Description logics with aggregates and concrete domains
Information Systems
SBI: a semantic framework to support business intelligence
OBI '08 Proceedings of the first international workshop on Ontology-supported business intelligence
Aggregate queries over ontologies
Proceedings of the 2nd international workshop on Ontologies and information systems for the semantic web
Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses
Information Sciences: an International Journal
Ontologies and summarizability in OLAP
Proceedings of the 2010 ACM Symposium on Applied Computing
A framework for multidimensional design of data warehouses from ontologies
Data & Knowledge Engineering
A methodology and tool for conceptual designing a data warehouse from ontology-based sources
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
FedDW global schema architect: UML-based design tool for the integration of data mart schemas
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
Towards ontology-based OLAP: datalog-based reasoning over multidimensional ontologies
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
Multi-dimensional navigation modeling using BI analysis graphs
ER'12 Proceedings of the 2012 international conference on Advances in Conceptual Modeling
Business model ontologies in OLAP cubes
CAiSE'13 Proceedings of the 25th international conference on Advanced Information Systems Engineering
APCCM '13 Proceedings of the Ninth Asia-Pacific Conference on Conceptual Modelling - Volume 143
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Business analysts frequently use Cockpits or Dashboards as front ends to data warehouses for inspecting and comparing multidimensional data at various levels of detail. These tools, however, perform badly in supporting a business analyst in his or her business intelligence task of understanding and evaluating a business within its environmental context through comparative data analysis. With important business knowledge either unrepresented or represented in a form not processable by automatic reasoning, the analyst is limited in the analyses that can be formulated and she or he heavily suffers from information overload with the need to re-judge similar situations again and again, and to re-discriminate between already explained and novel relationships between data. In an ongoing research project we try to overcome these limitations by applying and extending semantic technologies, such as ontologies and business rules, for comparative data analysis. The resulting Semantic Cockpit assists and guides the business analyst due to reasoning about various kinds of knowledge, explicitly represented by machine-processable ontologies, such as organisation-internal knowledge, organisation external domain knowledge, the semantics of measures and scores, knowledge about insights gained from previous analysis, and knowledge about how to act upon unusually low or high comparison scores. This paper outlines the architecture of the Semantic Cockpit and introduces its core ideas by a sample use case.