Initial draft of JOSS paper

paper/paper.bib

@@ -0,0 +1,56 @@
+@article{2011-d3,
+ title = {D3: Data-Driven Documents},
+ author = {Michael Bostock AND Vadim Ogievetsky AND Jeffrey Heer},
+ journal = {IEEE Trans. Visualization \& Comp. Graphics (Proc. InfoVis)},
+ year = {2011},
+ url = {http://idl.cs.washington.edu/papers/d3},
+}
+
+@article{2017-vega-lite,
+ title = {Vega-Lite: A Grammar of Interactive Graphics},
+ author = {Arvind Satyanarayan AND Dominik Moritz AND Kanit Wongsuphasawat AND Jeffrey Heer},
+ journal = {IEEE Trans. Visualization \& Comp. Graphics (Proc. InfoVis)},
+ year = {2017},
+ url = {http://idl.cs.washington.edu/papers/vega-lite},
+}
+
+@inproceedings{2017-voyager2,
+ title = {Voyager 2: Augmenting Visual Analysis with Partial View Specifications},
+ author = {Kanit Wongsuphasawat AND Zening Qu AND Dominik Moritz AND Riley Chang AND Felix Ouk AND Anushka Anand AND Jock Mackinlay AND Bill Howe AND Jeffrey Heer},
+ booktitle = {ACM Human Factors in Computing Systems (CHI)},
+ year = {2017},
+ url = {http://idl.cs.washington.edu/papers/voyager2},
+}
+
+@article{2016-voyager,
+ title = {Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations},
+ author = {Kanit Wongsuphasawat AND Dominik Moritz AND Anushka Anand AND Jock Mackinlay AND Bill Howe AND Jeffrey Heer},
+ journal = {IEEE Trans. Visualization \& Comp. Graphics (Proc. InfoVis)},
+ year = {2016},
+ url = {http://idl.cs.washington.edu/papers/voyager},
+}
+
+@article{2016-reactive-vega-architecture,
+ title = {Reactive Vega: A Streaming Dataflow Architecture for Declarative Interactive Visualization},
+ author = {Arvind Satyanarayan AND Ryan Russell AND Jane Hoffswell AND Jeffrey Heer},
+ journal = {IEEE Trans. Visualization \& Comp. Graphics (Proc. InfoVis)},
+ year = {2016},
+ url = {http://idl.cs.washington.edu/papers/reactive-vega-architecture},
+}
+
+@book{1977-exploratory,
+  title={Exploratory data analysis},
+  author={Tukey, John W},
+  volume={2},
+  year={1977},
+  publisher={Reading, Mass.}
+}
+
+@book{2005-grammar,
+ author = {Wilkinson, Leland},
+ title = {The Grammar of Graphics (Statistics and Computing)},
+ year = {2005},
+ isbn = {0387245448},
+ publisher = {Springer-Verlag New York, Inc.},
+ address = {Secaucus, NJ, USA},
+}

paper/paper.md

@@ -0,0 +1,100 @@
+---
+title: 'Altair: interactive statistical visualizations for Python'
+tags:
+  - Python
+  - visualization
+  - statistics
+  - Jupyter
+authors:
+  - name: Jacob VanderPlas
+    orcid: 0000-0002-9623-3401
+    affiliation: 1
+  - name: Brian E. Granger
+    orcid: 0000-0002-5223-6168
+    affiliation: 2
+  - name: Jeffrey Heer
+    orcid: 0000-0002-6175-1655
+    affiliation: 1
+  - name: Dominik Moritz
+    orcid: 0000-0002-3110-1053
+    affiliation: 1
+  - name: Kanit Wongsuphasawat
+    orcid: 0000-0001-7231-279X
+    affiliation: 1
+  - name: Eitan Lees
+    orcid: 0000-0003-0988-6015
+    affiliation: 3
+  - name:  Ilia Timofeev
+    orcid: 0000-0003-1795-943X
+    affiliation: 4
+  - name: Ben Welsh
+    orcid: 0000-0002-5200-7269
+    affiliation: 5
+  - name: Scott Sievert
+    orcid: 0000-0002-4275-3452
+    affiliation: 6
+
+affiliations:
+  - name: University of Washington
+    index: 1
+  - name: California Polytechnic State University, San Luis Obispo
+    index: 2
+  - name: Florida State University
+    index: 3
+  - name: TTS Consulting
+    index: 4
+  - name: Los Angeles Times Data Desk
+    index: 5
+  - name: University of Wisconsin--Madison
+    index: 6
+date: 07 August 2018
+bibliography: paper.bib
+---
+
+# Summary
+
+Altair is a declarative statistical visualization library for Python.
+Statistical visualization is a constrained subset of data visualization focused on the creation of visualizations
+that are helpful in statistical modeling. The constrained model of statistical visualization is usually expressed
+in terms of a visualization grammar [2005-grammar] that specifies how input data is transformed and mapped to visual
+properties (position, color, size, etc.).
+
+Altair is based on the Vega-Lite visualization grammar [@2017-vega-lite], which allows a wide range of statistical
+visualizations to be expressed using a small number of grammar primitives. Vega-Lite implements a view composition
+algebra in conjunction with a novel grammar of interactions that allow users to specify interactive charts in an few
+lines of code. Vega-Lite is declarative; visualizations are specified using JSON data that follows the
+[Vega-Lite JSON schema](https://github.com/vega/schema). As a Python library, Altair provides an API oriented towards
+scientists and data scientists doing exploratory data analysis [@1977-exploratory]. Altair's Python API emits Vega-Lite
+JSON data, which is then rendered in a user-interface such as the Jupyter Notebook, JupyterLab, or nteract using the
+[Vega-Lite JavaScript library](https://vega.github.io/vega-lite/). Vega-Lite JSON is compiled to a full Vega
+specification [@2016-reactive-vega-architecture], which is then parsed and executed using a reactive runtime that
+internally makes use of D3.js [@2011-d3]. 
+
+The declarative nature of the Vega-Lite visualization grammar [@2005-grammar, @2017-vega-lite], and its encoding in a
+formal JSON schema, provide Altair with a number of benefits. First, much of the Altair Python code and tests are
+generated from the Vega-Lite JSON schema, ensuring strict conformance with the Vega-Lite specification. Second, the JSON
+data produced by Altair and consumed by Vega-Lite provides a natural serialization and file format for statistical
+visualizations. This is leveraged by JupyterLab, which provides built-in rendering of these files. Third, the JSON data 
+provides a clean integration point for non-programming based visualization user-interfaces such as Voyager
+[@2016-voyager,@2017-voyager2].
+
+In addition to [static documentation](https://altair-viz.github.io/), Altair includes a set of Jupyter Notebooks with
+examples and an interactive tutorial. These notebooks can be read by anyone with only a web-browser through
+[binder](https://mybinder.org/).
+
+-![Seattle Weather Interactive Visualization](seattle_weather_interactive.png)
+
+The example above is an interactive Altair visualization of the weather in Seattle. The plot on the *left* shows the
+initial state: a scatterplot showing the temperature and dominant weather type between January and December, and a bar
+chart showing the counts grouped by weather type. The plot in the *middle* shows a brush that the user has drawn to
+focus on the summers; which are dominantly sunny. In the last plot on the *right*, the user has clicked on the a bar
+to filter the scatterplot.
+
+These interactions are achieved through two selections: an interval selection on the scatterplot and a multi selection
+on the bar chart. The selections drive filters in the other plot. The code for this and other examples is in the
+[Altair gallery](https://altair-viz.github.io/gallery/).
+
+# Acknowledgements
+
+We thank the many contributors that created examples, wrote documentation, and reported bugs. You can find an up-to-date
+list of contributors at https://github.com/altair-viz/altair/graphs/contributors.