An Analysis of Interaction Between Users and Open Government Data Portals in Data Acquisition Process

  • Di WangEmail author
  • Deborah Richards
  • Chuanfu Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11016)


The rate of development of open government data (OGD) portals has been fast in recent years due to potential benefits of the utilization of OGD. However, scholars have emphasized lack of use as a key problem in the realization of these benefits. Although studies have been carried out to understand decisive factors in OGD utilization from the aspects of either portals or users, they failed to consider the interaction between the two. Therefore, our study carried out an analysis of the interaction between users and OGD portals during users’ data acquisition process from three aspects: data acquisition methods, data quality requirements, and helping functions. We carried out a survey in a Chinese population to collect data for analysis. Results show users’ high acceptance of keyword search as their method for data acquisition through OGD portals but browsing showed higher usage frequency and was a more stable data acquisition behavior. Females show better acceptance of regular recommendations (e.g. RSS) based on their visiting histories than males. Users’ age, education background and occupation affect their demands of different data quality attributes. Our analysis also shows positive relationship between users’ data acquisition habits with their demands of data quality, users’ need of help with their feelings of difficulties in using the portal, and users’ need of help with their demands of data quality. We suggest promoting OGD utilization by offering better helping functions and improving data qualities in future development of OGD portals.


Open government data Data portal Data acquisition 


  1. 1.
    Attard, J., et al.: A systematic review of open government data initiatives. Gov. Inf. Q. 32(4), 399–418 (2015)CrossRefGoogle Scholar
  2. 2.
    Lourenço, R.P.: Open government portals assessment: a transparency for accountability perspective. In: Wimmer, M.A., Janssen, M., Scholl, H.J. (eds.) EGOV 2013. LNCS, vol. 8074, pp. 62–74. Springer, Heidelberg (2013). Scholar
  3. 3.
    Lourenço, R.P.: An analysis of open government portals: a perspective of transparency for accountability. Gov. Inf. Q. 32(3), 323–332 (2015)CrossRefGoogle Scholar
  4. 4.
    Heise, A., Naumann, F.: Integrating open government data with stratosphere for more transparency. Web Semant. Sci. Serv. Agents World Wide Web 14, 45–56 (2012)CrossRefGoogle Scholar
  5. 5.
    Kassen, M.: A promising phenomenon of open data: a case study of the Chicago open data project. Gov. Inf. Q. 30(4), 508–513 (2013)CrossRefGoogle Scholar
  6. 6.
    Ruijer, E., et al.: Connecting societal issues, users and data. Scenario-based design of open data platforms. Gov. Inf. Q. 34, 470–480 (2017)CrossRefGoogle Scholar
  7. 7.
    Wang, H.-J., Lo, J.: Adoption of open government data among government agencies. Gov. Inf. Q. 33(1), 80–88 (2016)CrossRefGoogle Scholar
  8. 8.
    Safarov, I., Meijer, A., Grimmelikhuijsen, S.: Utilization of open government data: a systematic literature review of types, conditions, effects and users. Inf. Polity 22, 1–24 (2017)CrossRefGoogle Scholar
  9. 9.
    Zuiderwijk, A., Janssen, M.: A coordination theory perspective to improve the use of open data in policy-making. In: Wimmer, M.A., Janssen, M., Scholl, H.J. (eds.) EGOV 2013. LNCS, vol. 8074, pp. 38–49. Springer, Heidelberg (2013). Scholar
  10. 10.
    Meijer, A., de Hoog, J., van Twist, M., van der Steen, M., Scherpenisse, J.: Understanding the dynamics of open data: from sweeping statements to complex contextual interactions. In: Gascó-Hernández, M. (ed.) Open Government. PAIT, vol. 4, pp. 101–114. Springer, New York (2014). Scholar
  11. 11.
    Florini, A.: Making transparency work. Glob. Environ. Politics 8(2), 14–16 (2008)CrossRefGoogle Scholar
  12. 12.
    Wijnhoven, F., Ehrenhard, M., Kuhn, J.: Open government objectives and participation motivations. Gov. Inf. Q. 32(1), 30–42 (2015)CrossRefGoogle Scholar
  13. 13.
    Willinsky, J.: The unacknowledged convergence of open source, open access, and open science. First Monday 10(8) (2005)Google Scholar
  14. 14.
    Galitz, W.O.: The Essential Guide to User Interface Design: An Introduction to GUI Design Principles and Techniques. Wiley, New York (2007)Google Scholar
  15. 15.
    Ubaldi, B., Open government data: towards empirical analysis of open government data initiatives. In: OECD Working Papers on Public Governance, vol. 22, p. 1 (2013)Google Scholar
  16. 16.
    The Open Difinition. Accessed 9 June 2018
  17. 17.
    OECD: Recommendation of the Council for enhanced access and more effective use of Public Sector Information (2008)Google Scholar
  18. 18.
    Kostovski, M., Jovanovik, M., Trajanov, D.: Open data portal based on semantic web technologies. In: Proceedings of the 7th South East European Doctoral Student Conference. University of Sheffield, Greece (2012)Google Scholar
  19. 19.
    Dix, A.: Human-computer interaction. In: Liu, L., Özsu, M.T. (eds.) Encyclopedia of Database Systems, pp. 1327–1331. Springer, Boston (2009). Scholar
  20. 20.
    King, W.R., He, J.: A meta-analysis of the technology acceptance model. Inf. Manag. 43(6), 740–755 (2006)CrossRefGoogle Scholar
  21. 21.
    Parycek, P., Hochtl, J., Ginner, M.: Open government data implementation evaluation. J. Theor. Appl. Electron. Commer. Res. 9(2), 80–99 (2014)CrossRefGoogle Scholar
  22. 22.
    Power, R., Robinson, B., Rudd, L., Reeson, A.: Scenario planning case studies using open government data. In: Denzer, R., Argent, R.M., Schimak, G., Hřebíček, J. (eds.) Environmental Software Systems, Infrastructures, Services and Applications, ISESS 2015. IFIP Advances in Information and Communication Technology, vol. 448, pp. 207–216. Springer, Cham (2015). Scholar
  23. 23.
    Magalhaes, G., Roseira, C., Manley, L.: Business models for open government data. In: Proceedings of the 8th International Conference on Theory and Practice of Electronic Governance. ACM (2014)Google Scholar
  24. 24.
    Susha, I., Grönlund, Å., Janssen, M.: Driving factors of service innovation using open government data: An exploratory study of entrepreneurs in two countries. Inf. Polity 20(1), 19–34 (2015)CrossRefGoogle Scholar
  25. 25.
    Gonzalez-Zapata, F., Heeks, R.: The multiple meanings of open government data: understanding different stakeholders and their perspectives. Gov. Inf. Q. 32(4), 441–452 (2015)CrossRefGoogle Scholar
  26. 26.
    Whitmore, A.: Using open government data to predict war: a case study of data and systems challenges. Gov. Inf. Q. 31(4), 622–630 (2014)CrossRefGoogle Scholar
  27. 27.
    Veeckman, C., van der Graaf, S.: The city as living laboratory: empowering citizens with the citadel toolkit. Technol. Innov. Manag. Rev. 5(3) (2015)CrossRefGoogle Scholar
  28. 28.
    Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46(2), 186–204 (2000)CrossRefGoogle Scholar
  29. 29.
    Carter, L., Bélanger, F.: The utilization of e-government services: citizen trust, innovation and acceptance factors. Inf. Syst. J. 15(1), 5–25 (2005)CrossRefGoogle Scholar
  30. 30.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q., 319–340 (1989)CrossRefGoogle Scholar
  31. 31.
    Dawes, S.S.: Stewardship and usefulness: policy principles for information-based transparency. Gov. Inf. Q. 27(4), 377–383 (2010)CrossRefGoogle Scholar
  32. 32.
    Wang, R.Y., Strong, D.M.: Beyond accuracy: what data quality means to data consumers. J. Manag. Inf. Syst. 12(4), 5–33 (1996)CrossRefGoogle Scholar
  33. 33.
    Ten Principles for Opening Up Government Information. Accessed 9 June 2018
  34. 34.
    Methodology - Global Open Data Index. Accessed 9 June 2018
  35. 35.
    8 Principles of Open Government Data. Accessed 9 June 2018
  36. 36.
    Board, P.S.T. (ed.): Public Data Principles (2012)Google Scholar
  37. 37.
    OpenDataBarometer ODB Methodology - v1.0 (2016)Google Scholar
  38. 38.
    Murillo, M.J.: Evaluating the role of online data availability: the case of economic and institutional transparency in sixteen Latin American nations. Int. Polit. Sci. Rev. 36(1), 42–59 (2015)CrossRefGoogle Scholar
  39. 39.
    Peytchev, A.: Consequences of survey nonresponse. ANNALS Am. Acad. Polit. Soc. Sci. 645(1), 88–111 (2013)CrossRefGoogle Scholar
  40. 40.
    Schmeets, H., Janssen, J.P.: Using national registrations to correct for selective non-response. Political preference of ethnic groups. Statistics Netherlands (2003)Google Scholar
  41. 41.
    Cronbach, L.J.: Coefficient alpha and the internal structure of tests. psychometrika 16(3), 297–334 (1951)CrossRefGoogle Scholar
  42. 42.
    Tavakol, M., Dennick, R.: Making sense of Cronbach’s alpha. Int. J. Med. Educ. 2, 53 (2011)CrossRefGoogle Scholar
  43. 43.
    Kaiser, H.F.: A second generation little jiffy. Psychometrika 35(4), 401–415 (1970)CrossRefGoogle Scholar
  44. 44.
    Dziuban, C.D., Shirkey, E.C.: When is a correlation matrix appropriate for factor analysis? Some decision rules. Psychol. Bull. 81(6), 358 (1974)CrossRefGoogle Scholar
  45. 45.
    Posten, H.O.: The robustness of the two—sample t—test over the Pearson system. J. Stat. Comput. Simul. 6(3–4), 295–311 (1978)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Wuhan UniversityWuhanChina
  2. 2.Macquarie UniversitySydneyAustralia

Personalised recommendations