Digital Multimedia Repositories Ontology (DMRO)

, Last updated by lawrynowicz, on Sun, 11/20/2011 - 10:36


DMRO download page


1 Purpose.

The aim is to make the ontology in a way to be useful for internal e-LICO platform experiments, and in the further step also for the use in tasks of general interest, such as the task of the second e-LICO open challenge. In this way, our goal is to exploit the Digital Multimedia Repositories Ontology (DMRO) for providing semantic annotations of the test dataset(s) (in particular dataset to be provided for the second e-LICO open challenge) for the tasks of:

a) design of recommendation, and personalization solutions for digital multimedia repositories,

b) meta-learning/meta-mining on the DMER (Data Mining Experiments Repository),

c) testing semantic data mining algorithms.

2 Scope.

The ontology focus is to be on the applications in recommender systems, personalization, and adaptive faceted browsers of digital resources. Being oriented towards the above applications, the ontology being built is an application domain ontology. Thus, we envisage re-using terms from relevant domain ontologies that cover the domain of DMR ontology. The specific coverage is specified by the competency questions and terms identified. Level of ontology development will be assessed according to the nature of the use-cases to be presented as the proof of concept. The domain ontology (DMRO) must cover all the most relevant concepts of the selected domain and concepts related to e-LICO tasks in more detail.

3 Implementation language.

The ontology is to be developed in Web Ontology Language (OWL).

4 Intended End-Users.

We have identified the following intended end-users of DMRO:

User 1. Web browser user searching for multimedia content

User 2. Multimedia providers

User 3. Web site administrator

User 4. Data-miners

5 Intended Use Cases.

Use 1. Video lecture recommendation.

Use 2. Dynamic adaptation of a faceted browser interface.

Use 3. Personalizing faceted browser interface.

Use 4. Testing semantic frequent pattern discovery algorithms in the context of recommendation and personalization application scenarios (e.g. semantically described frequent clickstreams, semantic features of videos frequently watched together).

Use 5. Testing semantic subgroup discovery algorithms.


6. Reusing Ontology Statements

From the analysis of the competency questions on ontologies relevant for our domain and application it follows that:

Dublin Core - can be reused for modeling general metadata properties of Resources,

FOAF - for modeling the users, authors, participants, their personal data, and social aspects,

RDF Review - vocabulary for the annotations, reviews and marks,

SWRC ontology - for Events,

OBO Relation Ontology - for standard relations.