Missing Datasets

These days, I’m a fellow over at the Data & Society Research Institute. I’m working on a couple of different projects, but the primary one has to do with missing datasets.

Calling something “missing” automatically implies that it should exist, and that’s sort of the point of my project. We’re living in a time of unprecedented levels of data collection. This isn’t a revolutionary insight, it’s just a rote fact. We are systematically tracked, recorded, and documented in ways that are more thorough and expansive than ever before. Though people have different relationships and attitudes to the tactics, methods, vehicles of this data collection (attitudes that range from hopefulyness around perceived benefits to desperate techno-pessimism about potential abuses), no one is exempt.

But at the exact same time that this massive overcollection is unfolding, there are blank spots in the data ecosystem. That is, within contexts that seem to have nearly every possible metric quantified and recorded, there exist spaces that are curiously devoid of data.

Here are some pretty familiar examples that explain what I mean: Despite the fact that the workplace is heavily-studied by sociologists and companies have obvious incentives for collecting data on employees, before ProPublica’s 2013 initiative there was no data on unpaid internships. There was no set of data that anyone could point to that gave any idea of how many students were working unpaid internships, or how many companies were offering them. It was a missing dataset.

An even better-known (and much more political) example has to do with civilians and the police. It wasn’t until quite recently, thanks to initiatives like D. Brian Burghart’s Fatal Encounters website and The Guardian’s The Counted campaign, that we as a public started to have an idea of the number of civilians killed in interactions with legal enforcement agencies. Prior to their work, that was a missing dataset.

In the article The Collection and the Cloud, Amelie Abreu points out that "...the Internet Archive isn’t the Internet Archive, but an Internet Archive, very much built and collected from a certain standpoint and position of power". Abreu's point -- that there’s always a reason why certain things get saved and others don’t -- applies to data as well. There’s a reason why certain data becomes a dataset, and that reason is as much personally and institutionally motivated as it is technologically. There’s not much incentive for a company to collect data on why it isn’t paying employees, just like there isn’t much incentive for the police to talk about how many unarmed civilians are killed each year, or there isn’t much incentive for tech companies to release abysmal diversity statistics. It’s not that organizations are maliciously trying to hide information so much as there’s just no reason for them to go out of their ways to collect, let alone publish, that data.

But of course, there is reason for other people to have that data, and in a time where data is collected about nearly everything, it wouldn't be surprising for many to feel as though not having data means that something doesn’t exist. For every dataset where there’s an impetus for someone not to collect, there’s a group of people who would benefit from its presence. More data doesn’t always mean better answers, but in cases where data is used as the end-all tool of proof or a definitive measure for change, then it’s clear that lacking it can be a serious structural disadvantage.

And here’s where my project comes in. I’m interested in finding and helping those who are directly affected by the issues in question fill other missing datasets. Is there a way to both provide access to previously unattainable datasets and give those people who have a stake in information the ability to affect it?

That’s the high-level overview of some of the work I’ll be doing this year. I’m just at the beginning of the process, but if you’re interested in any of these questions or have relevant datasets of your own, please do reach out.

Mimi Onuoha
The Personal Data Conundrum

For a long time, if you had asked me what one thing I would change about most people’s relationships to their data, my answer would have been awareness.

What I meant by that was simple: I wanted people to know more about the roles data plays in their lives and in the world.

In my mind, that meant loads of things: understanding that digital footprints have memories and lifelines, and that access to them brings the ability to infer things about people and relationships. It included knowing that companies like Facebook can make money off your data even while you still technically own all your content; understanding that data isn’t truth; knowing that photos can and are photoshopped (even by institutions like governments); believing that the Department of Homeland Security has and does track people who haven’t done anything wrong (though now it has greater means and a longer reach to do so).

It also meant knowing that personal data is the valuable currency that many corporations deal in. It involved accepting the fact that the things you knowingly and unknowingly produce have the ability to reach dizzying levels of dissemination, and the potential to live longer lives than you.

 Banksy's Dismaland included a gigantic chart of surveillance in the UK that was both impressive and overwhelming. 

Banksy's Dismaland included a gigantic chart of surveillance in the UK that was both impressive and overwhelming. 

That’s just a (small) sample of the sorts of things that I think everyone should know. My thought process was that if everyone knew and understand the data landscape — not just data literacy, but the whole picture— the potential for our data to be used against us would be significantly minimized.

Obviously, that was a rosy, idealized point of view. And lately I haven’t been feeling the same way.

Lately I’ve been getting stuck on something I like to call the Personal Data Conundrum. Now that you know that you leave data trails everywhere, what are you to do with that information? So you know that companies make money off of you. Now what? Your data is valuable in conjunction with others’; for most of us, it carries less value when considered individually. So opting out as one person doesn’t necessarily change the system itself. And a company like AT&T may be handing over data to the US government, but it’s not like switching to T-Mobile solves the problem. Either way, your data is still out of your hands (and now your cell phone service is even spottier).

Lots of activists, artists, and privacy enthusiasts have one answer: that you should protect yourself. Use Tor! Download Telegram! Get a VPN! Use masked email addresses! But those are all individual responses to a systemic issue, and in situations with an unequally distributed playing field, it’s inevitable that only those with the time, resources, and interest will adopt those measures. And even if that wasn’t the case, the larger problems remain. Should you quit using a cell phone? Stop accessing public wifi? Refuse to use Google Maps, because even though it gives you directions it also combines your location data with the other hundreds of datapoints Google has on you? Our very ways of communicating are so ingrained in these compromised systems. For a lot of people, opting out of being a data machine means opting out of feeling like you’re fully participating in society.

So now my sense is that though awareness is important, demanding (or even hoping for) everyone to be completely knowledgeable about and connected to their personal data is shortsighted and overly-optimistic. Ignorance and indifference are completely reasonable responses to the realization of your lack of agency. Some people may think that if there’s nothing they can do about a situation, they’d rather not engage at all—-and I can’t even blame them for that line of thought.

So there’s the dilemma. I think it’s important for people to understand and think about their data, but once they do that, they end up directly confronting problems in efficacy that I don’t have practical answers for solving.

Mimi Onuoha
How To Get Your Mobile Data

A quick announcment before I jump in: I just launched Pathways, the output of my 2014-15 Fulbright-National Geographic Digital Storytelling Fellowship. It’s a site that shows the stories derived from collecting a month’s worth of mobile data from Londoners. I did the design, UX, and development for the whole thing, as well as the research, data collection and data analysis, so it’s quite exciting to have it finally live. Check it out here.

In conjunction with Pathways, below is a guide on how you can get the same locative, social media, and metadata that I collected from my participants. Quick note: this isn’t a guide for developers, programmers, or people who identify as very technical. If you fit in that crowd, then you’ll immediately realize that there are many more efficient ways of doing these things. Because the goal of Pathways is to be relevant to people who don’t have any passion or interest in data, this guide is meant to provide easy, not-very-technical hacks for getting your own data.


The main work I did with Pathways was in collecting location data. To be honest, there aren’t great options right now. I asked my participants to install OpenPaths, an open source mobile app that allows you to securely access your location information. OpenPaths is the best option you have in terms of security, but it’s not the most accurate and isn’t being actively developed anymore, which makes me reticent to really recommend it.

On the other hand, I’m not any more excited about the other options. Moves is the best option in terms of level of sophistication around tracking, but I can’t mention Moves without needing to say in the same breath that it’s owned by one of our favorite not-historically-great-with-privacy corporations, Facebook.

So you’ve got to choose what’s more important to you—security or effectiveness? An ugly choice, I know.


You can easily send yourself WhatsApp data from within the app itself. Click over on the chats tab, and then click the following: WhatsApp —> Menu button —> Settings —> Chat Settings —> Backup conversations —> email conversation without media


Open up Skype (on your computer). Choose a conversation. Right click, and you should see the option to “jump back”. Jump back all the way to the beginning, then hit Command + A (or Ctrl + A on a PC) to highlight all of your messages, then Command + C (Ctrl + C) to copy all the messages. Open up a text file and paste.


Really similar to WhatsApp. First go to Messages, then open Viber. Click the following sequence: [messages] —> open Viber —> more option … —> Settings —> calls and messages —> email message history


Google provides a service called Google Takeout where you can easily export your data. On the “Download Your Data” page, you’ll want to choose only “Hangouts”, otherwise it’s going to take hours to get all of your different types of Google Data. I suggest choosing a .zip format as it’ll be easy for you to extract. Google will alert you once your files are ready to download.

Once you get them, you can use this lovely great and free resource provided by Jay, a system administrator who is making your life easier. Just follow the instructions on this site:


Facebook is notorious for eating all of your data and then not providing that data in a really easy format. Getting your data, though, is easy enough:

  1. Go to top right of any Facebook page and select Settings
  2. Click "Download a copy of your Facebook data" below your General Account Settings
  3. Click Start My Archive

Other Options

Those are all pretty simple ways of doing things. They’ll give you access to some of your messages, and you can save everything into a text file. A slightly more technical option if you have an iPhone is to download a program like iPhone Backup Extractor or iBackupViewer; those will give you access to the actual databases that your messages for this apps are saved in locally on your phone.

If you have an Android phone, there are equivalent programs like Android File Transfer, which I believe that you can use even if you haven’t rooted your phone (if you don’t know what that means, don’t worry—it means you haven’t done it).

Mimi Onuoha
The Things You Don't Want To Know

A little while ago, one of my friends emailed me a link to Prism, an application that allows you to see a streamgraph visualization of your texting history over time.

In the email, my friend provided one small caveat: "My sources say it feels a bit creepy to see contacts appear and fade over time. Definitely a case of private data, methinks."

 Image taken from Prism website. 

Image taken from Prism website. 

Let me just point out that I spend a lot of time talking about data literacy, privacy, data ownership, and what you can learn about yourself through data. Most of the work I do revolves around data collection and analysis, in some way, shape, or form(at).

In other words, you would think that I would be the target audience for something like Prism. But I couldn't bring myself to use it. Why? Because I really didn't want to see what it was going to show. I know the basics of my texting history. I know how it's changed as I've moved in and out of cities, countries, and relationships. After all, I lived through those experiences. And given that I know exactly how bittersweet some of them were, the last thing that I want to see is a cheery data viz reminding me of just which people have popped in and then slowly (or even worse, abruptly) faded out of my life. I already feel that particular shade of wistfulness when I stumble over similar information in other people's lives; how much worse will it be to see it in my own?

Maybe that's something that we should talk more about. Just because we have access to all sorts of data about the world and ourselves doesn't necessarily mean that we need to see all of it. To be clear, I'm all for data analysis, empowerment, journalism and the things that you can through all three. But surely we can acknowledge that not everything is suited to routine and saccharine representation through shapes, lines, and maps. Do you want to know how few of your friends will be alive for your 95th birthday? Do you want to know how many times you cried after your last breakup? And those are just the trivial examples!

Perhaps there are things in this world—-messy, difficult, things—-whose very nature demands that we consider them apart from the sense of order, categorization, and understanding that data visualizations tread in. Maybe some things mean less, not more, once categorized and put into metrics.

Or maybe I'm wrong. After all, I could just be squeamish. So you tell me: is there always something to be gained by relentless quantification, or are there things that gain more power by resisting it? I'd love to hear from others (and not just because I'm staring at a CSV file of my old iMessages, wondering whether or not to open it).

Mimi Onuoha
Pinterest meets CCTV Surveillance

I feel like one day I woke up and was on Pinterest. I didn't remember signing up for it, I barely knew what the site was for, but all of a sudden I was regularly seeing cheery emails in my inbox proclaiming "X person started following you on Pinterest" and "Happy Pinning!" Pro tip: ignoring them will not make those emails go away.

Today, though, all those Pinterest emails are no longer for naught. Since I moved to the UK I've been fascinated by the fact that the city has over 7000 CCTV surveillance cameras. I even wrote a post about it over at National Geographic.

But even more captivating to me than the cameras themselves are the signs alerting the public to their presence. Some of the signs are curt and straightforward in tone, others lighthearted, still more apologetically explanatory.

But I shouldn't just have to explain it to you--you should get the chance to see them for yourself. So I created a Pinterest board where I'll be uploading the photos that I take of CCTV signs. Up until this point I've been haphazard in my dedication to documenting them, but starting from now I'll be religious in taking a photo of every one of these signs that I see, and then uploading those pictures to the board.

(So, yes, this is a post letting you know about the pictures I'm taking of the signs that let us know about the pictures that the British state is taking of us. Got that straight?)

Check out the board here.

Mimi Onuoha
Online and Offline, Seen Differently

I want to use this post to say something that's more of an addendum to a previous post I wrote on the online/offline "divide" (or lack thereof) than a full thought. Basically, I'm taking a stab at illustrating the same principles from that post. But I mean that literally, because now I'm using drawings. Also, they were created very quickly in Illustrator, which both adds to the pun and means that I realize I have no excuse for their bare-bones appearance. Do forgive.

To start, let me point out that we live in a networked world, and our lives unfold across that world both online (though mobile and personal computing devices that we use to connect to an Internet through which we, among other things, interact with others) and offline (through the device that is our physical bodies, which also allow us to, among other things, interact with others).

Often when people talk about that fact, they describe it in terms of one or the other. For instance, they'll describe the offline world as "real life", or insist on how "fake" personas on Facebook and Twitter are. They'll wonder if social media is causing us to lose our ability to connect in the "real world".

All those worries, and more, treat the world as if it looks like this:

In that world, offline and online are two distinct and discrete modes, and we just jump between the two.

But that isn't the case. As my current project is exploring, these modes are profoundly connected, and constantly influencing each other. Neither is any more or less "real" than the other. What's more, they seamlessly overlap.

So it's probably a bit more appropriate to render them like this:

In this figure, online status is something that is layered on top of offline status, and the missing X-axis lable is "time." This graph shows that when a child is first born, they may not be online (yet!), but that state eventually is one that exists in addition to the pre-existing offline state. After all, so long as we're living, we're in the offline, physical world. But of course, we also have the ability to also be online. Those moments when the lines overlap represent moments when one is taking advantage of that ability. Like me, for instance, as I post this on my site, or you, as you read it, or the woman on the bus who is emailing her employees at the red light, or the cyclist who is taking a moment to look up Google Maps directions for his route home. Being in the online world does not mean that you step out of the offline.

And that chart could be changed or modified as needed. The following might be what a more personalized version would look for someone who was much older, and who lived most of his/her life in a time before the Internet became the major force it is:

You could also wonder if this isn't a little more accurate, as there's a case to be made for the fact that though we all must leave the offline world, it's much harder for our digital selves to be erased from the online world:

That last one is debatable for a few different reasons, but on any account, it's all very interesting. I'm hoping that those images help make clear the online/offline fluidity that I talk and write about so often. Let me know your thoughts if you have any: @thistimeitsmimi.

Mimi Onuoha
A Theory On Data, Trust, and Communication

Recently I was talking with a friend about a sketch released by comedy duo Key and Peele. The sketch consists just of two characters texting each other back and forth, but the humor is in how they each end up attributing completely different meanings to the exact same words they read. (The scene's embedded below, but be warned, there's some language in it that makes it definitely NSFW. You can skip viewing and still understand the rest of the post just fine).

I bring up the scene because I’ve been thinking a bit about trust, data, relationships, and communication, or more specifically about how the different ways that we communicate can affect our levels of trust in one another. Let me show a small chart to better illustrate what I mean:

Above is a scale of different ways of communicating with people. The modes that give the most information are towards the right and those that give the least are on the left. The items that are closer to the right side of the scale are associated with greater intimacy and trust, while the ones towards the left side provide more ease through instanteneity. This is not to say that the ones at the right require more trust, only that they have the potential to foster higher levels of trust.

Let’s expand a bit more: at the right you have interaction where all channels for data are open (here when I say "data" I mean both the implicit and explicit messages that we exchange when we’re communicating). A huge portion of human interaction is non-verbal; when you’re sitting face-to-face with someone, you don’t just pay attention to the content of what they say. You also consider their expressions, how they’re sitting, the intonation of the words they utter, the attitude that they project, and so on. In fact, it’s the non-verbal communication that fills in the gaps of what someone’s direct words might not cover.

When you think about it, what I’m saying likely comes as no surprise. It’s why after reading a resume or application, institutions still insist on an in-person interview. It’s why presidential candidates pay as much attention to their image as to their speeches. As people, we tend to be much better at discerning information when we have access to more than just words.

But as you look towards the left of the scale, more streams of communication are cut off, signaling the loss of potential channels for information-gathering. When you’re video chatting with someone, you can see and hear them but you miss being able to catch the micro-reactions and subtle clues that an in-person interaction would provide. On the phone, you’ve got hearing but no sight; in messaging (whether chat or text) you’re lacking sight and sound but you do get the immediacy and back-and-forth that defines a conversation. This is contrary to e-mail, which is essentially just streams of asynchronous monologues, and Twitter, which is really a large conversation unfolding at once where everyone is invited but can only say so much at any given time. MOving down the left side of the scale is a bit like compressing a file. You can still transmit content, but chunks of information are removed. Though you can still communicate, it does become that much more difficult to discern the more subtle (and often significant) messages.

But this, again, isn’t a surprise when you think about it. We know the mistakes that arise when you’re texting a friend who responds with “kay”, leaving you to decipher whether they’re being passive-aggressive or just concise. We’ve all had the experience of hearing silence on the other end of a phone call and wishing desperately that we could see the expression on the other person’s face. And surely you’ve been in the unenviable position of having written an email that receives no response for days, or even weeks. The forms of communication towards the bottom of the scale provide us with the ease of not needing to be in the same place or even responding at the same time, but there’s no arguing the fact that there are bits of information that are lost in the tradeoff.

 A slightly more lighthearted take on the concept of the communication scale, this is a depiction by Colleen Douglass of a moment from the HBO TV Show Girls where two characters described the "totem of chat". 

A slightly more lighthearted take on the concept of the communication scale, this is a depiction by Colleen Douglass of a moment from the HBO TV Show Girls where two characters described the "totem of chat". 

Now, you ask: why does this matter?

Well, a week or so ago, I wrote a post for National Geographic about data, tracking, and the climate around both. If you haven’t read it yet, go here to take a look.

One point I alluded to in the post was that the people who are participating in my project have agreed to give me access to their data because they realize that data's already available to lots of corporate entities. But there's an essential part of the picture that I didn’t have the space to highlight in the post, and I can sum that missing element up in one word: trust. Here’s my theory: trust is manufactured through multiple interactions that hover closer to the right side of the scale that I presented earlier. In other words, no matter how many text messages you send, you’ll never truly trust someone unless you graduate to a more context-rich mode of communication.

The reason this is crucial for me is because trust forms the foundation for data sharing. You need trust in order to share the pieces of information that you think reveal something substantive about you. And sure enough, when I think about it in terms of my project, all of the participants who are sharing data with me in this first round are people who I have had either substantial or meaningful (or both!) in-person connections with. Most I’ve met multiple times face-to-face; the others I’ve spent at least an hour or more just talking with. Not coincidentally, the ones who I’ve spent the most time with are the people who I asked to participate and who acquiesced; those who I spent the least time with happen to be the people who volunteered to participate in the project (this is a noteworthy point because I likely wouldn’t have felt like I had fostered enough trust to be able to seriously ask them myself). For all of the participants, before any talk of tracking was brought up, I had already had conversations with them that stretched beyond superficial topics like weather and the tube.

So what am I saying? That successful collection of data from people is and must be built upon a foundation of trust.

This is a theory whose details I’m still fleshing out, but its implications are compelling for someone like me, who is interested in the interpersonal sharing of data between people. I’ll see how this theory unfolds as I begin recruiting and talking to people who I’d like to be involved in the second round of tracking for my project.

One final note: once you have established a bond through higher-context interaction forms, it becomes much easier to use the lower ones. For instance, I’ve known my friend Monika since we were both 8 years old. To this day, we have a steady stream of communication through various messaging services. She can text me one word and I’ll immediately be able to determine her tone and what she means when she’s saying it; this is simply because I have so much material from our years of being friends and interacting in person with each other that I can draw on that to flesh out the her texts. What someone else might interpret as inappropriate I might laugh at, because I know what she really means.

On the other hand, when a friend of mine received a strange message from someone she was talking to on Tinder, lacking any sort of rich information stream from him, she was more inclined to simply stop engaging. Without the in-person data to fill in the gaps, she had no way of being able to decipher the tone or more general connotation around his message.

As I just said, I still have at least one more round of tracking to go, so I’ll continue to reflect on this process of using the scale from the beginning of this post to help explain the importance of building up genuine bonds with the people involved in my project. I’m looking forward to fleshing out this theory as I discover more.

We Don't Remember Where We Go Online

(The alternative title of this post is Results of Browser Experiment 1. More explanatory, more boring.)

Last week, I conducted a browser experiment with students at the Royal College of Art. The idea was to continue some of the investigations I've been doing on conceptions of different types of spaces--except this time, instead of looking at how people think of physical space, I wanted to examine how they think about non-space (aka their browser histories). After all, part of my mission for my fellowship project this year is not just determining how to map browser histories, but also figuring out how people think of them. Hopefully, doing the latter will help reveal what type of meaning, if any, these histories can contain.

For the experiment, I asked a group of about ten students to write down every single site that they remembered visiting on their computers over the past 24 hours. Then they gave me their actual browser histories so that I could do some comparisons. They had been pre-warned that they would be asked to do this, and they and their data are respectively anonymous and secure.

I've only just now begun diving into the data, but I thought I'd show some of the immediately apparent results.

Here are examples of some of the lists that I received from the students:

As you can see, they don't have very much written on them. The most that any one person remembered was 14 sites; the least, 3.

They also all have some clear overlaps in sites. Though I've only shown a few samples, nearly every single one of them had Google, Facebook and Podio (a platform for comunication that we use at the RCA) on their lists. Revealing, but not necessarily a surprise.

Browser histories are essentially saved as SQLite database files (though it really depends on the browsers), so I did a bit of exporting and wrote a few Python scripts to begun looking at the data. It's worth mentioning the fact that though all of the students individually remembered no more than 14 of their sites, the actual number of sites they visited in the time frame were much more than that, ranging from anywhere from 80 to 353 sites.

So far I've seen that the students on average remembered no more than about 10% of the sites they visit. Again, this doesn't come as a complete surprise, but it is interesting to see the actual numbers. Memory and cognition are very much tied together; and as much as I hate to cite TED talks as research, journalist Joshua Foer does have a great talk about strength of spatial memory and the fact that humans remember things in context. The browser history remains a space out of context, and thus the way we think of it is fundamentally different. The fact that the students were so completely removed from the sites that they visit everyday corroborates this.

I should mention that this is still a theory. After all, I haven't nearly dived into the subject or data enough. For instance, browser history databases include data on how long you spend on sites; though I have looked at the data myself and anecdotally have ideas about the ties between those numbers and the sites that the students remembered, I do need to get the actual figures.

So in conclusion: these are just the barest, most preliminary results, but they do show that there's a divide between what we go online and where we actively remember going. I'll eventually be doing some more work with them before I delete the data for good.

Below I've got some of the guides that I gave out so the students would know how to access their histories. Feel free to take a look; I think it's good practice to know where the information is stored. Right now I've only got the ones for Mac + Chrome and Safari, but the Windows versions are on the way.

Understanding the Online/Offline "Divide"

This year I’m working on a monster of a project for the Fulbright National Geographic Digital Storytelling Fellowship. For the project, I'll be assembling a group of Londoners, gathering their mobile geolocation information and their browser histories, then creating representations that provide insight into both.

The project leaks into many different fields (data/privacy, mapping, online/offline interactions, representation of information, understandings of urban spaces, and the interplay of qualitative and quantitative research, to name a few). It contains a lot of moving pieces that all present their own specific challenges.

But I’ve got the next nine months to think, talk, and write about those challenges. What I thought I’d use this post for is as a way to outline the place that I’m coming from for the project as a whole. Some of the underlying topics that inform the project have been swirling in my head for awhile now, and I've realized that since the way that I present the project on the National Geographic site isn’t necessarily commensurate with how I approach the topics in my mind, some explanation might be in order.

Here are the two defining tenets of my point of view, as informed by everything from well-established academic theories to dubiously-trustworthy anecdotal experience.

1.) Our online and offline lives are not separate and remote spheres. In my first post on the National Geographic website, I boldly proclaim that we are all “living a double life.”

The interesting thing about the discussion of online vs offline and physical vs digital is the fact that many people appear to see them as two opposite ends of a spectrum.

But this is a false duality. Our identities and actions bleed over into our online and offline habits. One affects the other, each is just as “real” as its counterpart. We are constantly-connected beings, so much so that even if you aren’t on Facebook, the logic of Facebook continues to stay with you (The idea that this isn’t the case, called digital dualism and coined by Nathan Jurgenson, has been written about by many and is further expanded here .

I often like to think about life as something that unfolds across various contexts. These contexts help determine and affect how we act when in conversation with different actors. (This is another well-established ideology in sociology and anthropology; see Erving Goffman’s “The Presentation of Self in Everyday Life” for more.) All of the spaces that we inhabit can be thought of as contexts, and your behavior across them may vary. You act slightly different at a dinner with your parents than you do when hanging out with your friends on a Friday night, which is still different than the tone you might affect when posting something on Facebook (or should I say Ello?), which remains different than how you might be when commenting anonymously on Youtube videos. You are not any more “you” in any one of these contexts; they all highlight different aspects of you. These are all just different contexts that you exist in, and even though some unfold through mediums like screens and phones, they are no less real or impactful on your everyday life than those that happen in face-to-face interactions.

I like the context-approach to viewing our interactions because it accommodates for the fact that we do live across different media, both on and offline, and that’s perfectly okay. This fact is something that I think we need to more generally normalize across all of our interactions.

But like I said, I think that’s a hard thing for many people to wrap their minds around. I used to be an educator in my past life, and one thing I learned from that was to always start working/talking/teaching from the place that people are at. So that’s one thing I’m attempting to do with my project, particularly in the way that I talk about it on the National Geographic website. I want start from the idea that digital and physical are two different worlds in an attempt to convey (or test) how they aren’t. Hopefully, the end results of my project will show this in a clear and easy-to-understand manner.

2.) The browser space may not be metaphysically experienced the same as offline, physical space.

I mentioned that I like the context perspective because it makes it easier to conceive of how our interactions within online and offline sites can share characteristics. But even though I think all of the places we experience, both on and offline, come together and form one fluid existence, one of the most interesting things about my project for me is that the two modes I’m comparing are not necessarily equals in terms of how they are experienced.

Here’s what I mean: I’m collecting geolocation data and making maps that show how a small group of people experience the city of London. They travel around the city physically, and the locations they visit are stored in their phones, which is how I'm accessing them. This makes a lot of sense to most people who hear it.

I’m also collecting the same people’s browser data and looking at all the sites that they visit for the month. So the obvious response would be to think of these--physical location and browser locations--as two flips of the same coin. However, the experience of browsing the web may not be the same as the experience of wandering the city. The city is a clear and easily-understood space; the browser history is a space that is hard for us to think about, to understand. How much do you know about your browser history, and how much do you remember about it?

The way that we humans make sense of things is through narrative structures, and narrative structures work on principle by omission, or by leaving things out (RCA PhD student John Fass has more about this on his blog). But the browser history doesn’t afford us that luxury. Your locations are to maps as the websites you go to are to browser histories, except that maps have a clear geography to them, and browser histories don’t.

What I’m really grappling with is the task of spacializing a non-space, and the difficulties inherent in that. The way that I’m trying to deal with this is by thinking, in Latour-ian terms, about the connections between the two.

These are the theoretical issues that form the foundation of the project that I’m working on, and it’s at the crossroads of these two realizations that I think my project really becomes interesting. Over the course of the next several months, I’ll be diving into all different aspects of the project, particularly many of the things that I outlined in the second paragraph of this entry.

But as I mentioned, the thoughts outlined in this entry form, in some sense, a basis, so hopefully it’s worth taking the time to outline the perspectives.