Learning Object Metadata
INTRODUCTION NEW!!!!
Metadata means information about data. In this case, I'm going to introduce the term metadata and the way they operate. Metadata are really important because they give the oportunity of keeping the information about learning contents in places similar to virtual lybraries where you can get into them and get the necessary object for your educational objective. You can also "give" your own contents in such a way someone can re-use them by requesting the object to the lybrarian that is a repository. In tis article, LOM gives structure, especs and values of the metadata in a general sense.
1. Overview.
1.1 Scope
This Standard is a multi-part standard that specifies Learning Object Metadata. This Part specifies a conceptual data schema that defines the structure of a metadata instance for a learning object. For this Standard, a learning object is defined as any entity -digital or non-digital- that may be used for learning, education or training.
For this Standard, a metadata instance for a learning object describes relevant characteristics of the learning object to which it applies. Such characteristics may be grouped in general, life cycle, meta-metadata, educational, technical, educational, rights, relation, annotation, and classification categories.
The conceptual data schema specified in this part permits linguistic diversity of both learning objects and the metadata instances that describe them.
This conceptual data schema specifies the data elements which compose a metadata instance for a learning object.
This Part is intended to be referenced by other standards that define the implementation descriptions of the data schema so that a metadata instance for a learning object can be used by a learning technology system to manage, locate, evaluate or exchange learning objects.
This Part of this Standard does not define how a learning technology system represents or uses a metadata instance for a learning object.
This Standard is a multi-part standard that specifies Learning Object Metadata. This Part specifies a conceptual data schema that defines the structure of a metadata instance for a learning object. For this Standard, a learning object is defined as any entity -digital or non-digital- that may be used for learning, education or training.
For this Standard, a metadata instance for a learning object describes relevant characteristics of the learning object to which it applies. Such characteristics may be grouped in general, life cycle, meta-metadata, educational, technical, educational, rights, relation, annotation, and classification categories.
The conceptual data schema specified in this part permits linguistic diversity of both learning objects and the metadata instances that describe them.
This conceptual data schema specifies the data elements which compose a metadata instance for a learning object.
This Part is intended to be referenced by other standards that define the implementation descriptions of the data schema so that a metadata instance for a learning object can be used by a learning technology system to manage, locate, evaluate or exchange learning objects.
This Part of this Standard does not define how a learning technology system represents or uses a metadata instance for a learning object.
1.2 Purpose
The purpose of this multi-part Standard is to facilitate search, evaluation, acquisition, and use of learning objects, for instance by learners or instructors or automated software processes. This multi-part Standard also facilitates the sharing and exchange of learning objects, by enabling the development of catalogs and inventories while taking into account the diversity of cultural and lingual contexts in which the learning objects and their metadata are reused.
By specifying a common conceptual data schema, this Part of this Standard ensures that bindings of Learning Object Metadata have a high degree of semantic interoperability. As a result, transformations between bindings will be
straightforward.
This Part of this Standard specifies a base schema, which may be extended as practice develops, e.g., facilitating automatic, adaptive scheduling of learning objects by software agents.
The purpose of this multi-part Standard is to facilitate search, evaluation, acquisition, and use of learning objects, for instance by learners or instructors or automated software processes. This multi-part Standard also facilitates the sharing and exchange of learning objects, by enabling the development of catalogs and inventories while taking into account the diversity of cultural and lingual contexts in which the learning objects and their metadata are reused.
By specifying a common conceptual data schema, this Part of this Standard ensures that bindings of Learning Object Metadata have a high degree of semantic interoperability. As a result, transformations between bindings will be
straightforward.
This Part of this Standard specifies a base schema, which may be extended as practice develops, e.g., facilitating automatic, adaptive scheduling of learning objects by software agents.
2. Overview of the Metadata Structure
2.1 Basic metadata structure
Data elements describe a learning object and are grouped into categories. The LOMv1.0 Base Schema (clause 6) consists of nine such categories:
a) The General category groups the general information that describes the learning object as a whole.
b) The Lifecycle category groups the features related to the history and current state of this learning object and those who have affected this learning object during its evolution.
c) The Meta-Metadata category groups information about the metadata instance itself (rather than the learning object that the metadata instance describes).
d) The Technical category groups the technical requirements and technical characteristics of the learning object.
e) The Educational category groups the educational and pedagogic characteristics of the learning object.
f) The Rights category groups the intellectual property rights and conditions of use for the learning object.
g) The Relation category groups features that define the relationship between the learning object and other related learning objects.
h) The Annotation category provides comments on the educational use of the learning object and provides information on when and by whom the comments were created.
i) The Classification category describes this learning object in relation to a particular classification system.
2.1 Basic metadata structure
Data elements describe a learning object and are grouped into categories. The LOMv1.0 Base Schema (clause 6) consists of nine such categories:
a) The General category groups the general information that describes the learning object as a whole.
b) The Lifecycle category groups the features related to the history and current state of this learning object and those who have affected this learning object during its evolution.
c) The Meta-Metadata category groups information about the metadata instance itself (rather than the learning object that the metadata instance describes).
d) The Technical category groups the technical requirements and technical characteristics of the learning object.
e) The Educational category groups the educational and pedagogic characteristics of the learning object.
f) The Rights category groups the intellectual property rights and conditions of use for the learning object.
g) The Relation category groups features that define the relationship between the learning object and other related learning objects.
h) The Annotation category provides comments on the educational use of the learning object and provides information on when and by whom the comments were created.
i) The Classification category describes this learning object in relation to a particular classification system.
Collectively, these categories form the LOMv1.0 Base Schema. The Classification category may be used to provide certain types of extensions to the LOMv1.0 Base Schema, as any classification system can be referenced.
2.2 Data elements
Categories group data elements. The LOM data model is a hierarchy of data elements, including aggregate data elements and simple data elements (leaf nodes of the hierarchy). In the LOMv1.0 Base Schema, only leaf nodes have individual values defined through their associated value space and datatype. Aggregates in the LOMv1.0 Base Schema do not have individual values. Consequently, they have no value space or datatype. For each data element, the
LOMv1.0 Base Schema defines:
· name: the name by which the data element is referenced;
· explanation: the definition of the data element;
· size: the number of values allowed;
· order: whether the order of the values is significant;
Categories group data elements. The LOM data model is a hierarchy of data elements, including aggregate data elements and simple data elements (leaf nodes of the hierarchy). In the LOMv1.0 Base Schema, only leaf nodes have individual values defined through their associated value space and datatype. Aggregates in the LOMv1.0 Base Schema do not have individual values. Consequently, they have no value space or datatype. For each data element, the
LOMv1.0 Base Schema defines:
· name: the name by which the data element is referenced;
· explanation: the definition of the data element;
· size: the number of values allowed;
· order: whether the order of the values is significant;
2.3 List values
In some instances, a data element contains a list of values, rather than a single value. This list is of one of the following kinds:
· ordered: the order of the values in the list is significant. For example, in a list of authors of a publication, the first author is often considered the more important one. As another example, in a hierarchical classification structure, the order is from more general to more specific.
· unordered: the order of the values in the list bears no meaning. For example, if the description of a simulation includes three short texts that describe the intended educational use in three different languages, then the order of these texts is not significant. They may appear in any order without loss of information. If an aggregate data element contains a list of values, then each of these values shall be a tuple of component elements.
In some instances, a data element contains a list of values, rather than a single value. This list is of one of the following kinds:
· ordered: the order of the values in the list is significant. For example, in a list of authors of a publication, the first author is often considered the more important one. As another example, in a hierarchical classification structure, the order is from more general to more specific.
· unordered: the order of the values in the list bears no meaning. For example, if the description of a simulation includes three short texts that describe the intended educational use in three different languages, then the order of these texts is not significant. They may appear in any order without loss of information. If an aggregate data element contains a list of values, then each of these values shall be a tuple of component elements.
Antonio, veo que llevamos el blog con bastante contenido, además en bilingüe. Si es que tenemos un nivel... :-)
ResponderEliminarSeguimos pendientes de las actualizaciones.
Ángeles y Toni