“Data is the new black”, or so we’re told.

With so much hype around the data revolution, can data really help us to make better cities? Technology now touches all aspects of our work and lives meaning data is no longer just the remit of analysts and actuaries, but is here and now for town planning.

Data: why should planners care?

The advice we give everyday about land use, built form, and infrastructure unavoidably impacts the way people live. From housing choices, to local economic development, access to recreation activities, and transport options, the decisions we make as urban planners and designers directly impacts lives. It’s a big deal.

But with all this responsibility how much do we really know about the communities we shape? And I don’t mean the density or plot ratio, I mean the lives that people lead.

Do we understand why people choose to live in one neighbourhood over another? If renting is a lifestyle choice, one of economic necessity, or both? And when a new park or plaza opens, what do we know about the people that use it, where they come from and how they spend their time?

data for neighbourhoods.jpeg

As our cities grow we place more pressure on the community engagement process to help us understand local life. Although engaging with local citizens and stakeholders is an essential part of a balanced and democratic planning process, for many projects ‘citizen feedback’ is relied upon as the sole source for local knowledge and insights. Whether online or face-to-face, well crafted community engagement can prove a rich source of stories and sentiment about a place. This makes engagement highly valuable for understanding desires and values, but it is far less effective at quantifying behaviours or uncovering patterns. For example, if asked to provide feedback on local parks in your neighbourhood you are likely to base your responses on your most recent experience: if a local playground has recently been closed for renovation, or the weather has been cold and wet your responses will be skewed.

But it needn’t be this way. As technology touches more aspects of our lives it becomes straightforward to digitally track behaviours and uncover patterns. Frequent flyer programs and store credit cards were originally created to help marketing teams better understand consumer behaviours. Similarly, digital travel cards (Opal Card, MyKi) and automated tolling systems can also yield valuable data sets about commuter behaviour. But this is just the beginning. With more than 78% of Australians now using internet-enabled mobile phones, and 84% of us accessing the internet daily[1], we are generating an immense pool of data every day about who we are, the places we go, and what we value.

They’ve got my data

That’s right. Each time you log on to free wifi, register to attend a public event, or like a local business page you leave a trail of information behind you.

Through our mobile phones, our internet searches, and our social media profiles, we are constantly sharing aspects of our lives, and it’s being put to use.

Information like this is used by Google Maps to generate live traffic volumes[2], by Facebook and Twitter to tailor your news feed to the things you are most likely to read[3], and by advertising and marketing agencies to target digital ads to the right people[4]. Now before you put your phone on flight mode and delete all your social media accounts, it’s important to take this knowledge in context. Shared data is most often aggregated and anonymised, making it impossible to determine individual attributes or behaviours. All the major players strictly adhere to data protection laws[5], and data that is shared through open API’s (an automated means to access third party data) is typically limited to an automation of what is publicly available through their sites. We're all familiar with the recent trouble Facebook have found themselves in, but even they substantially tightened their data access rules in 2014, albeit after the current breach.

But even with the aggregation and anonymisation, social data remains highly insightful. Consider Google. So many parts of our lives touch Google products: our navigation, emails and calendars, and of course our internet searching. And these tiny pieces of information power their products. If you search a local restaurant or park in Google, you will receive a profile on that place including photos, reviews, and the times of the day it is likely to be busy.  With the exception of people who have directly added content such as photos and reviews, the rest of the data provided has been aggregated from sources across the web, as well as crowdsourced from a number of Apps. Over time the information available about the restaurant or park become rich and nuanced. Add in local Eventbrite listings nearby, public Facebook groups, and even the way people portray their lives on Instagram, and an accurate depiction emerges of the place itself as told through the words and actions of the people that go there.

And this is the power of ‘social data’.  

Better cities with social data

It’s clear that social data can play a role in quantifying the components of our urban environments. But its dynamic, irregular, user-generated nature also make it an excellent source of intel on the social side of our cities.

1. Real time

Cities are changing faster than ever, so it’s important the data we use is equally dynamic. When seeking to understand the impact of a new Footpath Trading Policy, or park upgrade, social data allows us easily understand the real changes created by our work.

2. Fine grain

Postcode-level data is so 1990s. We now know that people conceive ‘local’ as neighbourhood scale, not municipality or postcode[6]. Geolocation features on most internet devices now make hyper-local data possible. This allows us to examine the social dynamics of a particular office park or shopping centre as compared to the wider neighbourhood, as well as pinpoint the hotspots of activity.

3. Simple comparison

Living our lives online is virtually ubiquitous across the world. In developing nations the free services of Facebook and Linkedin can be the first choice for hosting business pages and events. This means we can use social data to compare Barcelona’s innovation district with the emerging precincts in Sydney or Melbourne. Or examine the presence of small businesses across mid-sized Southeast Asian cities.

We can only create great places if we truly understand the way people live. And social data provides us with the ability to articulate the personality of the places that we make and manage.

Don’t discount it as a fad, data is here to stay.


Neighbourlytics is an Australian startup pioneering the use of social data in city-making, to make better, more unique and equitable cities.


This article originally appeared in New Planner – the journal of the New South Wales planning profession – published by the Planning Institute of Australia. For more information, please visit: www.planning.org.au/news/new-planner-nsw

[1] Sensis Social Media Reporthttps://www.sensis.com.au/asset/PDFdirectory/Sensis-Social-Media-Report-2017.pdf

[2] ‘The bright side of sitting in traffic: Crowdsourcing road congestion data?’, Google: Official Blog, https://googleblog.blogspot.com.au/2009/08/bright-side-of-sitting-in-traffic.html

[3] ‘Here’s How Facebook’s News Feed Actually Works’, Time Magazinehttp://time.com/collection-post/3950525/facebook-news-feed-algorithm/

[4] ‘The future of online advertising is big data and algorithms’, The Conversationhttps://theconversation.com/the-future-of-online-advertising-is-big-data-and-algorithms-69297

[5] see: https://privacy.google.com/businesses/compliance/#?modal_active=nonehttps://www.facebook.com/policy.phphttps://help.instagram.com/155833707900388 

[6] HyperLocal Movement http://www.zavvie.com/hyperlocalwp

Jessica Christiansen-Franks

Passionate about creating liveable, equitable and interesting cities, I have over fifteen years experience working across urban design, placemaking, community development and citizen engagement, and been involved in some of Australia's most complex and notable urban development projects.

In my work as co-founder of Neighbourlytics I am focussing on using big data to provide insights into the unique local identity of neighbourhoods to create places people love and feel connected to.