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At [Plotly](Plot.ly), we are excited about the collaboration that Authorea can power. We started Plotly because we have experience similar problems with collaboration. Our problems involved data analysis and visualization. Authorea is about making it easier to collaborate in the writing and publication of your papers. In this article, we'll discuss and demonstrate how Plotly and Authorea together can change the way you collaborate on your data analysis, visualization, and publication.   ##  1.1 Plotly solves three problems: * First, in order to query a database, clean data, analyze data, graph results, share the project, and discuss a project, you have to use too many tools, file types, and technologies. Switching between the jumbles is inefficient, painful, and chaotic.  
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* Third, when you look at a graph in a deck or paper, you can't see or access the data behind it to do your own analysis of that data reproduce or validate those results. The data and graph divide also prevents you from introducing your data to a dataset hidden behind a graph.  ##  1.2 How Plotly solves these problems Plotly lets you make interactive graphs with Plotly's GUI, or [Plotly APIs](Plot.ly/api) in Python, R, MATLAB, REST, Arduino, Julia, Perl, or [IPython Notebooks](nbviewer.ipython.org/github/plotly/IPython-plotly/tree/master/). Plotly also lets you analyze data with fits functions, and a Python sandbox. Share your graphs publicly or as a private file, then edit together with your team, like you would a Google Document. You can comment, save your versions, and easily download, export, or embed your graphs (see _e.g.,_ [this Washington Post article](http://www.washingtonpost.com/blogs/wonkblog/wp/2013/06/14/do-low-taxes-on-the-rich-leave-the-middle-class-with-lower-wages/)).