Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings |
| Subtitle of host publication | 3rd IEEE International Conference on Advanced Learning Technologies, ICALT 2003 |
| Pages | 493 |
| Number of pages | 1 |
| Publication status | Published - 28 Jul 2003 |
| Event | 3rd IEEE International Conference on Advanced Learning Technologies (ICALT 2003) - Athens, Greece Duration: 9 Jul 2003 → 11 Jul 2003 Conference number: 3 |
Publication series
| Name | Proceedings - 3rd IEEE International Conference on Advanced Learning Technologies, ICALT 2003 |
|---|
Abstract
Learning object metadata aims at describing educational resources in order to allow better reusability and retrieval. Unfortunately, annotating complete courses thoroughly with LOM metadata can be a tedious task. We show how additional inference rules can make this task easier, and allow us to derive additional metadata from existing ones. Additionally, using these rules as integrity constraints helps us to define the constraints on LOM fields, thus taking an important step towards a complete axiomatization of LOM metadata (with the goal of transforming the LOM definitions from a simple syntactical description into a complete ontology). We used RDF metadata descriptions and an inference language explicitly developed for RDF (TRIPLE) to represent metadata and axioms. We show how these rules can be applied for the extensions of course metadata, the creation of views onto the metadata or metadata consistency checking.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Social Sciences(all)
- Education
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Proceedings: 3rd IEEE International Conference on Advanced Learning Technologies, ICALT 2003. 2003. p. 493 1215216 (Proceedings - 3rd IEEE International Conference on Advanced Learning Technologies, ICALT 2003).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Completing LOM-how additional axioms increase the utility of learning object metadata
AU - Brase, Jan
AU - Painter, Mark
AU - Nejdl, Wolfgang
N1 - Conference code: 3
PY - 2003/7/28
Y1 - 2003/7/28
N2 - Learning object metadata aims at describing educational resources in order to allow better reusability and retrieval. Unfortunately, annotating complete courses thoroughly with LOM metadata can be a tedious task. We show how additional inference rules can make this task easier, and allow us to derive additional metadata from existing ones. Additionally, using these rules as integrity constraints helps us to define the constraints on LOM fields, thus taking an important step towards a complete axiomatization of LOM metadata (with the goal of transforming the LOM definitions from a simple syntactical description into a complete ontology). We used RDF metadata descriptions and an inference language explicitly developed for RDF (TRIPLE) to represent metadata and axioms. We show how these rules can be applied for the extensions of course metadata, the creation of views onto the metadata or metadata consistency checking.
AB - Learning object metadata aims at describing educational resources in order to allow better reusability and retrieval. Unfortunately, annotating complete courses thoroughly with LOM metadata can be a tedious task. We show how additional inference rules can make this task easier, and allow us to derive additional metadata from existing ones. Additionally, using these rules as integrity constraints helps us to define the constraints on LOM fields, thus taking an important step towards a complete axiomatization of LOM metadata (with the goal of transforming the LOM definitions from a simple syntactical description into a complete ontology). We used RDF metadata descriptions and an inference language explicitly developed for RDF (TRIPLE) to represent metadata and axioms. We show how these rules can be applied for the extensions of course metadata, the creation of views onto the metadata or metadata consistency checking.
UR - http://www.scopus.com/inward/record.url?scp=33646543476&partnerID=8YFLogxK
U2 - 10.1109/ICALT.2003.1215216
DO - 10.1109/ICALT.2003.1215216
M3 - Conference contribution
AN - SCOPUS:33646543476
SN - 0769519679
T3 - Proceedings - 3rd IEEE International Conference on Advanced Learning Technologies, ICALT 2003
SP - 493
BT - Proceedings
T2 - 3rd IEEE International Conference on Advanced Learning Technologies (ICALT 2003)
Y2 - 9 July 2003 through 11 July 2003
ER -