What's the big idea?
NYC311 is the city's non-emergency call line bringing over 3,600 non-emergency government services to the fingertips of 8.5+ million New Yorkers 24 hours a day, 7 days a week, 365 days a year. With public access to all NYC311 service requests since 2010 updated daily in OpenDataNYC, communities are empowered by allowing local members, elected officials to social researchers and civic hacktivists to monitor and assess for themselves the status and quality of the city’s functions such as access to adequate heating and ensuring neighborhood non-emergency health and safety concerns. The volume of data alone speaks to the invaluable insights waiting to be mined from this robust data set; however, researchers should proceed with caution when using this powerful data set.
What are the concerns About 311 Data?
The nature of NYC311 Open Data and lack of information available about nuances in the 311 data present hurdles to make the information truly accessible and usable for research. For example, the bias of who uses the data and disproportionality of frequency of use by a particular demographic group in reporting complaints requires a closer examination of local and sectoral context by referencing other departmental data (Maciag, 2016). What a Hundred Million Calls To 311 Reveal About New York further speaks to the nuances in the data and presents case examples of when the data has furthered or hampered the efficiency of government service (Johnson, 2010). Another article investigates, Who Is Most Likely to Dial 311? which cite demographics and civic engagement as important considerations to the validity of the data (Tuhus-Dubrow, 2014). The Promises and Pitfalls of 311 Data further “caution against interpreting 311 data as a measure of mass civic engagement akin to voter turnout, but argue that it is a potentially useful measure of aggregate demands for public services” (Trump & White, 2015).
What is being done and ITS potential USE?
Exemplifying potential power of this public data, researchers from the Boston Area Research Initiative created two 311-related ecometrics for the Boston Research Map: engagement and custodianship which measure a neighborhood’s likelihood of knowing and using the system, and likelihood of actually reporting an incident, respectively (O’Brien, Sampson & Winship, 2015). With a good understanding of the data and a bit of creativity, 311 data does present innovative approaches to the pulse of the city. As another example, researchers at NYU CUSP demonstrated the Structure of 311 service requests as a signature of urban location which “can be used to monitor and predict socioeconomic performance of urban neighborhoods, allowing urban stakeholders to quantify the impacts of their interventions” (Wang, Qian, Kats, Kontokosta & Sobolevsky, 2017).
- Johnson, S. (2010, November 1). “What a Hundred Million Calls to 311 Reveal About New York.” Wired Magazine, November. Retrieved from at https://www.wired.com/2010/11/ff_311_new_york/ Google Scholar
- Maciag, M. (2016, January). “When It Comes to 311, the Customer Isn’t Always Right.” Goverming.com Retrieved from http://www.governing.com/topics/mgmt/gov-311-data.html
- Meier, R. (2017, February 23). “The Rise and Fall of New York City (311 complaints).” TIL BigQuery. Retrieved from https://tilwbq.com/the-rise-and-fall-of-new-york-city-311-complaints-72bd894e0c74
- O’Brien, D.T., Sampson, R.J., Winship, C. (2015). Ecometrics in the age of big data: Measuring and assessing “broken windows” using administrative records. Sociological Methodology, 45: 101-147. Retreived from https://www.northeastern.edu/csshresearch/bostonarearesearchinitiative/projects/seeing-neighborhoods-big-data/
- Trump, K, White A. (2015, November 30). “Research Note: The Promises and Pitfalls of 311 Data.” Sage Journals. Retrieved from http://journals.sagepub.com/doi/10.1177/1078087416673202
- Tuhus-Dubrow, R. (2014, April 8). “Who Is Most Likely to Dial 311?” NextCity.org. Retrieved from https://nextcity.org/daily/entry/who-is-most-likely-dial-311
- Wang L, Qian C, Kats P, Kontokosta C, Sobolevsky S (2017) Structure of 311 service requests as a signature of urban location. PLoS ONE 12(10): e0186314. https://doi.org/10.1371/journal.pone.0186314