I've been working on this for a while, so it's probably worth posting something about it.
Palladio is a platform for data visualization and exploration designed for use by humanities researchers. We're in early beta at the moment and will be doing a series of releases throughout 2014. You can read about it and try it out here: http://palladio.designhumanities.org/
I think the website does a pretty good job of explaining the capabilities of the platform, so I'll leave that for the moment. I encourage you to go check it out before reading on, because it will be worth understanding how the platform works to give some context to the discussion below.
So, why am I super-excited about this? Mostly because of the great team, which has the vision, technical skills, theoretical and domain knowledge, and information design chops to pull off this type of project. I consider myself lucky to be able to work with this group.
It's also great to be working on a project like this for a field that is simultaneously very strong on information theory and a bit underserved in terms of some types of tools. This is in stark contrast to my usual enterprise data management and visualization work where the theory tends to be weak but a plethora of tools exist.
In addition to trying to build a tool that incorporates important and underserved aspects of humanistic inquiry, I am excited to work with a team that buys into introducing state-of-the-art concepts around data exploration tools in general. Many of the concepts we are working to implement in Palladio are directly applicable to the types of data exploration problems we find in the enterprise and are concepts rarely expressed in existing tools. Palladio is a great example (one of many great examples) of how the process of humanistic inquiry can motivate the development of methods that are both technically and conceptually applicable in wildly different disciplines.
The thing that initially most impresses people about Palladio is the way that filtering and movement are integral to the visualization. Specifically, the visualizations update and move in real-time as you filter. This is not a new concept, but I don't think I've ever seen it fully implemented in a general-purpose tool. Getting the level of movement right is a design challenge that the team is tackling as a work in progress, but in my opinion this characteristic of real-time updates and movement is a key feature for a data exploration tool, and few if any tools implement it.
I'll try not to get too squishy here, but this behavior of the tool allows a person to interact with the data in a very direct way, giving a feel for the data that would not otherwise exist. When you can see the results of your interactions with the data in real time, it is a lot easier to conceptually link step-changes and interesting events with the actions that caused them. For example, dragging a filter along the timeline component allows you to play back history at your own speed, speeding up or slowing down as suits you. My theory-foo is weak, but when you see it, I think you'll understand. Try it out with the sample data.
The time for client-side data visualization in the browser has come and we are taking advantage of that in a big way. A great strength of browser-rendered visualizations is that they allow true interaction with the visualization. Just using SVG or Canvas as a nicer replacement for static images is fine, but it isn't fully exploiting the medium. Add to this that the type of interactivity we are providing with Palladio is technically impossible in a client-server setup. Even if the server responds to queries instantaneously, the round-trip time the client-server communication introduces means that interactions won't be as closely linked as they are in Palladio, severely degrading the quality of the interactive experience.
Admittedly, we have work to do on performance and our cross-browser support could be better. Additionally, the problem of data that simply doesn't fit in the browser's memory remains unaddressed, though we have some ideas for mitigating the problem. But I think this is an application design approach that could be exploited for the vast majority of data sets out there, either because the data itself is relatively small, or through judicial use of pre-aggregation to avoid performance and size issues.
Lastly, user experience and information design have been integral components of this project from the start. The design has been overhauled several times along the way, and I wouldn't be at all surprised if it happened again. To be clear, I'm a complete design newb, but we have a great designer working on the team. One thing that has become clear to me through this process is that designing a general purpose interactive visualization tool is hard. There are more corner-cases than I previously imagined possible, but we are trying to get the big pieces right and I think we're on the road to success.
Obviously the organizational dynamics on a small team like ours are very different than those in a big development organization, but it seems like information design on most of the enterprise data exploration tools from larger vendors either started out problematic and stayed that way, or started out pretty well and started slipping as the tool took off. I'm not sure if there is an answer to this, but it's clear that when building a tool in this space, having at least one information designer with a strong voice on the team is indispensable.
Let me sum up
It's been a great ride so far and we've got some exciting things planned for the rest of the year. This is definitely a work in progress, and feedback is very welcome. Follow the Humanities + Design lab on Twitter for updates.