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Analysing Open Data in Virtual Research Environments

Name: Analysing Open Data in Virtual Research Environments
Creator: Anneke Zuiderwijk
Keywords: Knowledge management, Computer Networks and Communications, Policy making, Computer science, business.industry, 05 social sciences, OGD, General Social Sciences, user support, VREs

New Collaboration Opportunities to Improve Policy Making

descriptionPublicationkeyboard_double_arrow_right Article 01 Oct 2017 Netherlands IGI GlobalInternational Journal of Electronic Government Research, volume 13, pages 76-92 (issn: 1548-3886, eissn: 1548-3894,

Authors: Anneke Zuiderwijk;

doi: 10.4018/ijegr.2017100105

Analysing Open Data in Virtual Research Environments

- Summary
- Subjects
- References
  (27)
- Metrics

Abstract

This article describes how virtual research environments (VREs) offer new opportunities for researchers to analyse open data and to obtain new insights for policy making. Although various VRE-related initiatives are under development, there is a lack of insight into how VREs support collaborative open data analysis by researchers and how this might be improved, ultimately leading to input for policy making to solve societal issues. This article clarifies in which ways VREs support researchers in open data analysis. Seven cases presenting different modes of researcher support for open data analysis were investigated and compared. Four types of support were identified: 1) ‘Figure it out yourself', 2) ‘Leading users by the hand', 3) ‘Training to provide the basics' and 4) ‘Learning from peers'. The author provides recommendations to improve the support of researchers' open data analysis and to subsequently obtain new insights for policy making to solve societal challenges.

Country

Netherlands

Related Organizations

Delft University of Technology
Netherlands

Subjects by Vocabulary

Microsoft Academic Graph classification: Knowledge management Policy making Computer science business.industry Social issues Underdevelopment Open data business

Keywords

Computer Networks and Communications, OGD, General Social Sciences, user support, VREs, Collaboration, Open Governmental Data, Hardware and Architecture, Virtual Research Environment, Software, ues

27 references, page 1 of 3

Ardito, C., Costabile, M. F., Desolda, G., Matera, M., & Buono, P. (2016). A Meta-design Approach to Support Information Access and Manipulation in Virtual Research Environments. In M. X. Bornschlegl, F. C. Engel, R. Bond et al. (Eds.), Advanced Visual Interfaces. Supporting Big Data Applications: AVI 2016 Workshop, AVIBDA 2016, Bari, Italy, June 7-10 (pp. 115-126). Cham: Springer International Publishing. doi:10.1007/978-3- 319-50070-6_9 [OpenAIRE]

Batie, S. S. (2008). Wicked problems and applied economics. American Journal of Agricultural Economics, 90(5), 1176-1191. doi:10.1111/j.1467-8276.2008.01202.x [OpenAIRE]

Bornschlegl, M. X., Manieri, A., Walsh, P., Catarci, T., & Hemmje, M. L. (2016). Road mapping infrastructures for advanced visual interfaces supporting big data applications in virtual research environments. Paper presented at the Workshop on Advanced Visual Interfaces AVI. doi:10.1145/2909132.2927471 [OpenAIRE]

Buddenbohm, S., Enke, H., Hofmann, M., Klar, J., Neuroth, H., & Schwiegelshohn, U. (2015). Success Criteria for the Development and Sustainable Operation of Virtual Research Environments. D-Lib Magazine, 21(9/10). doi:10.1045/september2015-buddenbohm [OpenAIRE]

Bueren, E. M., Klijn, E. H., & Koppenjan, J. F. (2003). Dealing with wicked problems in networks: Analyzing an environmental debate from a network perspective. Journal of Public Administration: Research and Theory, 13(2), 193-212. doi:10.1093/jopart/mug017

Calzolari, A., Valerio, A., Capone, F., Napolitano, M., Villa, M., Pricci, F., & Belardelli, F. et al. (2014). The European research infrastructures of the ESFRI Roadmap in biological and medical sciences: Status and perspectives. Annali dell'Istituto Superiore di Sanita, 50(2), 178-185. PMID:24968918

Candela, L., Castelli, D. & Pagano, P. (2013). Virtual Research Environments: An Overview and a Research Agenda. Data Science Journal, 12, GRDI75-GRDI81. doi:10.2481/dsj.GRDI-013

Carusi, A., & Reimer, T. (2010). Virtual Research Environment Collaborative Landscape Study. Retrieved from http://www.jisc.ac.uk/publications/reports/2010/vrelandscapestudy.aspx#downloads

Chen, D., & Zhao, H. (2012, March 23-25). Data security and privacy protection issues in cloud computing. Paper presented at the International Conference on Computer Science and Electronics Engineering (ICCSEE), Hangzhou, China.

Choi, J., & Tausczik, Y. (2017). Characteristics of Collaboration in the Emerging Practice of Open Data Analysis. Paper presented at the ACM Conference on Computer Supported Cooperative Work and Social Computing, Portland, OR. doi:10.1145/2998181.2998265 [OpenAIRE]

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Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	7
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

Usage byUsageCounts

visibility	views	163
download	downloads	64

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	7
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average