Serving and visualizing LCA results on a web page

The deliverable for this working group would be to have **a working web-based application that can serve LCA results to users**.

Specifically, there would be a landing page where:
* the user could pick one or several products/services,
* define a functional unit (reference flow, allocation method, impact assessment method, etc.),
* send this calculation setup to the LCA calculation app,
* and receive the results, which could be visualized using graphs
* and be exported in a variety of format (csv, ecospold, etc.).

The results would be cached for ulterior requests.

A nice-to-have feature would be to let the user submit data to be added to the triplestore database, either by manually entering the data or by a drag-and-drop of a csv file (in a pre-defined format first, but maybe using a ML text classifier in the future).

Foreseeable tasks:
* [x] create a basic Flask project
* [x] host the code on Github, with instructions for "reproducibility"
* [x] set on a structure for the Flask project to reflect the future needed modules
* [x] write basic user functions on the landing page (picking a product, defining a functional unit, etc.)
* [ ] make the LCA calculation module work with dummy matrices, or Exiobase matrix
* [ ] cache the matrix on first request
* [ ] register users' requests and results in a database
* [x] install the Flask app on a droplet with Ubuntu or Fedora
* [ ] develop the converter module, effectively converting a triplestore extract into a 2D matrix
* [x] make a simple widget to be embedded in third-party pages