Yesterday we launched our new city pages.

We’ve had city pages as collections of information and tips for Dopplr users for over a year, and now we’re made those pages public to the internet: the first stage in creating what we’re calling a “Social Atlas” internally.

A few weeks ago we mailed everyone who had contributed a tip to Dopplr and asked if they would prefer to keep what they had posted private to only Dopplr members, and we’re happy to say no-one chose to – so the collective intelligence of Dopplr is available to everyone on the web to help them travel smarter.

Of course, this works both ways, and we hope of course that more people find Dopplr this way and choose to participate to make our social atlas more comprehensive.

Here’s an example of our new public tips pages: tips tagged “breakfast” in San Francisco:

From which I can find a hidden gem like the one Yoz suggests:

So that’s the useful stuff, but perhaps the most noticeable, eyecatching thing about the new pages is the inclusion of Creative-Commons-licenced photography of the world’s cities powered by Flickr.

We’ve curated a small collection of CC-attribution-sharealike licenced photos from Flickr Places, and then superimposed a graph of Dopplr traveller activity, added some interesting factoids like where most people travel to and from that city and hey presto!

We’re pleased as punch with them, and especially happy to be able to support the Creative Commons in a small way. Many thanks to our friends there and at Flickr for their assistance in putting this together.

It was fascinating to work through thousands of amazing images to select them for the city pages. We created a small tool internally to help speed up this task, which we’ll write a separate more technical post about later.

We’re far from having an image for everywhere on Earth, but we’ll be adding more every week.

One other interesting side-effect of creating the public city pages was that we had to make public pages for the whole geographical hierarchy of our ’social atlas’.

So, we now have ‘place’ pages for countries and all of the USA’s states.

And, I find these pages fascinating! I’ve not been able to stop clicking around them in the same way that I could pore over an atlas when I was a child. You keep turning up things like this:

And my favourite:

I think Funafuti might be my new favourite place…

What’s yours? Go explore!

Celia’s our Community Design Manager at Dopplr, and many of you may have heard from her when you have a problem or a query about the service.

But, the main part of her job is to take that feedback and use it as a basis for designing new and improved ways for you to use Dopplr.

She’s behind the recent update to one of mainstays of the Dopplr interface – the Traveller Overview.

To mark the redesign, I asked her to write a little about the process of coming up with the new interface.

Over to Celia:

The original impetus behind reworking these pages came from the fact that we’d just launched public profiles. We wondered how much of that thinking we could share with the old page, which had essentially stayed the same since we first launched in 2007.

It started off with the idea that we could make the journal the default tab (rather than Trips) and put some of the modules from the public profile, such as future trips, in a side column of the same page.

One idea that came from that discussion was that we should highlight travel coincidences more, as they’re at the heart of Dopplr. It was suggested that we tag or highlight them in some way, which led to thinking that we could group them and push them to the top of the page. We could group them together as we were already doing on trip pages, so people could easily see who was near them “in time and space”.

The result, as you’ll see, is a page which devotes the top left to to coincidences, the bottom left to the journal (a more comprehensive view of activity on your Dopplr account), and the right hand side to future trips.

We also wanted to make sure that the page worked for new users, or people who hadn’t yet added any trips or fellow travellers. The page they see is focussed on adding trips and making connetions to other people.

To make the navigation work, we created a tab for this page and called it “Overview”. To make it fit, we needed to rework the tab structure a little, while keeping some of the familar features that existing users expected to find.

As part of this work, we also created a new view in the “Your trips” tab that allows you to see your past trips.

Up till now there hadn’t been a good way of doing this: you could navigate via the Journal or use the Carbon tab, but neither were really satisfactory. People would often ask us for a view of their past trips, so it’s something we’re very pleased to have built.

Thanks to Celia for that insight into the process, and of course, all her hard work on the redesign.

We still want to do lots more to make Dopplr clearer, easier and more delightful to use, but I’m really glad that we’re starting to get more ways into browsing past trips. While we’re trying to provide a tool for smarter travel focussed on optimising your future, it’s really pleasurable to look back over where you’ve been and see photos and facts about the trip. Looking forward to doing more on that side of Dopplr.

As ever, we’re looking forward to hearing what you think about the new design.

The story starts out like this…

We decided we wanted to make some new stickers to give away, especially in time for dConstruct2008 in Brighton. We were trying to figure out what to do and where to get them printed, when Denise from Moo.com suggested that we use Moo stickers, each representing a city – as they reminded her of the blocks that we use in the Dopplr ’sparklogo’.

We thought this was a great idea, especially as we thought we could go one further and actually generate the city stickers directly from our database, to ssatisfy our near-constant obsession with visualising the world of Dopplr.

MattB got to work making a small bit of code that produced the top 78 cities as colour blocks, to a design template I made in Adobe Illustrator and saved as SVG file for him to manipulate.

With help from our friends at Moo, we were able to interface this directly with their API, creating a limited-edition 100 sticker books to give away.

They went down really well at the event, and we’re starting to collect pictures of people stickering their laptops, moleskines and sometimes themselves with physical infovis in a new Dopplr Moo Stickers group on Flickr.

Things took an unexpected and amazing turn this morning, when Denise IM’d me and let me know that someone had left a comment on Moo’s blog, saying that they really liked how the stickers looked and decided to create a little webapp to generate their own: Mooplr!

Just as we had, Mooplr gets the Dopplr API and Moo API to talk to each other to make stickers.

But Kev Lloyd, the man behind Mooplr went further, and created a simple, minimal interface to let you search for whatever cities or towns you want to make stickers for.

It’s moments like this morning that you realise that the rhetoric of “web2.0″ does have some substance to it, when it allows people to easily create wonderful stuff with what you put out there for them to play with.

Thanks Lloydie!

Small tweak to how we display coincidences in Dopplr, originally uploaded by blackbeltjones.

One of the great things about using copy as interface is how quickly you can change it if you have an idea.

This lunchtime I was looking at my Dopplr journal, and realised we should make it a lot clearer when exactly you and the people in your network are going to be in the same place at the same time.

After all, Dopplr is all about coincidences and maximising serendipity.

Tom said it would be pretty easy to do, MattB agreed and it went live this afternoon!

Not bad going the day after the moo.com summer party…

As we’ve mentioned before, the Dopplr website assigns a distinct colour to every city in our database. This is all very well, but sometimes it generates a colour that’s a little hard to see against a white background (Stockholm’s colour, for instance, is extremely pale), and I wanted to fix this.

Luckily, the W3C have a draft technique for measuring the contrast between two colours, so now when we generate the city colour we first check it to make sure that it’ll be sufficiently visible against our white background. If it’s not, we darken the colour until the contrast is high enough. This means that we’ll be changing the colours of some cities, but the new city colours will be the same as the old colours, only darker.

There are several places in Dopplr where we work hard behind the scenes to turn information that makes sense to people into data that makes sense to machines.

The most important one is where we interpret places and dates and turn them into trips. This is harder than it sounds, because over the centuries people have evolved an astonishing variety of ways of referring to place and time.

This was important recently when we launched our new SMS, Twitter and email features. We get quite a few requests for an explanation of how they work, so here’s a little insight.

The key to Dopplr’s ‘intelligence’ is learning from you and your fellow travellers over time.

For example, let’s say you’ve just joined Dopplr. You type ‘Paris’ into the Add A Trip form, and we look at the history of everyone’s trips from the last 18 months of our database and conclude that 99% of the time, that means “Paris, France”. However, if you’ve been using Dopplr for a while then we also look back at your own trip history. If you’ve previously been on a trip to “Paris, Texas” then that’s the default we’ll choose.

So the more trips you go on, the better we get to know you.

Incidentally, this ‘popularity content’ ranking of places has led to some lovely map visualisations and interesting statistics. If you haven’t seen them before, do look back in our blog at our Raumzeitgeist and Mid-2008 Travel Outlook posts.

When we’re scanning emails, twitters and text messages, we’ve got a few more factors to interpret. This time we’re looking for the dates of your trip as well as the place. We start with some complicated pattern matching which can spot a wide range of date formats in any prose it’s given. But of course most communication about travel mentions a lot of dates; for example, an airline confirmation might mention the date of a future change in luggage allowance.

Once we’ve got a candidate list of dates, we take a look at your traveller network to see if anyone who shares trips with you is going to the same place. If so, and the dates of their trips are similar to yours (within 24 hours or so) then we bump that date suggestion way up the list. If you and your friends or colleagues are going on the same holiday, conference trip or work visit, this works very effectively.

So the more people you share trips with, the better we get to know you.

For every email or twitter that we scan, we remember how you reacted to the result. If you confirm the trip, that’s a success for our system. If we guessed wrong but you chose one of our alternative suggestions, that’s a partial success. And if not, we failed. In any case, we add your message to the test suite we used to judge the quality of our engine, and use it to improve the results.

So the more messages you send us, the more we can improve our system and make it better for everyone.

While we generally release a new version of the service fairly regularly, there’s always something that’s ready-to-rock; and just this week we’ve put live a number of improvements and new features that we’ve been working on beside some of the major new stuff that’s coming soon.

First up, there’s now the ability to add a ‘multi-hop’ trip – something that a lot of you have been asking for. More on that in a separate post.

Secondly – we’ve made some improvements to our tools to manage how you share information with people.

Celia, our community design manager took the lead on that one, incorporating your feedback and our drive to try make everything as simple, elegant and clear as we can.

Over to Celia for her take on the process:

“Redesigning the ‘Connections’ pages was my first design task at
Dopplr. It seemed daunting at first but turned out to be a lot of fun.

We knew that the existing pages were too complicated and that we could
make them better. But instead of relying on our own sense of what
could be improved, we asked our travellers to tell us what they
thought. So we posted a question up on Get Satisfaction and got lots
of fantastic responses – it was really exciting to watch them come in.
A huge thank you goes to everyone who helped us out.

We didn’t incorporate all the ideas there into this version of the
design – there’s always a process of pick and choose that you go
through when coming up with a coherent scheme. The things that didn’t
make it this time round are definitely on file for future reference,
though.

After taking in people’s comments, the next step was to sit down and
digest it and come up with some sketches. The main aim was to keep the
pages as clear as possible – they show lots of different kinds of
relationships and the goal was to make it really easy to see what was
what.

The main changes you’ll notice are that we’ve condensed four tabs down
into just two, and made the titles of the sections within each tab as
explanatory as possible. Hopefully the new version makes it easier to
see who’s who in your Dopplr network.”

Lastly, we’ve given various things like our page headings a spring-clean to make search and other functions easier to find.

We’ve also redesigned our city pages.

This one makes me very happy – I think the guys did a beautiful job on them.

Over to Boris for some colour-commentary on that:

“While adjusting a few things here and there to better fit our not-so-incredibly-tight grid layout (mea culpa!), I was recoding the block that holds the Google Map on the individual trip screens. In so doing, it stretched out to 100% over on the Place screens. While in this state it clearly broke everything around it, I immediately thought “my, that’s pretty…”

A bit more sculpting, a few discussions with the team and it was agreed that it was pretty… and promptly forgotten for about 5 weeks (haha).

We added it to the to-do list maybe two weeks ago – and in a blaze of activity, Tom pulled in the incoming future-trip parabolics, fixed a map-centering issue and made beautiful colour-coded custom place-name markers et voilà.

We can haz new Place screen headers with better communicating maps! Yatta! Please to enjoy!”

This is one of the reasons I love working on Dopplr as a designer – that we’re able to work with our users on improving things, and also those wonderful moments where you accidentally discover a better way to do something by breaking it… Serendipity!

On a cold winter evening in 2006, the founders-to-be of Dopplr got together in a West London pub to talk about an idea for a new kind of travel website. After much excited discussion about features and ways of working, Matt Jones agreed to participate on one condition: that whatever we made would give travellers a way to understand the carbon impact of their travels.

Today, serendipitously on Earth Day 2008, we’re launching a carbon calculator for your trips. Working with AMEE (”The World’s Energy Meter”) we can automatically build a travel carbon profile for you. Because AMEE are an impartial platform who work with many organisations that collect data or propose solutions, this means that you’ll be able to eventually reuse this profile with other services.

My 2008 carbon calendar looks like this:

Of course, the mode of transport you choose for your trips makes all the difference to their carbon impact. That means an upgrade to our trip form, which now lets you specify how you’re travelling:

Now here’s Matt Jones to give his take on why this matters so much:

One of the aspects of creating social tools that fascinates me is the ability to make the invisible visible, and what effect surfacing these patterns then has on us as individuals and groups.

For a while there have been carbon calculators on airline websites and environmentalist websites, but generally they have been about directly showing the impact of an individual action, rather than the patterns and trends influencing the actions in the first place.

That’s why I thought it was an essential component of from the start of Dopplr as a social tool for intelligent travellers to optimise their path through the world – and I’m delighted the beginnings of this are here now. Particular props to Boris and Tom for pulling off the design, which I’m pleased as punch with.

It’s a first step, and as with everything we do part of the bigger, beautiful jigsaw of the web. As MattB’s said it’s plugged into AMEE, and you might be already be subscribed to things like WorldChanging or EdenBee that can help you decide what to do about it.

It’s not enforcing any particular course of action – it’s the weighing scales, not the diet.

What we all do with this information is up to us.

Hello!

My name’s Celia, and I’ve joined Dopplr as the Community Design Manager. As Matt said, that means that my job is to talk to the people out there who are using Dopplr, find out what’s working and what’s not, and help the development team improve things accordingly.

This is going to take a few different forms. For example, sometimes I might post screenshots or prototypes that we’ve been working on, and ask for your feedback. Other times I might ask you seemingly vague questions to try and get to the bottom of what you’d really like us to do for you. Or I might ask you quite directed questions about something that we’ve already built – and that’s what I’m about to do now.

We think the ‘Manage Connections’ page could be better. We have some ideas up our sleeves, but we’d like to know what you think of it, too. What’s working for you, and what’s not? Let us know what you think by joining the discussion over on the Satisfaction site.

Look forward to talking to you there!

We got great reaction to our Raumzeitgeist post, including a lot of queries about the data-set and, unfortunately, some confusion over what we were showing in the main image.

Most people assumed (probably due to me omitting the details – my bad) that we had plotted every trip that people had made last year.

Here’s the amazing part – even with the coverage of the globe shown on that map, it’s not nearly everywhere Dopplr travellers went!

What we are showing are what we call ‘Cluster Cities’ which is the basis of some new functionality you might have already noticed if you’re a Dopplr user that’s been studying their journal feeds/emails closely.

Rewind to Reboot, Copenhagen at the end of May 2007.

We’re sitting on the grass in the sunshine with a bunch of early Dopplr users, including Stowe Boyd and Stephanie Booth – when Stephanie is the first to voice something we’ve heard a lot from Dopplr users since: “make my trips more ‘fuzzy’”.

By which, she and others meant that they would like to see coincidences in the surrounding area of ‘social spacetime’ to their trip – i.e. “show me if there are going to be people I know nearby the stated destination of my trip when I’m going to be there, as I’d probably like to change my plans a little to see them.”

This is a cornerstone of our goal to help optimise travel for Dopplr users – surfacing information about such near coincidences to let them judge whether to alter their plans to make their trip more worthwhile.

We’re going to be releasing a lot of functionality to exploit fuzzy, social spacetime through the early part of 2008, but the first part of it has leaked out into the journal.

Here’s an example.

Previously, if I’d added a trip to San Francisco, I’d have missed out on seeing coincidences with people who live in Oakland, or are visiting Berkeley for instance. Now we fuzz up the edges of your trip’s destination to include those nearby, so you can make that valuable visit on the BART…

Cluster Cities are the way we’ve made this happen. To explain them, here’s Matt B. with the science bit!

To make the database queries perform well enough to implement this feature, we needed to classify cities in densely populated areas into groups. By considering groups of cities as one, we cut down the work the database has to do when calculating who is affected by someone arriving in their area. We decided that these groups should be small enough that a traveller could reasonably expect to travel between any two cities in a group within a day.

Algorithms to cluster a spatial dataset are well known and not hard to implement. Unfortunately, they take a bit of tuning and experimentation to achieve satisfying results. Intuitively we expect cities like London, Tokyo and San Francisco to be at the centres of their clusters. In reality it’s rather hard to teach the cultural/social/economic conditions that cause this to an algorithm that’s only looking at latitude and longitude.

After some initially disappointing results, I stopped looking solely at the geographical data and considered what I could do if I incorporated the historical trip data that Dopplr has built up over our first year. I quickly came to the obvious conclusion: weight the clustering by the popularity of trip destination and let our travellers decide whether San Francisco or San Jose is the gravitational centre of Silicon Valley.

In analysing the top 2000 destinations I discovered that many of the top cities are very close together — for example, Glasgow and Edinburgh are only 40 miles apart. Again I used our trip data to eliminate overlaps. Within any 50 miles radius, only the most popular of two popular cities gets to be the cluster centre. This decision is one reason for the beauty of our central Raumzeitgeist visualisation. The layout has an appealing rhythm to it because the points in popular areas are a natural and fairly efficient circle packing.

The map of Cluster Cities visited in 2007 is what we’re using in the Raumzeitgeist image, and we’ve made a KML file for you to explore it in Google Earth that you can download here, and we hope you create some of your own images / visualisations from the data.

Aaron Straup Cope who helped me create the main image also did some fun visualisations based upon mashing it up through our API with Dopplr’s city colour-coding (as described previously) that I’ve illustrated this post with.

If you make something shiny – tag it “raumzeitgeist“, or let us know and we’ll try to blog it here.

Have fun!