Greetings! I'm happy to announce today the release of Oz 1.4.0.
https://github.com/metasoarous/oz If you're on the Slack #datascience channel, you may have already caught wind of some earlier versions. But in the interest of introducing it more broadly, I'm posting an overview here for those of you who aren't familiar. If you *are* familiar, you may still wish to scroll down to the bottom as there are some new features available in the latest release. *Vega & Vega-Lite* Oz is based on the fantastic Vega & Vega-Lite data visualization JS libraries, and so to really understand what Oz has to offer, it's best to start here. Vega & Vega-Lite are based on the seminal Grammar of Graphics, an approach to data visualization which emphasizes writing declarative descriptions of how properties of data should translate to aesthetic attributes of a visualization. This approach guided the design of the R's popular ggplot2 library, and has since influenced numerous libraries in other languages. Vega & Vega-Lite take this vision further in two important ways: 1. In Vega & Vega-Lite, data visualizations are described using *pure data*. This makes it more declarative, and confers all the benefits we know and love about data-driven programming in Clojure. For instance, you can send a chunk of Vega or Vega-Lite data over the wire from one program to another effortlessly (as Oz does), and load it up in another process without having to worry about the security concerns of executing someone else's code. The bottom line is that Vega & Vega-Lite are philosophically and technically compatible with "the Clojure way" (IT'S. JUST. DATA.). 2. Vega & Vega-Lite take the Grammar of Graphics one step further by introducing a Grammar of Interaction. You can declaratively describe the addition of controls (dropdowns, checkboxes, etc) and interactive properties of the visualization itself (click, hover, etc), and use the data from these interactions to inform other parts of a visualization. For example, you might highlight a set of points in one part of a visualization, and display summary statistics about that selection in another. This is facilitated in part by a general purpose dataflow language as part of the greater spec. Vega itself is highly customizable and flexible, but somewhat verbose and not suitable for day to day visualization tasks. Vega-Lite steps in as a somewhat higher level and more automated flavor which itself compiles down to Vega. I have been using them together for a better part of a year now, and can say without reservation that they are amazing. For years I've longed for a ggplot2 from Clojure, and at long last I've found something that to my surprise has not only matched, but truly surpassed the standard bearer. In short, I'm sold. If you want to get a better sense of Vega, and Vega-Lite in particular, I'd recommend this great talk from the creators at the Interactive Data Lab at the University of Washington in Seattle: https://www.youtube.com/watch?v=9uaHRWj04D4 If you're interested in a (mostly) more philosophical look at Vega & Vega-Lite, and their connections to Clojure philosophy, I did a little talk at a local Clojure meetup which you may find interesting: https://www.youtube.com/watch?v=hXq5Bb40zZY&t=815s *Oz* Oz itself is a very small and focused library, as most of the work falls on Vega & Vega-Lite. It offers the following features: - A REPL API for for pushing vega and vega-lite data to a browser window over websockets, for REPL-based data science workflows - Client side vega and vega-lite Reagent components, for more dynamic usage from ClojureScript apps - A grammar for composing Vega & Vega-Lite together in the context of html as hiccup, for document and dashboard generation - Plot/document publishing/sharing features via GitHub gists, the IDL's live vega editor <http://vega.github.io/editor>, and the new http://ozviz.io The last two features in particular are where Oz really brings some interesting value to the table beyond the role of a minimal wrapper. I have found the ability to create and quickly share visualizations and scientific documents from the comfort of my favorite text editor and REPL a godsend. While the first several years of my programming experience were in notebook environments (Mathematica, MATLAB, Sage, etc), I now find the experience of writing and executing code from a web application a burden. Part of my goal with Oz was to create a viable alternative to this workflow, and so far I've been very pleased. The last piece to this now in place (the ability to share hiccup+vega documents via http://ozviz.io), I'm excited to put this work out more broadly and hear what the community thinks about this approach to the creation and sharing of scientific documents. There are some other updates and improvements which those of you familiar with Oz may wish to take a look at in the changelog, included updated Vega* libs, and some smoothing out of the API and UI (https://github.com/metasoarous/oz/blob/master/CHANGELOG.md). Otherwise, please see the project README for up to date information on how to use the library: https://github.com/metasoarous/oz. Thanks for your time! 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