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SemCockpit - An Ontology-Driven, Interactive Business Intelligence Tool for Comparative Data Analysis

Project duration: January 2011 - February 2014
Project website: http://www.solvistas.com/de/fe/semcockpit/semcockpit/
Funded by: Bundesministerium für Verkehr, Innovation und Technologie (FFG - FIT-IT)
Project number: FFG-829594
Short description: 

Business intelligence (BI) tools support interactive reporting over the corporate data warehouse through online analytical processing (OLAP). Cockpits or dashboards are used as visual front-ends for inspecting and comparing multi-dimensional data at various levels of detail. These tools, however, perform badly in supporting the business intelligence task of understanding and evaluating a business within its environmental context through comparative data analysis. With the exact meaning of data in reports being buried in application code or SQL queries it is difficult to compare data across different reports. With comparative data analysis mainly supported by visual diagram inspection it is difficult to comprehend and reproduce previous findings. Further, business analysts heavily suffer 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 semCockpit, a multi-dimensional ontology (MDO) provides an unambiguous definition of business terms (also referred to as defined concepts) for the specific needs of OLAP. These concepts can be used in queries, making it easier to formulate, understand, and maintain very complex multi-dimensional queries and to interpret, compare, and share analysis results. The organization and maintenance of large repositories of business terms is facilitated by deriving subsumption hierarchies of concepts and organizing them along dimension hierarchies and cubes. Further, existing domain ontologies can be re-used for OLAP as semantic dimensions. Ontology-based measures use business terms to specify the data to be included in the calculation of derived measures.

In semCockpit, scores capture the results of comparisons explicitly and free the business analyst from visual comparison by diagram inspection. A comparative fact relates two groups of data, a group of interest and a group of comparison, and quantifies the result of the comparison by a score. Comparative facts are collected into comparative cubes, which can be interactively navigated similar to traditional OLAP cubes.

In semCockpit, judgement rules are defined over facts of a comparative cube and represent knowledge about possible explanations of a striking low or high score. This avoids the need to re-judge similar situations again and again. Judgement rules are organized in specialization hierarchies to allow for context-specific judgements.

The semCockpit approach is implemented by a proof-of-concept prototype on top of an off-the-shelf database management system and an OWL reasoner. Employing a model-driven approach, MDO constructs are automatically transformed to SQL views over the underlying data warehouse. Reasoning over multi-dimensional ontologies is implemented by an automatic transformation of MDO concepts to the web ontology language OWL and by delegating reasoning tasks to the OWL reasoner. The semCockpit approach was applied to a sample simplified showcase from prospective customers from health insurance industry.

Project partners: 
Project team: 
Michael Schrefl - Scientific Lead (DKE)
Bernd Neumayr - Senior Researcher, Project Management (DKE)
Stefan Anderlik - Junior Researcher (DKE)
Stefan Berger - Senior Researcher (DKE)
Christoph Schütz - Junior Researcher (DKE)
Arjol Qeleshi - Junior Researcher (DKE)
Christoph Ellinger - Junior Researcher (DKE)
Dieter Steiner - Junior Researcher (DKE)
Publications: 
B. Neumayr, M. Schrefl, K. Linner:
Semantic Cockpit: An Ontology-Driven, Interactive Business Intelligence Tool for Comparative Data Analysis
In: ER 2011 Workshop-Proceedings: Advances in Conceptual Modeling - Recent Developments and New Directions, Olga De Troyer, Claudia Bauzer Medeiros, Roland Billen, Pierre Hallot, Alkis Simitsis, Hans Van Mingroot (Eds.), First International Workshop on Modeling and Reasoning for Business Intelligence (MoRE-BI 2011), Springer Verlag, Lecture Notes in Computer Science (LNCS), Vol. 6999, ISBN 978-3-642-24573-2, pp. 55-64, 2011.
S. Anderlik, B. Neumayr, M. Schrefl:
Using Domain Ontologies as Semantic Dimensions in Data Warehouses
In: Paolo Atzeni, David W. Cheung, Sudha Ram (Eds.): Proceedings of the 31st International Conference on Conceptual Modeling (ER 2012), Florence, Italy, October 15-18, Springer Verlag, Lecture Notes in Computer Science (LNCS Vol. 7532), ISBN 978-3-642-34001-7, pp. 88-101, 2012.
T. Neuböck, B. Neumayr, T. Rossgatterer, S. Anderlik, M. Schrefl:
Multi-dimensional Navigation Modeling using BI Analysis Graphs
In: Silvana Castano, Panos Vassiliadis, Laks V. Lakshmanan, Mong-Li Lee (Eds.): Advances in Conceptual Modeling - Proceedings ER 2012 Workshops CMS, ECDM-NoCoDA, MoDIC, MORE-BI, RIGiM, SeCoGIS, WISM; Workshop on Modeling and Reasoning for Business Intelligence (MORE-BI 2012), Florence, Italy, October 15, Springer Verlag, Lecture Notes in Computer Science (LNCS Vol. 7518), ISBN 978-3-642-33998-1, pp. 162-171, 2012.
B. Neumayr, S. Anderlik, M. Schrefl:
Towards Ontology-based OLAP: Datalog-based Reasoning over Multidimensional Ontologies
In: Il-Yeol Song, Matteo Golfarelli (Eds.): Proceedings of the ACM 15th International Workshop on Data Warehousing and OLAP (DOLAP 2012), Maui, Hawaii, U.S.A., November 2nd, 2012, ACM Press, ISBN 978-1-4503-1721-4, pp. 41-48, 2012.
B. Neumayr, C. Schütz, M. Schrefl:
Semantic Enrichment of OLAP Cubes: Multi-dimensional Ontologies and their Representation in SQL and OWL
In: On the Move to Meaningful Internet Systems, OTM 2013 Conferences, Proceedings of the 12th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2013), Graz, Austria, September 10-12, 2013, Pieter De Leenheer, Deijing Dou (eds.), Springer Verlag, Lecture Notes in Computer Science (LNCS Vol. 8185), ISBN 978-3-642-41032-1, pp. 624-641, 2013.
M. Schrefl, B. Neumayr, M. Stumptner:
The Decision-Scope Approach to Specialization of Business Rules: Application in Business Process Modeling and Data Warehousing
In: Proceedings of the Ninth Asia-Pacific Conference on Conceptual Modelling (APCCM 2013), January 29 - February 1, 2013, Adelaide, South Australia, Conferences in Research and Practice in Information Technology, CRPIT, Vol. 143. Eds.: Flavio Ferrarotti and Georg Grossmann, pp. 3-18, 2013.
C. Schütz, B. Neumayr, M. Schrefl:
Business Model Ontologies in OLAP Cubes
In: Proceedings of the 25th International Conference on Advanced Information Systems Engineering (CAiSE 2013), Valencia, Spain, June 17-21, 2013, Camille Salinesi et al. (editors), Springer Verlag, Lecture Notes in Computer Science (LNCS Vol. 7908), ISBN 978-3642387081, pp. 514-529, 2013.
T. Neuböck, B. Neumayr, M. Schrefl, C. Schütz:
Ontology-driven Business Intelligence for Comparative Data Analysis
In: Business Intelligence - Proceedings of the Third European Business Intelligence Summer School (eBISS 2013), Schloss Dagstuhl, Wadern, Germany, July 7-12, 2013, Springer Verlag, Lecture Notes in Business Information Processing (LNBIP Vol. 172), Chapter 3, ISBN 978-3-319-05460-5, pp. 77-120, 2014.
D. Steiner, B. Neumayr, M. Schrefl:
Judgement and Analysis Rules for Ontology-driven Comparative Data Analysis in Data Warehouses
In: Proceedings of the Eleventh Asia-Pacific Conference on Conceptual Modelling (APCCM 2015), January 27-30, 2015, Sydney, Australia, Conferences in Research and Practice in Information Technology, CRPIT, Vol. 165. Eds.: Henning Köhler and Motoshi Saeki, pp. 71-80, 2015.
Downloads
  • Datalog program implementing example for: Thomas Neuböck, Bernd Neumayr, Thomas Rossgatterer, Stefan Anderlik, and Michael Schrefl: Multi-dimensional Navigation Modeling using BI Analysis Graphs.
  • Extended sample MDO and Datalog program for: Bernd Neumayr, Stefan Anderlik, and Michael Schrefl: Towards Ontology-based OLAP: Datalog-based Reasoning over Multidimensional Ontologies.