TechnicityTO 2016: Open data driving business opportunities

Our afternoon at Technicity 2016 started with a panel on open data, moderated by Andrew Eppich, managing director of Equinix Canada, and featuring Nosa Eno-Brown, manager of Open Government Office at Ontario’s Treasury Board Secretariat, Lan Nguyen, deputy CIO at City of Toronto, and Bianca Wylie of the Open Data Institute Toronto. Nguyen started out talking about how data is a key asset to the city: they have a ton of it gathered from over 800 systems, and are actively working at establishing data governance and how it can best be used. The city wants to have a platform for consuming this data that will allow it to be properly managed (e.g., from a privacy standpoint) while making it available to the appropriate entities. Eno-Brown followed with a description of the province’s initiatives in open data, which includes a full catalog of their data sets including both open and closed data sets. Many of the provincial agencies such as the LCBO are also releasing their data sets as part of this initiative, and there’s a need to ensure that standards are used regarding the availability and format of the data in order to enable its consumption. Wylie covered more about open data initiatives in general: the data needs to be free to access, machine-consumable (typically not in PDF, for example), and free to use and distribute as part of public applications. I use a few apps that use City of Toronto open data, including the one that tells me when my streetcar is arriving; we would definitely not have apps like this if we waited for the City to build them, and open data allows them to evolve in the private sector. Even though those apps don’t generate direct revenue for the City, success of the private businesses that build them does result in indirect benefits: tax revenue, reduction in calls/inquiries to government offices, and a more vibrant digital ecosystem.

Although data privacy and security are important, these are often used as excuses for not sharing data when an entity benefits unduly by keeping it private: the MLS comes to mind with the recent fight to open up real estate listings and sale data. Nguyen repeated the City’s plan to build a platform for sharing open data in a more standard fashion, but didn’t directly address the issue of opening up data that is currently held as private. Eno-Brown more directly addressed the protectionist attitude of many public servants towards their data, and how that is changing as more information becomes available through a variety of online sources: if you can Google it and find it online, what’s the sense in not releasing the data set in a standard format? They perform risk assessments before releasing data sets, which can result in some data cleansing and redaction, but they are focused on finding a way to release the data if all feasible. Interestingly, many of the consumers of Ontario’s open data are government of Ontario employees: it’s the best way for them to find the data that they need to do their daily work. Wylie addressed the people and cultural issues of releasing open data, and how understanding what people are trying to do with the data can facilitate its release. Open data for business and open data for government are not two different things: they should be covered under the same initiatives, and private-public partnerships leveraged where possible to make the process more effective and less costly. She also pointed out that shared data — that is, within and between government agencies — still has a long ways to go, and should be prioritized over open data where it can help serve constituents better.

The issue of analytics came up near the end of the panel: Nguyen noted that it’s not just the data, but what insights can be derived from the data in order to drive actions and policies. Personally, I believe that this is well-served by opening up the raw data to the public, where it will be analyzed far more thoroughly than the City is likely to do themselves. I agree with her premise that open data should be used to drive socioeconomic innovation, which supports my idea that many of the apps and analysis are likely to emerge from outside the government, but likely only if more complete raw data are released rather than pre-aggregated data.