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Supporting business intelligence by providing ontology-based end-user information self-service

Published: 27 October 2008 Publication History

Abstract

Business users need to analyse changing sets of information to effectively support their working tasks. Due to the complexity of enterprise systems and available tools, especially technically unskilled users face considerable challenges when trying to flexibly retrieve needed data in an ad-hoc manner. As a consequence, available data is limited to information artefacts like queries or reports which have been predefined for them by IT experts. To improve information self-service capabilities of business users, we present an ontology-based architecture and end-user tool, enabling easy data access and query creation for business users. Our approach is based on a semantic middleware integrating data from heterogeneous information systems and providing a comprehensible data model in the form of a business level ontology (BO). We show how our end-user tool Semantic Query Designer (SQD) enables convenient navigation and query building upon the BO, and illustrate its usage and the processing of data over all layers of our system architecture in detail, using a comprehensible use case example. As flexible query creation is a crucial precondition of leveraging the usage of enterprise data, we contribute to the enablement of business users of making better informed decisions, thus increasing effectiveness and efficiency of business processes.

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cover image ACM Other conferences
OBI '08: Proceedings of the first international workshop on Ontology-supported business intelligence
October 2008
95 pages
ISBN:9781605582191
DOI:10.1145/1452567
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 October 2008

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Author Tags

  1. business intelligence
  2. conceptual query design
  3. enduser development
  4. information integration
  5. ontology

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  • (2023)Self-service business intelligence and analytics application scenarios: A taxonomy for differentiationInformation Systems and e-Business Management10.1007/s10257-022-00574-321:1(159-191)Online publication date: 5-Feb-2023
  • (2023)Business User-Oriented Recommender System of DataResearch Challenges in Information Science: Information Science and the Connected World10.1007/978-3-031-33080-3_44(613-621)Online publication date: 23-May-2023
  • (2020)User-Related Challenges of Self-Service Business IntelligenceInformation Systems Management10.1080/10580530.2020.181445838:4(309-323)Online publication date: 12-Sep-2020
  • (2018)GOWDAProceedings of the ACM Symposium on Document Engineering 201810.1145/3209280.3229099(1-4)Online publication date: 28-Aug-2018
  • (2018)Using Semantic Web technologies in the development of data warehouses: A systematic mappingWIREs Data Mining and Knowledge Discovery10.1002/widm.12939:3Online publication date: 7-Dec-2018
  • (2017)Semantic Navigation and Discussion in a Digital Boardroom2017 IEEE 11th International Conference on Semantic Computing (ICSC)10.1109/ICSC.2017.39(290-296)Online publication date: 2017
  • (2016)Self-Service Business IntelligenceBusiness & Information Systems Engineering10.1007/s12599-016-0424-658:2(151-155)Online publication date: 15-Feb-2016
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  • (2013)Utilizing Structured Information from Multiple External Sources in the Context of the Multidimensional Data ModelBusiness Information Systems10.1007/978-3-642-38366-3_8(88-99)Online publication date: 2013
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