Authors:
Matthias Frank
1
and
Stefan Zander
2
Affiliations:
1
FZI Research Center for Information Technology, Germany
;
2
Hochschule Darmstadt, Germany
Keyword(s):
Linked Open Data, Semantic Web, Wiki Systems, Knowledge Engineering.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Enterprise Ontology
;
Information Systems Analysis and Specification
;
Knowledge Acquisition
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
One of the main driving forces for the integration of Semantic Media Wiki systems in corporate contexts
is their query construction capabilities on top of organization-specific vocabularies together with the possibility
to directly embed query results in wiki pages. However, exploiting knowledge from external sources
like other organizational knowledge bases or Linked Open Data as well as sharing knowledge in a meaningful
way is difficult due to the lack of a common and shared schema definition. In this paper, we introduce
Linked Data Wiki (LD-Wiki), an approach that combines the power of Linked Open Vocabularies and Data
with established organizational semantic wiki systems for knowledge management. It supports suggestions
for annotations from Linked Open Data sources for organizational knowledge bases in order to enrich them
with background information from Linked Open Data. The inclusion of potentially uncertain, incomplete,
inconsistent or redundant Linked Open Data with
in an organization’s knowledge base poses the challenge of
interpreting such data correctly within the respective context. In our approach, we evaluate data provenance
information in order to handle data from heterogeneous internal and external sources adequately and provide
data consumers with the latest and best evaluated information according to a ranking system.
(More)