veyepar: How Web APIs and Data-centric Tools Power the Materials Project

Author(s):	Dan Gunter, Shreyas Cholia
Location	A2
Date	mar Wed 20	Days Raw Files
Start	13:55	First Raw Start	13:47
Duration	00:50:00	Offset	0:07:52
End	14:45	Last Raw End	15:48
Chapters	00:00 0:35:04
Total cuts_time	39 min.

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Python has been an important tool for analysis and manipulation of scientific
data. This has traditionally taken the form of large datasets on disk or in
local databases, which are then processed by sophisticated numerical and
scientific libraries (SciPy and friends). Increasingly, science is becoming a
collaborative enterprise where "big data" is generated in multiple locations
and analyzed by multiple research groups.

In this talk we discuss how Python data analysis can help scientists work more
collaboratively by integrating Web APIs to access remote data. We will discuss
the details of this approach as applied to the Materials Project (see
materialsproject.org), a Department of Energy project that aims to remove the
guesswork from materials design using an open database of computed properties
for all known materials. Using the Python Materials Genomics (pymatgen)
analysis package (see packages.python.org/pymatgen), Materials Project data
can be seamlessly analyzed alongside local computed and experimental data. We
will describe how we make this data available as a web API (through Django)
and how we provide access to both data and analysis under a single library.
The talk will go over the technology stack and demonstrate the potential power
of these tools within an IPython notebook. We will finish by describing plans
to extend this work to address key challenges for distributed scientific data.

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