Web-based Analysis and Visualization Environment, or Weave for short, is open source software intended for flexible visualization.

Weave (BETA 1.0) is a new web-based visualization platform designed to enable visualization of any available data by anyone for any purpose. Weave is an application development platform supporting multiple levels of user proficiency — novice to advanced — as well as the ability to integrate, disseminate and visualize data at "nested" levels of geography.

It looks like everything is done through a click interface, and you can piece together modules and link them, etc. There is some setup involved, but there are a number of video tutorials and documents to get everything installed.

Source code also available on GitHub.

[Weave]

With the new year, many of you (myself included) and your employers resolved to be more productive this year. You are going to finish that side project. Learn that new language. Run that long distance. You are going to be all that you can be. Then you spent all day in front of the television yesterday while playing Angry Birds. Little did you know, productivity and Angry Birds go hand-in-hand.

Enter Productivity Birds, created and used internally by Stamen.

We’ve used these graphs as the simplest-possible visualization of how we spend our time so we know how we’re doing relative to the budget for a project. Operationally, the data output of these graphs feeds directly into an accrued revenue model that lets us predict our income earlier. The day/week granularity makes it possible to collect the data as a team without making everyone unhappy with management overhead, and the bias toward whole- or half-day increments helps stabilize fractured schedules (not for me, though—my time is probably the most shattered of anyone in the studio).

Calendar time is represented on the horizontal axis and time spent on a project is the vertical. The object of the game is to hit the bird, where a bird over the pig means a risk of losing money, and a bird past the big means a risk of finishing late. The stacked area chart on the bottom shows who has been or is working on the project.

The small app, built with Protovis, is available on GitHub.

[tecznotes]

Seeing how things change over time can be important for a business so that you can figure out what works best. Square, the company that turns your iPhone into a credit card reader, just released Cube, an open-source system to help you visualize time series data. It's built on MongoDB, Node, and D3.

Once you're all setup server-side, it's pretty quick to put together a dashboard, as shown in the video below:

A lot of the boiler plate time series work is done for you via the visualization components, but if you want to dig deeper, you can also access Cube's query and aggregation functions. This gets you sums, medians, minimums, maximums, and some others, as well as clumping by minutes, hours, days, weeks, or months. If you've done this sort of a stuff with your own code before, you know how annoying it can be.

Cube is still a work-in-progress, but with Mike Bostock, now a visualization scientist at Square, this could be something to keep an eye on.

[Cube]

When we make charts and graphs, we usually think of the data abstractions in terms of bars, dots, and other geometric shapes. ImagePlot, from UCSD-based Software Studies, instead makes it easier to use images to understand large collections.

Existing visualization tools show data as points, lines, and bars. ImagePlot's visualizations shows the actual images in your collection. The images can be scaled to any size and organized in any order - according to their dates, content, visual characteristics, etc. Because digital video is just a set of individual still images, you can also use ImagePlot to explore patterns in films, animations, video games, and any other moving image data.

You can do this with other software (like R, for example), but ImagePlot is specifically built to handle lots of images (in the millions) and so it is much more robust, and it's GUI-based, so no programming is required to use the software, which works on Windows, OS X, and Linux. The interface is pretty basic and not totally clear at first, but play around with the sample datasets and you should be able to pick it up fairly quickly.

Here's a zoomed out view of Time Magazine covers:

These are Van Gogh paintings organized by month/year on the horizontal and color on the vertical:

So you can see there's quite a bit of flexibility with the program, which could lead to some fun if you have a large image dataset. Save your results as a high-resolution image or even in animation form.

You can download ImagePlot here, and for more ideas for what you can do with it, check out the Flickr stream.

[ImagePlot | Thanks, Lev]

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]

Inbox Influence is a new tool from the Sunlight Foundation that allows you to see the political contributions of the people and organizations that are mentioned in emails you receive. This easy-to-use tool can be used for researching influence background on corporate correspondence, adding context to newspaper headlines or discovering who is behind political fundraising solicitations.

Available for major browsers, the plugin is straightforward to use. Just install it like you would any other plugin, and then open Gmail in your browser. In the sidebar (where the ads usually are), you'll see contribution information for people in your inbox.

How much political influence is in your inbox?

[Inbox Influence]