Digital spreadsheets are the "killer app" that ushered in the PC revolution. This is largely because spreadsheets provide a conceptually simple way to do calculations that avoids the mental burdens of programming, especially considerations of control flow, data dependencies, and data structures. Spreadsheets are likely the most popular computational environment on the planet.

However, today's spreadsheet systems have many shortcomings. In particular, spreadsheets suffer from:

• poor scalability because executing formulas within the spreadsheet system has high overhead;
• great difficulty with reuse because there is no concept of encapsulation (and even different length data are problematic);
• great difficulty with transitioning from a spreadsheet to a program to facilitate integration into software systems and improve scalability;
• limited ability to handle complex data because there is no concept of structured data;
• poor readability because formulas must be expressions (not scripts) and any cell may have a formula; and
• limited ability to express calculations because formulas are limited to using a few hundred or so functions provided by the spreadsheet system (or specially coded macros).

The vision of the SciSheets Project is to deliver the power of programming with the simplicity of spreadsheets. At present, many of the SciSheets use cases are motivated by computational challenges encountered by researchers in the biological and chemical sciences. Key features of SciSheets include:

• formulas that are Python expressions or scripts to improve expressiveness and provide access to complex computations in Python packages;
• exporting spreadsheets as standalone Python programs to improve scalability and enable reuse of spreadsheet calculations in other spreadsheets and in programs; and
• hierarchical tables and cells that may have multiple values to handle complex data such as n-to-m relationships.

SciSheets is a web application that is accessed from a web browser. So, no program installation is required to use SciSheets. A beta release of SciSheets is planned for the beginning of 2017. Currently, SciSheets is at an alpha level that is suitable for evaluation purposes. Please contact jlheller@uw.edu if you are interested in doing such an evaluation.

More details can be found in the [SciSheets summary] (https://docs.google.com/document/d/1dOgMzlOWAx5SGB8ev_E02jO79eewbPZ25m37SrK7IAo/edit#heading=h.lmbccclro00t) and the [YouTube video on SciSheets] (https://www.youtube.com/watch?v=N9QQK5n72ZM).

The following is for interested developers. SciSheets makes use of a related project, BaseStack, that provides an easy way to install web applications in VMs.

To install on a virgin VM:

1. Copy ScienceStacks/BaseStack/setup.sh to $HOME

2. bash setup_vm.sh

3. Answer "yes" as required and enter root password

4. cd $HOME

5. git clone --recursive https://github.com/ScienceStacks/SciSheets.git

6. cd SciSheets

7. bash setup.sh

8. Make sure that ~/SciSheets/bin is in your PATH

Note that you will also need to install pandas if you want to make use of its python packages. Also, SciSheets currently runs only in python 2.7.