Opening up Government Datasets for Big Data Analysis to Support Policy Decisions

Authors: K. Hardy, A. Maurushat

Abstract:

Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: Big data, open data, productivity, transparency.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1339203

References:

[1] PricewaterhouseCoopers, Deciding with Data: How Data-Driven Innovation is Fuelling Australia’s Economic Growth. PwC, 2014.
[2] Government 2.0 Taskforce, Engage: Getting on with Government 2.0 – Report of the Government 2.0 Taskforce. Australian Government, 2009.
[3] Australian Government Information Management Office, Australian Government Information Interoperability Framework: Sharing Information Across Boundaries. AGIMO, 2006.
[4] Australian Government Information Management Office, National Government Information Sharing Strategy: Unlocking Government Information Assets to Benefit the Broader Community. Australian Government, 2009.
[5] Data to Decisions Cooperative Research Centre, Review of Barriers to Open Data and Related Re-Use of Information in Five Exemplar Federal Data Sets. Data to Decisions CRC, November 2014, Draft Report.
[6] IBM, Bringing Big Data to the Enterprise: What Is Big Data? (last accessed 8 October 2015).
[7] Department of Finance and Deregulation, The Australian Public Service Big Data Strategy: Improved Understanding Through Enhanced Data-Analytics Capability. Australian Government, 2013.
[8] V. Mayer-Schönberger and K. Cukier, Big Data: A Revolution That Will Transform How We Live, Work and Think. London: John Murray, 2013.
[9] Barcelona Inspires, BCN Smart City (last accessed 8 October 2015).
[10] Lateral Economics, Open for Business: How Open Data Can Help Achieve the G20 Growth Target. Lateral Economics and Omidyar Network, June 2014.
[11] Open Government Partnership, What is the Open Government Partnership? (last accessed 8 October 2015).
[12] Australian Government, Information Security Management Guidelines. Australian Government, 2013.
[13] Jane Yakowitz, “Tragedy of the data commons” Harv Journal Law & Tech, vol 25, no. 1, pp. 1-67.
[14] Stephen Wilson, “You can de-identify but you can’t hide’, Lockstep, 25 April 2015 < http://lockstep.com.au/blog/2015/04/25/de-identification-risks> (last accessed 8 October 2015).
[15] Dan Barth-Jones, ‘Does de-identification work or not’, FierceBigData, 23 June 2014 < http://www.fiercebigdata.com/story/does-de-identification-work-or-not/2014-06-23> (last accessed 8 October 2015).
[16] Australian Information Commissioner, What is covered by privacy? (last accessed 8 October 2015).
[17] Australian Government Productivity Commission, Annual Report 2012-13. Australian Government, 2013.
[18] Australian Information Commissioner, Principles on Open Public Sector Information. Australian Information Commissioner, 2011.
[19] Peter Mell, “NIST Presentation: Overview of Big Data and Security Implications” National Institute of Standards and Technology (2015) http://breakinggov.sites.breakingmedia.com/wp-content/uploads/sites/4/2012/11/bigdata.pdf.
[20] Alana Maurushat, Lyria Bennett-Moses and David Vaile, “Using ‘Big’ Metadata for Criminal Intelligence: Understanding Limitations and Appropriate Safeguards,” (June, 2015) Proceedings of the 15th International Conference on Artificial Intelligence and Law 196 http://dl.acm.org/ft_gateway.cfm?id=2746110&ftid=1596343&dwn=1&CFID=542654113&CFTOKEN=24738647 (last accessed October 10, 2015).
[21] Jane Bambauer, Krish Muralidhar, and Rathindra Sarathy, “Fool’s Gold: an Illustrated Critique of Differential Privacy” (2014) 16 Vanderbilt Journal of Entertainment & Technology Law.
[22] Ed Felten, and Narayanan, “No Silver Bullet: De-identification Still doesn’t Work” (July 9, 2014) http://randomwalker.info/publications/no-silver-bullet-de-identification.pdf (last accessed October 9, 2015).
[23] Ann Cavoukian and Jonas, “Privacy by Design in the Age of Big Data” (June 8, 2012) http://privacybydesign.ca/content/uploads/2012/06/pbd-big_data.pdf (last accessed October 9, 2015).