Pictures and Big Data, what can they tell us?

Or could this data even be harmful when in the wrong hands?Before taking a closer look at this, I would like to dive into the work of Gillian Rose[1], who created a framework of how urban scholars have been working and engaging with photography as a visual representation of urban spaces.

This is important because it helps us understand how images interact with the urban space.

The author provides a framework for this, suggesting three main approaches that are used by scholars: representing, evoking and performing the urban.

Representing the urban: An urban area can be represented by visual media.

Thus, a specific picture is approached as being representational.

Rose mentions that generally a large focus lies on this approach.

Some genres are: documentary photography, photojournalism, art photography.

Traditionally, pictures were often used to represent changes over time, descriptively, being used to objectively documents changes of the area over time for example during urban development projects with pictures before and after a specific change.

Though, as the author points out, a picture is never objective.

Photography can be tied up with a certain ideology.

A picture, as much as it can tell us, is always only what the photographer wants us to see through his eyes, his view through the camera.

I find this point especially true in times, where Instagram seems to be the main way how we see and perceive the world.

I wrote about the problem of a disproportionate perception of reality through Instagram in another blogpost.

Evoking the urban: Rose describes a different way of approaching images.

Instead of only focusing on the representation, one can look at the affective feelings an image evokes.

Images can convey feelings and emotions, sensual effects.

This adds an additional layer to images, which is becoming increasingly important.

Performing the urban: The general focus of scholars lies on what Rose describes as images produced by “‘expert’ visual practitioners”.

Scholars mainly work with images created by professionals such as artists, photographers, architects etc.

But the increased availability of cheap cameras since the end of the 19th century and nowadays of digital photography has led to an increasing large amount of amateur photography.

Especially the widespread usage of social networks with vast amounts of digital pictures and videos gives us another way of analyzing these images.

Online, images are attached to more data than just the image itself, they become performing.

Mapmakers can use the geo-tags, which are attached to many pictures, to create virtual maps of places based on Instagram pictures.

Timestamps, upload patterns etc.

give us many more ways of analyzing images.

To understand the difference between these approaches, I want to give an example of how we discussed these approaches in one of my lectures in university.

We students had to choose an image that involves the different approaches.

I chose an image posted on Instagram depicting the Oberbaumbrücke in Berlin.

This bridge is famous, but not as iconic for the city, compared to other landmarks such as the Brandenburg Gate.

For me, it represents Kreuzberg, a specific part of the city.

The bridge and a sunset in the background evokes a feeling of home and harmony.

I feel myself beamed back to Berlin, where I was born and raised.

The performing level is added through Instagram, where it has a timestamp, a geo-tag, and people can even interact with it, by commenting, liking or sharing it.

This creates even more data.

“The Best Photo Spots in Berlin_BIG_019” by ftrc is licensed under CC BY-SA 2.

0The main insight from this article shows us, how different approaches give us different levels of information and data.

While we had a look at single pictures, what can the billions of images that are shared online tell us?Lev Manovich, Nadav Hochman, and Jay Chow asked a similar question, trying to learn more about cultural patterns and reflections of specific places through thousands of images on Instagram.

[2] The researchers developed new techniques to analyze and compare Instagram’s big data for different cities.

Their results can be found on Phototrails.

Mapping pictures by time or various visual attributes such as the hue, brightness, contrast etc.

, the researchers were able to create distinctive, unique patterns for different cities, such as New York, Tokyo or Tel Aviv based on 2.

3 million Instagram pictures.

One can see unique, recurring day and night shifts for every city.

Even events such as Hurricane “Sandy” can also be mapped and analyzed like this.

Moreover, the research takes a closer look at uploads in Tel Aviv over a time span of over three months, revealing specific social, cultural and political insights from people’s activities.

The artist project ‘On Broadway’[3] gathers even more data and maps it specifically along the Broadway in New York.

Their inspiration comes from an old artist book that you can unfold to a 25 feet-long continues photographic view of both sides of a section of Sunset Boulevard.

The project combines several data layers such as household income, taxi drop-offs and pickups, Foursquare check-ins and the amount of Twitter messages together with Instagram posts and the Google Streetview images along the street.

Personally, I find this project very interesting, and one can travel along the virtual Broadway, looking at the different data sets.

This creates a digital layer and gives us insights into the patterns along the actual street.

One can see, where the most tourists go to, where the money is made, and which areas of Broadway don’t attract as much interest in the real world.

Big Data has become a buzzword nowadays, and many see the future in this: a world where the vast amounts of digital data we create becomes a valuable resource, giving us better and better insights into people’s lives and daily patterns.

The data mapping described here seems to be only the beginning.

But where do they get this data from?.They get it from us, you and me, normal people that use their electronic devices, that upload data onto the internet.

Most of the time we create data without even knowing it.

Even though the methods described here are mainly for research or artistic purposes, how does it look like with large corporations?.Won’t they use that information to make even more money?.What about my privacy?.Did I allow them to use this data?“Opere 34” by D’Apostrophe ❜, Donatello D’Angelo is licensed under CC BY-NC 4.

0This is a major concern.

Shoshana Zuboff is warning us with her new book.

[4] She describes the collection of data through constant surveillance by corporations as “surveillance capitalism”.

Corporations are increasingly sneaking into every corner of our lives.

Our smartphones are excellent surveillance devices and we gladly give up our privacy for a little more comfort, better search results, not having to type ourselves anymore.

To relate this concept to the research methods of mapping data in a city, Zuboff also talks about surveillance in “smart cities”.

Corporations like Google increasingly sell their technology to cities as solutions to almost any problem, promising innovation.

They ‘force’ cities into integrating their technology in order to stay competitive.

They promise great things like better traffic predictions.

While we saw what Big Data can tell us, should we give private corporations access to public space and practically unlimited access to the data of citizens in these spaces?.Zuboff discusses the smart city partnership project of Toronto and Sidewalk Labs, a Google company.

Sidewalk Labs won a proposal to develop an empty space at Toronto’s eastern waterfront.

The project has been increasingly criticized as non-transparent and dangerous.

[5] In a letter to the city council, US venture capitalist Roger McNamee wrote: “The smart city project on the Toronto waterfront is the most highly evolved version to date of … surveillance capitalism”.

McNamee even was an early investor of Google and Facebook but has become quite concerned about privacy and data handling.

He further writes: “No matter what Google is offering, the value to Toronto cannot possibly approach the value your city is giving up”.

He sees a threat that Google will use the data to nudge our decisions in certain directions.

This would become easier with better data predictions.

In a nutshell, pictures can tell us stories.

There are different layers we can look at: symbolic, evoking and performing.

When a picture becomes performing online, it is bound to more than just the picture, but to other data as well.

Pictures itself are data, and in large amounts images can be mapped in different ways.

Big Data can tell us stories, give us insights into cultural, political and social aspects of urban areas.

It can reveal daily patterns and it can be mapped to tangible places and related to other data sets, as we can see with the project On Broadway.

But this can also be threat to our privacy, making us transparent and predictable, maybe even controllable, when in the wrong hands.

Therefore, we need to think about, with whom we want to share this data, who can control it.

We need regulations to keep control of our data and privacy.

[1] Gillian Rose, ‘Visual Culture, Photography and the Urban: An Interpretive Framework’, Space and Culture, India, 2.

3 (2014), 4 <https://doi.




92> .

[2] Nadav Hochman and Lev Manovich, ‘Zooming into an Instagram City: Reading the Local through Social Media’, First Monday, 18.

7 (2013) <https://doi.




4711> .

[3] Daniel Goddemeyer and others, ‘ON BROADWAY’ <http://on-broadway.

nyc/> [accessed 8 June 2019].

[4] S Zuboff, ‘The Age of Surveilance Capitalism: The Fight for a Human Future at the New Frontier of Power’ (London: Profile Books.

, 2019), pp.


[5] Leyland Cecco, ‘“Surveillance Capitalism”: Critic Urges Toronto to Abandon Smart City Project | Cities | The Guardian’, 6 June 2019 <https://www.




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