] Ambientes de aprendizaje [×] Objetos virtuales de aprendizaje [×] Tecnologías de la Información y la comunicació TIC [×] Tecnológias ancestrales

[−] Procesos didáticos [×] Aprender [×] Diseñar dispositivos didáctico [×] Enseñar [×] Evaluar dispositivos didácticos [×] Gestionar dispositivos didácticos

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8.7 Wiki Tree of Science Thesaurus

[−] Ciencias

[−] Ambiente [−] Interacciones

[×] Interacciones ambientales [−] Interacciones físico

[−] Fuerza [×] Fuerza de gravedad [×] Fuerza de roce [−] Fuerza normal

[×] Massa [×] Fuerza Tensión

[×] Movimento [×] Seres inanimados [×] Seres muertos [−] Seres vivos

[−] Funciones Vitales [×] Alimentación [×] Crecimiento [×] Nutrición [×] Reproducción [×] Respiración

[−] Sistemas Vitales [×] Sistema Circulatorio [×] Sistema Digestivo [×] Sistema reproductor

[−] Cambio químico [−] Reacciones químicas

[−] Cambio de color [−] Ecuación química

[−] Moléculas [−] Colisiones

[×] Cinética química [−] Átomos

[×] Enlaces químicos [×] Formación de precipitados

[−] Sustancias químicas [×] Intercambio de calor [×] Producción de gases [−] Propiedades químicas