In many ways, data wants to be social. It wants to get out there for people to see, interact with other datasets, and it wants people to talk about it. There aren't that many places for that to happen though. Newly launched BuzzData wants to fill that void. It's pitched as a "social network designed for data."

You might be thinking, "Wait, haven't we seen this before?" Well, yeah. Again, there's something about data that wants to be shared, but no one has quite figured out how to make it work on a large scale.

Like those before it, BuzzData lets you upload datasets and lets people comment on said datasets, but that's where the similarities stop. There are no tools to visualize and explore your data, and the goal is not so much to get people to make as much stuff as they can with the numbers (although that would certainly help support the community), but more to talk about the data and add context.

Once you upload a dataset, you can link to papers or graphics and include attachments. If you make the dataset public, other BuzzData users can follow datasets — like you might follow a question on Quora — and leave comments and suggestions. If you don't have data to share, you can participate just by following others' datasets.

The above, for example, is a dataset I uploaded on Playboy Playmate of the Year body measurements. (We saw how things have changed over the decades a while back.) I was also able to provide links to articles and graphics, so you don't just get a spreadsheet with a link to a source.

If I wanted, I could add collaborators so that that they could help me keep the data up to date.

It's an interesting concept worth exploring. However, unlike a Twitter or a Quora, there's less of an immediate gratification when you use it, so it'll be a challenge to get enough people interested where things are updated frequently. It's one thing to be excited about data and another to be interested enough to participate.

Then again, maybe there will be a Wikipedia-like flourish with all the excitement around data these days.

A couple of weeks ago, Visually, a new infographics-based startup, launched with a warm reception among all the popular tech blogs. I didn't post about it right away for a couple of reasons. The first is that I've been sick for the past couple of weeks, and it's been hard to think in between all the nose-blowing. Seriously, this cold will not die. Secondly, I wasn't sure how I felt about the new site (partially due to the first reason). Now that I've let my thoughts simmer, it's clear that Visually has potential, but it's way too early to tell if it will actually work.

Visually has online tools in the works to make the graphic design process more approachable to the masses, but in its current state, the site is more like a design-heavy Visualizing.org. It's a catalog of infographics, most of them designed as visual snacks, which shouldn't be surprising considering the team. This isn't necessarily a bad thing. I've posted a few of the infographics highlighted on the Visually homepage here on FlowingData. But I can't help but feel it's more about pretty pictures and traffic than it is about making sense of data.

Before I even got a chance to poke around the site, the general sense I got from the designers I follow wasn't very good.

Some weren't happy with their graphics being posted on the site out of context. Many graphics are designed to fit in with text and don't make a whole lot of sense on their own. I get where the designers are coming from, but stuff like this happens regardless on blogs, news sites, etc. At least there's a source link so that people who care can get more information.

The part about Visually that could be a deal breaker for many (and is worth careful consideration) is the terms of service. Correct me if I'm wrong, but this part under User Submissions seems to say that if you upload or share a graphic that you designed, Visually, or rather, something called GraphCast, is allowed to use, edit, and "exploit" your work any which way:

By submitting the User Submissions to GraphCast, or displaying, publishing, or otherwise posting any content on or through the Sites or the Service, you hereby do and shall grant GraphCast a worldwide, non-exclusive, perpetual, irrevocable, royalty-free, fully paid, sublicensable and transferable license to use, modify, reproduce, distribute, prepare derivative works of, display, perform, and otherwise fully exploit the User Submissions in connection with the Sites, the Service and GraphCast’s (and its successors and assigns) business, including without limitation for promoting and redistributing part or all of the Sites (and derivative works thereof) or the Service in any media formats and through any media channels (including, without limitation, third party websites).

The terms are actually specified for a site called graphcast.com, but all you get is an error message: "The service is not available. Please try again later."

Coming back to the tool, Robert Kosara, an adviser to Visually, says that it's disruptive technology. It looks like a stripped down Adobe Illustrator for graphs.

Is it disruptive? I don't know, I haven't used the tool. For the masses, it could be useful. Is it worth $100 to $250 per month? That could be a tough sell. I'm personally fine with my R to Illustrator workflow, but again, I'm not in the target audience.

I asked CEO Stew Langille where he saw Visually in a couple of years. His response:

I see Visually being the most compelling platform for data visualization. The largest community of visualizations, the ability to create and share visualizations, and an educational resource to introduce data viz to the masses. We see ourselves not only increasing the supply of data viz tools and resources, but growing the demand as well. We will be market makers for the industry.

They will get lots of eyeballs for sure. The team and their partners are experts in marketing and social media, so there will be some community that develops. What type of community is still up in the air. For example, Visually has a Twitter tool that lets you compare two accounts. Enter two usernames, and you get an instant infographic. Here's the meat of the graphic comparing @aplusk to @cnn. (It reminds me a lot of this.)

It's great that you can get this big graphic for such little effort, but I'm disinterested. There are lots of people, however, looking for some quick entertainment. For me, Visually is one of those sites that I want to like. There's just not enough there right now for me to get excited about it. Maybe in a couple of years I'll be singing a different tune, but right now, there's still a lot of work to be done.

What are your first impressions?

It's easy to share static graphics. Save an image and then upload it to your own site. Boom, you're done. However, when it comes to interactive graphics, which come in a variety of file formats, it's not as straightforward. The Visualizing Player helps with this:

We love and respect what you create and we know how much effort goes into each piece (it's why everything that gets uploaded to Visualizing is protected under a CC license). One of our core missions here at Visualizing is to build you the best possible platform and the most powerful tools for sharing those creations.

Now when you go to Visualizing, there's an embed code accompanied with each graphic, and it's easy to share any visualization on your own blog or site. The embed works for 7 formats: HTML5, Java, Flash, PDF, Video, Image, and URL.

For example, above is Gregor Aisch's interactive on Europe's energy, and here's Christian Behrens' Flight & Expulsion interactive. Click on the play button on the bottom left to load and start:

There are still a couple of kinks in the player. For one, the player does take a little while to load initially. I wish they'd show a progress bar or a quicker loading static image so that you don't get a blank screen. The URL view is also kind of weird as it basically just loads an entire page in an iframe. Still though, whether you're the one making a visualization or the one sharing it, the player is a good way to get more eyeballs.

[Visualizing | Thanks, Charlene]

Whenever I post a Sankey diagram (for example, here, here, and here), someone always asks how they can make their own. I'm always surprised that so many people have data where the chart type applies, but in any case, I've never had a good answer other than open up Illustrator and do it by hand. DensityDesign tries to make Sankey diagram creation easier with Fineo.

There's some good news and bad news though. The good news is that Fineo is easy to use. Upload a CSV data file, choose the order you want the columns, and you've got your diagram.

The bad news is it's not really a Sankey diagram. In the examples I linked above, you might have noticed a certain flow where you start with a single population, and at each segment there is a split or decay. Fineo, on the other hand, takes a column-by-column data structure and splits by categories on each column, which is actually much more like Parallel Sets, by Robert Kosara and Caroline Ziemkiewicz, but with curves (as Robert pointed out).

In any case, like I said, Fineo is easy to use and makes it easy to create something like the top diagram. Although, you might want to give Parallel Sets a try if Fineo doesn't do it for you.

As for actual Sankey diagrams? I'm afraid my best answer is still do it by hand in Illustrator. Any other suggestions are welcome.

[Fineo via @JeffClark]

Last year Stamen Design received a grant from the Knight News Challenge to design and implement Citytracking, a project to help people gather data about their cities and gain some kind of understanding about it. Dotspotting, the phase of the project, just launched. It makes it much easier to put dots on a map.

There's currently a whole chain of elements involved in building digital civic infrastructure for the public, and these are represented by various Stamen projects and those of others. At the moment, the current hodgepodge of bits — including APIs and official sources, scraped websites, sometimes-reusable data formats and datasets, visualizations, embeddable widgets etc. — is fractured, overly technical and obscure, held in the knowledge base of a relatively small number of people, and requires considerable expertise to harness. That is, unless you're willing to use generic tools like Google Maps. We want to change this. Visualizing city data shouldn't be this hard, or this generic.

The process is pretty simple. Once you've created an account, upload a list of addresses (or latitude and longitude if you like) as CSV, RSS, or an Excel spreadsheet, and Dotspotting will handle the rest (i.e. geocoding and placement). Bam. Map with dots.

Here's the important part of Dotspotting though. It's not just about getting an online map that you can interact with. It's about making location data easier to distribute. After you've made your map and filtered to your liking you can export the geocoded data in most major geo formats or download the map itself. Print, edit, and/or share without having to worry about the technical bits.

[Dotspotting]

Men and women are different. You know that. But do they tweet differently? Tweetolife is a simple application that lets you compare and contrast what men and women tweet about. Simply type in a search term or phrase and compare. For example, search for love, and 63 percent of tweets that contain that word were from women, based on the sample data collected between November 2009 and February 2010.

Similarly, do a detailed query for "hate" (as shown above) to see what words are usually associated. For men, hate is most often used with cynicism, scum, and racism. For women, or in this case tweenage girls it seems, hate is most often used with Bieber, maths, and ew.

You can also see how terms are used by time of day. Below is a search for early lunch, lunch, and late lunch. As you can see, the humps arise accordingly.

While context is bound to be missing from many queries, Tweetolife is still kind of fun to poke around. Can you find anything amusing?

[Tweetolife | Thanks, Amac]

GeoCommons, an open repository of data and maps, launched version 2.0 this week, which is more feature-rich and robust than the first. Two of the major updates have to do with the fast-changing data landscape: amount of data and browser technology.

In this new version, you can load tens of thousands of points no problem, whereas in the previous version, the application grew sluggish.

If you've used GeoCommons before, you'll also notice is the change to the workflow for making your maps. It's now streamlined so that you choose your base map from one of the available popular map providers, upload your data or choose from the repository, and then decide what features you want to show and how you want to show them.

Finally, once you're satisfied with your map, it's easy to embed it, as shown below, which maps homes for sale in Seattle, Washington. And of course what's becoming the norm, GeoCommons now supports both Flash and HTML5, so that you can use the tool and embed your maps for most devices.

There's lots to to play around with, so give it a try for yourself. Plus, it's free to use. There's also an enterprise version, which provides additional functionality for anlaytics and private data storage.

Data Wrangler also seems to do more guesswork, so you can set less specific parameters. Just roll over stuff, and it'll show a preview of possible changes or formatting. Keep the change or easily undo it.

The video below describes what all the tool can do, but it's better to just try it out. Copy and paste your own mangled data or give Data Wrangler a whirl with the sample provided.

I'd be interested to hear what the Google Refine users think of Data Wrangler. I never got the hang of it and seem to always end up writing code rather than learn my way around the menus and clicks. I think I'll be coming back to this one though.

[Data Wrangler via Waxy]

A while back, Google showed how Influenza outbreaks correlated to searches for flu-related terms with Google Flu Trends. It helped researchers and policy-makers estimate flu activity much sooner than with previous methods. Google Correlate is the evolution of Flu Trends in that now you can correlate search trends with not just flu cases, but with your own data or other search queries.

The above, which you already know about, matches flu cases with searches for "treatment for flu." Similarly, the search phrase that correlates highest with "Toyota for sale" is "used Hyundai," as shown below.

You can also see how your data is related geographically. For example, annual rainfall (left) strongly correlates with searches for "disney vacation package." Although, it looks like distance is a strong factor in the latter, which should be a reminder that correlation is different from causation. Google is careful to point this out in their FAQ and explanation of the tool.

Nevertheless, it's fun to poke around and sometimes see the non-sensical correlations. For example, the strongest correlation with "flowingdata" is "how to scan a document," because the growth rates of both seem similar.

There's also a search by drawing function. You draw a time series, and Correlate finds terms that best match that trend. In the below chart, I drew a line (blue) that had steady growth, but plateaued towards present day.

What weird correlations can you find?

[Google Correlate]

You know Matthew Ericson's simple weather mashup? It shows only what you need to know for the day. WeatherSpark is the the opposite of that.

WeatherSpark is a new type of weather website, with interactive weather graphs that allow you to pan and zoom through the entire history of any weather station on earth. Get multiple forecasts for the current location, overlaid on records and averages to put it all in context.

See weather data all the way back to 1948, compare multiple cities, see historical hourly minimums and maximums, and see forecasts from three different sources. By default, you'll see cloud cover, precipitation, and temperature, but you can also view solar elevation, pressure, wind direction, and wind speed.

The interface is still rough, and it has that programmer's feel to it where it's about spitting out as much data output as you can. I don't imagine ever needing to know this much about the weather, but it's fun to click around for the sheer amount of graphage going on. You can also pretend to be a weatherman in your living room.

[WeatherSpark]