Employing Aviation-specific Contexts for Business Rules and Business Vocabularies Management in SemNOTAM

Felix Burgstaller

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

SemNOTAM is a knowledge and rule-based semantic filter system for safety and time critical announcements of temporary changes to flight conditions (NOTAMs). The relevance and importance of NOTAMs to a specific situation is determined by business rules (BRs). In SemNOTAM, many BRs apply across several situations and thus can be collected into super-situations. To support an incremental BR elicitation process, required by their number, and later maintenance of BRs, an adequate BR management system is vital. However, current systems provide mostly simple organisation techniques insufficient for SemNOTAM. Many research fields, e.g., library information science, manage large information bases by utilising problem-specific contexts. These contexts may be hierarchically structured. Similarly, we propose aviation-specific contexts to manage BRs and their associated business vocabularies in SemNOTAM. To implement the proposed management system we employ design science. In this paper we present the method, preliminary results, and the evaluation planned to this end.
Original languageEnglish
Title of host publicationOnTheMove Academy (OTMA). On the Move to Meaningful Internet Systems: OTM 2016 Workshops - Confederated International Workshops: EI2N, FBM, ICSP, Meta4eS, and OTMA 2016, Revised Selected Papers.
Place of PublicationBest Contribution Award
PublisherSpringer International Publishing
Pages315 - 325
Number of pages10
Volume10034
Publication statusPublished - Oct 2016

Publication series

NameLecture Notes in Computer Science (LNCS)

Fields of science

  • 102 Computer Sciences
  • 102010 Database systems
  • 102015 Information systems
  • 102016 IT security
  • 102025 Distributed systems
  • 102027 Web engineering
  • 102028 Knowledge engineering
  • 102030 Semantic technologies
  • 102033 Data mining
  • 502050 Business informatics
  • 503008 E-learning

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Management and Innovation

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