Public affairs schools face the challenge of including emergent topics in their curricula to prepare students for the public sector job market. Some such topics reflect advances in the use of information technologies; others reflect updates to industry standards or changing needs of public sector information management professionals. This article focuses on big data that are created through citizens’ use of new technologies and the combination of administratively collected data with online data. Big data require changes in government information management skills, including collection, cleaning, and interpreting unstructured and unfiltered data; real-time decision making based on early signals and patterns that emerge; and new organizational roles and tasks, such as open innovation and change management. This article reviews the existing literature, compares big data requirements in neighboring disciplines, and suggests 13 modules for a big data syllabus that extend Mason’s PAPA model of ethical considerations for the information age.
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References
1.
AsalN. N.RethemeyerR. K. (2015, February 26). Building terrorism from social ties: The dark side of social capital. Civil Wars, 1–23. doi:10.1080/13698249.2014.981942.
2.
AtkinsonG. M.WaldD. J. (2007). “Did you feel it?” Intensity data: A surprisingly good measure of earthquake ground motion.Seismological Research Letters, 78, 362–368.
3.
Bingham-HallJ.LawS. (2015, August). Connected or informed? Local Twitter networking in a London neighbourhood. Big Data and Society. doi:10.1177/2053951715597457.
4.
boydd.CrawfordK. (2012). Critical questions for big data.Information, Communication and Society, 15(5), 662–679.
5.
BrabhamD. (2008). Crowdsourcing as a model for problem solving: An introduction and cases.Convergence, 14(1), 75–90.
6.
BrownsonR. C.FieldingJ. E.MaylahnC. M. (2009). Evidence-based public health: A fundamental concept for public health practice.Annual Review of Public Health, 30, 175–201. doi:10.1146/annurev.publhealth.031308.100134.
7.
BurrusD. (2014). The Internet of things is far bigger than anyone realizes.Wired. Retrieved from http://www.wired.com/insights/2014/11/the-internet-ofthings-bigger.
8.
ClarkW. R.GolderM. (2014). Big data, causal inference, and formal theory: Contradictory trends in political science?PS: Political Science and Politics, 48(1), 65–70.
9.
CohenB.FerngY. H.Wong-McLoughlinJ.JiaH.MorseS. S.LarsonE. L. (2012). Predictors of flu vaccination among urban Hispanic children and adults.Journal of Epidemiology and Community Health, 66(3), 204–209. doi:10.1136/jech.2009.099879.
10.
CourtD. (2015, January). Getting big impact from big data. McKinsey Quarterly. Retrieved from http://www.mckinsey.com/insights/business_technology/getting_big_impact_from_big_data.
11.
CoxM.ElsworthD. (1997, October 18–24). Application-controlled demand paging for outof-core visualization. Paper presented at the 8th IEEE Visualization ’97 Conference, Phoenix, AZ. Retrieved from http://www.evl.uic.edu/cavern/rg/20040525_renambot/Viz/parallel_volviz/paging_outofcore_viz97.pdf.
12.
CukierK. N. (2010, February 25). Data, data everywhere. Economist. Retrieved from http://www.economist.com/node/15557443.
13.
CukierK. N.Mayer-SchoenbergerV. (2013, May/June). The rise of big data: How it’s changing the way we think about the world. Foreign Affairs. Retrieved from http://www.foreignaffairs.com/articles/2013-04-03/rise-big-data.
14.
DavenportT. H.BarthP.BeanR. (2012). How “big data” is different.MIT Sloan Management Review, 54(1), 43–46. Retrieved from http://sloanreview.mit.edu/article/how-big-data-is-different.
15.
DesouzaK. (2014). Realizing the promise of big data. Washington, DC: IBM Center for the Business of Government. Retrieved from http://www.businessofgovernment.org/sites/default/files/Realizing the Promise of Big Data.pdf.
16.
EagleN.PentlandA.LazerD. (2009). Inferring friendship network structure by using mobile phone data.Proceedings of the National Academy of Sciences of the United States of America, 106(36), 15274–15278.
17.
Editorial: Community cleverness required. (2008). Nature, 455(1). Retrieved from http://www.nature.com/nature/journal/v455/n7209/full/455001a.html.
18.
FriedmanU. (2012, October 8). Big data: A short history. Foreign Policy. http://foreignpolicy.com/2012/10/08/big-data-a-short-history.
19.
Gartner. (n.d.). Gartner IT glossary: Big data. Retrieved from http://www.gartner.com/it-glossary/big-data.
20.
GeorgeG.HaasM. R.PentlandA. (2014). Big data and management.Academy of Management Journal, 57(2), 321–326.
21.
HelmsJ. (2015). Five examples of how federal agencies use big data. Retrieved from IBM Center for the Business of Government website: http://www.businessofgovernment.org/blog/business-government/five-examples-how-federal-agencies-use-big-data.
22.
IansitiM.LakhaniK. (2014). Digital ubiquity: How connections, sensors, and data are revolutionizing business.Harvard Business Review, 92(11), 91–99.
23.
KayyaliR.KnottD.Van KuikenS. (2013). The big-data revolution in US health care: Accelerating value and innovation. Retrieved from McKinsey and Company website: http://www.mckinsey.com/insights/health_systems_and_services/the_bigdata_revolution_in_us_health_care.
24.
LazerD.KennedyR.KingG.VespignaniA. (2014). The parable of Google flu: Traps in big data analysis.Science, 343(6176), 1203–1205.
25.
LazerD.PentlandA. S.AdamicL.AralS.BarabasiA. L.BrewerD.et al. (2009). Computational social science.Science, 323(5915), 721–723.
26.
MasonR. O. (1986, March). Four ethical issues of the information age. MIS Quarterly, 5–12.
27.
McAffeeA.BrynjolfssonE. (2012). Big data: The management revolution.Harvard Business Review, 90(10), 60–68.
28.
McKinsey Global Institute. (2011). Big data: The next frontier of innovation, competition, and productivity. Retrieved from http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation.
29.
MergelI.RethemeyerR. K.IsettK. (2015). Big data in public affairs. Manuscript submitted for publication.
30.
MervisJ. (2012). Agencies rally to tackle big data.Science, 336(6077), 22.
31.
MillerJ.KalilT. (2014). Crowdsourcing ideas to accelerate economic growth and prosperity through a strategy for American innovation. Retrieved from White House website: http://www.whitehouse.gov/blog/2014/07/28/crowdsourcing-ideas-accelerateeconomic-growth-and-prosperity-throughstrategy-ameri.
32.
MorseS. S. (2012). Public health surveillance and infectious disease detection.Biosecurity and bioterrorism: biodefense strategy, practice, and science, 10(1), 6–16. doi:10.1089/bsp.2011.0088.
33.
MurdochT. B.DetskyA. S. (2013). The inevitable application of big data to health care.Journal of the American Medical Association, 309(13), 1351–1352.
34.
NeumannW. R.ParkY. J.PanekE. (2012). Tracking the flow of information into the home: An empirical assessment of the digital revolution in the U. S. from 1960–2005.International Journal of Communication, 6, 1022–1041.
35.
NovyA.LeuboltB. (2005). Participatory budgeting in Porto Alegre: Social innovation and the dialectical relationship of state and civil society.Urban Studies, 42(22), 2023–2036.
36.
O’GradyM.O’HareG. (2012). How smart is your city?Science, 335(6076), 1581–1582.
37.
O’MalleyM. (2014). Doing what works: Governing in the age of big data.Public Administration Review, 74(5), 555–556.
38.
OnnelaJ.SaramäkiJ.HyvönenJ.SzabóG.LazerD.KaskiK.et al. (2007). Structure and tie strengths in mobile communication networks.Proceedings of the National Academy of Sciences of the United States of America, 104(18), 7332–7336.
39.
OverbyS. (2013). 6 IT outsourcing lessons learned from HealthCare.gov’s troubled launch. Retrieved from CIO website: http://www.cio.com/article/2381755/outsourcing/6-it-outsourcing-lessonslearned-from-healthcare-gov-s-troubledlaunch.html.
40.
PirogM. A. (2014). Data will drive innovation in public policy and management research.Journal of Policy Analysis and Management, 33(2), 537–543.
41.
PrpićJ.TaeihaghA.MeltonJ. (2015). The fundamentals of policy crowdsourcing.Policy and Internet. doi:dx.doi.org/10.1002/poi3.102.
42.
RaddickM. J.BraceyG.GayP. L.LintottC. J.MurrayP.SchawinskiK.et al. (2010). Galaxy zoo: Exploring the motivations of citizen science volunteers.Astronomy Education Review, 9(1). Retrieved from http://arxiv.org/abs/1303.6886.
43.
U. S. News and World Report. (2012). Best grad schools: Information and technology management. Retrieved from http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-public-affairs-schools/information-technologymanagement-rankings?int=a95909&int=a06908.
44.
WadeC. (2014, April 15). The Reddit reckoning. Slate. Retrieved from http://www.slate.com/articles/technology/technology/2014/04/reddit_and_the_boston_marathon_bombings_how_the_site_reckoned_with_its_own.html.
