Skip to main content
SpringerLink
Log in

A Methodology for Quality-Based Selection of Internet Data Sources in Maritime Domain

  • Conference paper
  • First Online:
Business Information Systems (BIS 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 255))

Included in the following conference series:

Abstract

The paper presents a methodology for identification, assessment and selection of internet data sources that shall be used to supplement existing internal data in a continuous manner. Several criteria are specified to help in the selection process. The proposed method is described based on an example of the system for the maritime surveillance purposes, originally developed within the SIMMO research project. As a result, we also present a ranking of concrete data sources. The presented methodology is universal and can be applied to other domains, where internet sources can offer additional data.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Notes

  1. 1.

    SIMMO – System for Intelligent Maritime MOnitoring, the JIP-ICET 2 project financed by the Contributing Members of the European Defence Agency.

  2. 2.

    http://www.imo.org/en/OurWork/Safety/Navigation/Pages/AIS.aspx.

  3. 3.

    http://www.dogpile.com/.

  4. 4.

    https://mamma.com/.

  5. 5.

    http://www.webcrawler.com/.

References

  1. Robey, D., Markus, M.L.: Rituals in information system design. MIS Q. 8, 5–15 (1984)

    Article  Google Scholar 

  2. International Organization for Standardization: ISO 8402–1986 (GB/T6583-1992): Quality-Vocabulary, June 1986

    Google Scholar 

  3. Vespe, M., Sciotti, M., Battistello, G.: Multi-sensor autonomous tracking for maritime surveillance. In: International Conference on Radar, 2008, pp. 525–530. IEEE (2008)

    Google Scholar 

  4. European Commission: Integrated Maritime Policy for the EU. Working document III on Maritime Surveillance Systems (2008)

    Google Scholar 

  5. Kazemi, S., Abghari, S., Lavesson, N., Johnson, H., Ryman, P.: Open data for anomaly detection in maritime surveillance. Expert Syst. Appl. 40(14), 5719–5729 (2013)

    Article  Google Scholar 

  6. Alonso, J., Ambur, O., Amutio, M.A., Azañón, O., Bennett, D., Flagg, R., McAllister, D., Novak, K., Rush, S., Sheridan, J.: Improving access to government through better use of the web. World Wide Web Consortium (2009)

    Google Scholar 

  7. Rhodes, B.J., Bomberger, N.A., Seibert, M., Waxman, A.M.: Maritime situation monitoring and awareness using learning mechanisms. In: Military Communications Conference, MILCOM 2005, pp. 646–652. IEEE (2005)

    Google Scholar 

  8. Fooladvandi, F., Brax, C., Gustavsson, P., Fredin, M.: Signature-based activity detection based on Bayesian networks acquired from expert knowledge. In: 12th International Conference on Information Fusion, FUSION 2009, pp. 436–443. IEEE (2009)

    Google Scholar 

  9. Riveiro, M., Falkman, G., Ziemke, T.: Improving maritime anomaly detection and situation awareness through interactive visualization. In: 11th International Conference on Information Fusion, 2008, pp. 1–8. IEEE (2008)

    Google Scholar 

  10. Helldin, T., Riveiro, M.: Explanation methods for Bayesian networks: review and application to a maritime scenario. In: Proceedings of the 3rd Annual Skövde Workshop on Information Fusion Topics (SWIFT 2009), pp. 11–16 (2009)

    Google Scholar 

  11. Peter, B.: Data quality. The key to interoperability (2010)

    Google Scholar 

  12. Wang, R.Y., Reddy, M.P., Kon, H.B.: Toward quality data: an attribute-based approach. Decis. Support Syst. 13(3), 349–372 (1995)

    Article  Google Scholar 

  13. Wang, R.Y., Strong, D.M.: Beyond accuracy: what data quality means to data consumers. J. Manage. Inf. Syst. 12, 5–33 (1996)

    Article  Google Scholar 

  14. Batini, C., Cappiello, C., Francalanci, C., Maurino, A.: Methodologies for data quality assessment and improvement. ACM Comput. Surv. 41(3), 16:1–16:52 (2009)

    Article  Google Scholar 

  15. European Statistical System: ESS handbook for quality reports. Eurostat (2014)

    Google Scholar 

  16. European Parliament: Regulation (EC) No 223/2009 of the European Parliament and the Council of 11 on European statistics and repealing Regulation (EC, Euratom). Official J. Eur. Union 52 (2009)

    Google Scholar 

  17. Naumann, F., Freytag, J.C., Spiliopoulou, M.: Quality-driven source selection using data envelopment analysis. In: Proceedings of the 3rd Conference on Information Quality (IQ), Cambridge, MA (1998)

    Google Scholar 

  18. Dorofeyuk, A., Pokrovskaya, I., Chernyavkii, A.: Expert methods to analyze and perfect management systems. Autom. Remote Control 65(10), 1675–1688 (2004)

    Article  MATH  Google Scholar 

  19. Kazemi, S., Abghari, S., Lavesson, N., Johnson, H., Ryman, P.: Open data for anomaly detection in maritime surveillance. Expert Syst. Appl. 40(14), 5719–5729 (2013)

    Article  Google Scholar 

  20. Brown, B.B.: Delphi process: a methodology used for the elicitation of opinions of experts. Technical report, DTIC Document (1968)

    Google Scholar 

Download references

Acknowledgements

This work was supported by a grant provided for the project SIMMO: System for Intelligent Maritime MOnitoring (contract no. A-1341-RT-GP), financed by the Contributing Members of the JIP-ICET 2 Programme and supervised by the European Defence Agency.

Author information

Authors and Affiliations

  1. Poznań University of Economics and Business, Poznań, Poland

    Milena Stróżyna, Dominik Filipiak, Jacek Małyszko & Krzysztof Węcel

  2. LuxSpace Sarl, Betzdorf, Luxembourg

    Gerd Eiden

Authors
  1. Milena Stróżyna
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gerd Eiden
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dominik Filipiak
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jacek Małyszko
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Krzysztof Węcel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Milena Stróżyna .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Poznan Univ of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. Institut für Wirtschaftsinformatik, Universität Leipzig, Leipzig, Sachsen, Germany

    Rainer Alt

  3. Information System Institute, University of Leipzig, Leipzig, Germany

    Bogdan Franczyk

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Stróżyna, M., Eiden, G., Filipiak, D., Małyszko, J., Węcel, K. (2016). A Methodology for Quality-Based Selection of Internet Data Sources in Maritime Domain. In: Abramowicz, W., Alt, R., Franczyk, B. (eds) Business Information Systems. BIS 2016. Lecture Notes in Business Information Processing, vol 255. Springer, Cham. https://doi.org/10.1007/978-3-319-39426-8_2

Download citation

Publish with us

Policies and ethics

Search

Navigation