A Decision Model for Data Sharing

  • Silja M. Eckartz
  • Wout J. Hofman
  • Anne Fleur Van Veenstra
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8653)

Abstract

Data-driven innovation has great potential for the development of innovative services that not only have economic value, but that help to address societal challenges. Many of these challenges can only be addressed by data sharing of public and privately owned data. These public-private data sharing collaborations require data governance rules. Data governance can address many barriers, for example by deploying a decision model to guide choices regarding data sharing resulting in interventions supported by a data sharing platform. Based on a literature review of data governance and three use cases for data sharing in the logistics sector, we have developed a data sharing decision model from the perspective of a data provider. The decision model addresses technical as well as ownership, privacy, and economical barriers to sharing publicly and privately owned data and subsequently proposes interventions to address these barriers. We found that the decision model is useful for identifying and addressing data sharing barriers as it is applicable to amongst others privacy and commercial sensitive data.

Keywords

Data Governance Data-Driven Innovation Public Service Innovation Open Data Decision Model 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    European Commission, Digital agenda: Turning government data into gold, European Commission, Brussels (2011)Google Scholar
  2. 2.
    Manyika, J., et al.: Big data: the next frontier for innovatioin, competition, and productivity. McKinsey&Company (2011)Google Scholar
  3. 3.
    Janssen, K.: The influence of the PSI directive on open government data: An overview of recent developments. Government Information Quarterly 28(4), 446–456 (2011)CrossRefGoogle Scholar
  4. 4.
    Jaeger, P., Bertot, J.: Transparancy and technological change: ensuring qeual and sustained public access to government information. Government Information Quarterly 27(4), 371–376 (2010)CrossRefGoogle Scholar
  5. 5.
    Harrison, T., Pardo, T., Cook, M.: Creating Open Government Ecosystems: a research and development agenda. Future Internet 4(4), 900–928 (2012)CrossRefGoogle Scholar
  6. 6.
    Endsley, M.R.: Toward a theory of situation awareness in dynamic systems. Human Factors: The Journal of the Human Factors and Ergonomics Society 37(1), 32–64 (1995)CrossRefGoogle Scholar
  7. 7.
    Zuiderwijk, A., Helbig, N., Gil-Garcia, J., Janssen, M.: Guest Editors’ Introduction. Innovation through open data: a review of the state-of-the-art and an emerging research agenda. Journal of Theoretical and Applied Electronic Commerce Research 9(2) (2014)Google Scholar
  8. 8.
    Jetzek, T., Avital, M., Bjørn-Andersen, N.: Generating Value from Open Government Data. In: The 34th International Conference on Information Systems, ICIS 2013 (2013)Google Scholar
  9. 9.
    Janssen, M., Charalabidis, Y., Zuiderwijk, A.: Benefits, Adoption Barriers and Myths of Open data and Open government. Information Systems Management 29(4), 258–268 (2012)CrossRefGoogle Scholar
  10. 10.
    Klein, H., Myers, D.: A set of principles for conducting and evaluating interpretitive field studies in information systems. MIS Quarterly 23(1), 67–93 (1999)CrossRefGoogle Scholar
  11. 11.
    Walsham, G.: Doing interpretive research. European Journal on Information Systems 15(3), 320–330 (2006)CrossRefGoogle Scholar
  12. 12.
    Mingers, J.: Combining IS research methods: towards a pluralist methodology. Information System Research 12(3), 240–259 (2001)CrossRefGoogle Scholar
  13. 13.
    Janssen, M., Zuiderwijk, A.: Open data and transformational government. In: TGov Conference, London (2012)Google Scholar
  14. 14.
    Barry, E., Bannister, F.: Barriers to open data release: a view from the top. In: 2013 EGPA Annuaul Conference, Edinburgh (2013)Google Scholar
  15. 15.
    Weill, P., Ross, J.: IT Governance: how top performers manage IT decisions rights for superior results. Harvard Business School Press, Boston (2004)Google Scholar
  16. 16.
    Weber, K., Otto, B., Osterle, H.: One size does not fit all - a contigency approach to data governance. Journal of Data and Information Quality (JDIQ) 1(1), 4 (2009)Google Scholar
  17. 17.
    Batini, C., Scannapieco, M.: Data Quality: concepts. Springer, Heidelberg (2006)Google Scholar
  18. 18.
    Knight, S., Burn, J.: Developing a framework for assessing information quality on the World Wide Web. Informing Science, 159–172 (2005)Google Scholar
  19. 19.
    Nousak, P., Phelps, R.: A scorecard approach to improving data quality (January 1, 2002), http://www2.sas.com/proceedings/sugi27/p158-27.pdf (accessed March 14, 2014)
  20. 20.
    McDonnell, Big Data Challenges and Opportunities (2011), http://spotfire.tibco.com/blog/?p=6793
  21. 21.
    Bizer, C., et al.: Linked Data - The Story So Far (2011)Google Scholar
  22. 22.
    Batini, C., Scannapieco, M.: Data quality: concepts, methodologies, and techniques. Springer, Heidelberg (2006)Google Scholar
  23. 23.
    United Nations, Rotterdam Rules (2008), http://www.uncitral.org/pdf/english/texts/transport/rotterdam_rules (accessed 2012)
  24. 24.
    Dalmolen, S., Cornelisse, E., Stoter, A., Hofman, W., Bastiaansen, H., Punter, M., Knoors, F.: Improving sustainability throuhg intelligent cargo and adaptive decision making. In: E-Freight 2012. Delft (2012)Google Scholar
  25. 25.
    Esmeijer, J., Bakker, T., Munck, S.D.: Thriving and surviving in a data-driven society, TNO, Delft (2013)Google Scholar
  26. 26.
    Hofman, W., Bastiaansen, H.: A global IT infrastructure improving container security by data completion. In: ECITL, Zaragoza, Spain (2013)Google Scholar
  27. 27.
    Miller, P., Styles, R., Heath, T.: Open data commons, a license for open data. In: LODW 2008, Beijing (2008)Google Scholar
  28. 28.
    Berners-Lee, T.: Linked Data - four rules (June 18, 2009), http://www.w3.org/DesignIssues/LinkedData

Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Silja M. Eckartz
    • 1
  • Wout J. Hofman
    • 1
  • Anne Fleur Van Veenstra
    • 1
  1. 1.Technical Science DepartmentDutch National Institute of Applied ScienceGB DelftThe Netherlands

Personalised recommendations