Skip to main content
SpringerLink
Log in

SemFus: Semantic Fusion Framework Based on JDL

  • Conference paper
  • First Online:
Innovations and Advances in Computer, Information, Systems Sciences, and Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 152))

Abstract

Data fusion techniques combine data from multiple sources and gather related information to achieve more specific inferences than could be achieved by using a single source. The most widely-used method for categorizing data fusion-related functions is the JDL model, but it suffers from semantics and syntax issues. In order to achieve semantic interoperability in a heterogeneous information system, the meaning of the information that is interchanged has to be understood across the systems. Semantic conflicts occur whenever two contexts do not use the same interpretation of the information. Using semantic technologies for the extraction of implicit knowledge is a new approach to overcome this problem. In this paper a semantic fusion framework (SemFus) is proposed based on JDL which can overcome the semantic problems in heterogeneous systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. White FE (1991) Data fusion lexicon. Data fusion subpanel of the joint directors of laboratories technical panel for C3, Code 4202. NOSC, San Diego

    Google Scholar 

  2. Hall DL, Llinas J (1997) An introduction to multi-sensor data fusion. Proc IEEE 85:6–23

    Google Scholar 

  3. Cheng HG (1997) Representing and reasoning about semantic conflicts in heterogeneous information sources. Doctoral dissertation, Sloan School of Management, MIT, Cambridge

    Google Scholar 

  4. Nakamura EF, Loureiro AA, Frery AC (2007) Information fusion for wireless sensor networks: methods, models, and classifications. ACM Comput Surv 39:3

    Google Scholar 

  5. Dasarathy BV (1997) Sensor fusion potential exploitation-innovative architectures and illustrative applications. Proc IEEE 85:24–38

    Google Scholar 

  6. Boyd JR (1987) A discourse on winning and losing. Unpublished set of briefing slides available at Air University Library, Maxwell AFB, Alabama

    Google Scholar 

  7. Shulsky AN, Schmitt GJ (2002) Silent warfare: understanding the world of intelligence, 3rd edn. Brasseys Inc., New York

    Google Scholar 

  8. Bedworth MD, O’brien JC (1999) The omnibus model: a new model for data fusion. In: Proceedings of the 2nd international conference on information fusion, FUSION’99, ISIF, Sunnyvale, pp 437–444

    Google Scholar 

  9. Blasch E, Plano S (2002) JDL level 5 fusion model: user refinement issues and applications in group tracking. SPIE, vol 4729. Aerosense, pp 270–279

    Google Scholar 

  10. Polychronopoulos A, Amditis A, Scheunert U, Tatschke T (2006) Revisiting JDL model for automotive safety applications: the PF2 functional model. In: The 9th international conference on information fusion, Florence, 2006

    Google Scholar 

  11. John JS (2007) Where’s level 2/3 fusion—a look back over the past 10 years. In: 10th international conference on information fusion, 2007

    Google Scholar 

  12. Synnergren J, Gamalielsson J, Olsson B (2007) Mapping of the JDL data fusion model to bioinformatics. IEEE Explor 44:1506–1511

    Google Scholar 

  13. Steinberg AN, Bowman CL, White FE (1999) Revisions to the JDL data fusion model. Sensor fusion: architectures, algorithms, and applications. In: Proceedings of the SPIE, vol 3719

    Google Scholar 

  14. Llinas J, Bowman CL, Rogova G, Steinberg AN, Waltz E, White FE (2004) Revisiting the JDL data fusion model II. In: Proceedings of the 7th international conference on information fusion, Stockholm, 2004

    Google Scholar 

  15. Steinberg AN, Bowman CL, White FE (2004) Rethinking the JDL data fusion model. In: NSSDF conference proceedings, 2004

    Google Scholar 

  16. DeVin LJ, Holm M, Ng AHC (2010) The information fusion JDL-U model as a reference model for virtual manufacturing. J Robot Comp Integr 26(6):629–638

    Google Scholar 

  17. Cruz IF, Xiao H (2005) The role of ontologies in data integration. J Eng Intell Sys 13(4):245–252

    Google Scholar 

  18. Laskey KB, da Costa PCG, Wright EJ, Laskey KJ (2007) Probabilistic ontology for net-centric fusion. In: 10th international conference on information fusion, Quebec, 2007

    Google Scholar 

  19. Kokar MM, Matheus CJ, Baclawski K, Letkowski JA, Hinman M, Salerno J (2004) Use cases for ontologies in information fusion. In: Proceedings of the seventh international conference on information fusion, pp 415–421

    Google Scholar 

  20. Kokar M, Matheus CJ, Baclawski K (2009) Ontology-based situation awareness. Inform Fusion 10:83–98

    Article  Google Scholar 

  21. Kazakov M, Abdulrab H, Babkin E (2002) Ontology fusion approach for integration in heterogeneous distributed systems. Engineering context-aware object-oriented systems and environments, ECOOSE

    Google Scholar 

  22. Wache H, Voegele T, Visser U, Stuckenschmidt H, Schuster G, Neumann H, Huebner S (2001) Ontology-based integration of information-a survey of existing approaches. In: Proceedings of IJCAI workshop on ontologies and information sharing, pp 108–117

    Google Scholar 

  23. Boury-Brisset A-C (2003) Ontology-based approach for information fusion. In: Proceedings of the 6th international conference on information fusion, Cairns

    Google Scholar 

  24. Smart PR, Bahrami A, Braines D, McRae-Spencer D, Yuan J, Shadbolt NR (2007) Semantic technologies and enhanced situation awareness. In: Paper presented at the 1st annual conference of the international technology alliance, ACITA, Maryland

    Google Scholar 

  25. Gagnon M (2007) Ontology-based integration of data sources. In: 10th international conference on information fusion, Quebec

    Google Scholar 

  26. Little EG, Rogova GL (2009) Designing ontologies for higher level fusion. Inform Fusion 10:70–82

    Google Scholar 

  27. Matheus C, Kokar M, Baclawski K, Letkowski J, Call C, Hinman M, Salerno J, Boulware D (2005) SAWA: an assistant for higher-level fusion and situation awareness. In: Paper presented at the SPIE conference on multisensor, multisource information fusion, Orlando

    Google Scholar 

  28. Zafeiropoulos A, Konstantinou N, Arkoulis S, Spanos D, Mitrou N (2008) A semantic-based architecture for sensor data fusion. In: 2nd international conference on mobile ubiquitous computing, systems, services and technologies, 2008

    Google Scholar 

  29. Simperl E (2009) Reusing ontologies on the semantic web, a feasibility study. Data Knowl Eng 68(10):905–925

    Article  Google Scholar 

  30. Hall DL (2001) Handbook of multisensor data fusion. CRC Press, Boca Raton

    Google Scholar 

  31. Bizer H, Berners-Lee T (2009) Linked data—the story so far. Special issue on linked data. Int J Semantic Web Inform Sys 53:1–22

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1.  , Ferdowsi University of Mashhad, Mashhad, Iran

    Havva Alizadeh Noughabi, Mohsen Kahani & Behshid Behkamal

Authors
  1. Havva Alizadeh Noughabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohsen Kahani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Behshid Behkamal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Havva Alizadeh Noughabi .

Editor information

Editors and Affiliations

  1. School of Engineering, University of Bridgeport, University Avenue 221, Bridgeport, 06604, Connecticut, USA

    Khaled Elleithy

  2. School of Engineering, University of Bridgeport, University Avenue 221, Bridgeport, 06604, Connecticut, USA

    Tarek Sobh

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this paper

Cite this paper

Noughabi, H.A., Kahani, M., Behkamal, B. (2013). SemFus: Semantic Fusion Framework Based on JDL. In: Elleithy, K., Sobh, T. (eds) Innovations and Advances in Computer, Information, Systems Sciences, and Engineering. Lecture Notes in Electrical Engineering, vol 152. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3535-8_49

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-3535-8_49

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-3534-1

  • Online ISBN: 978-1-4614-3535-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation