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| Paper: |
The ALMA Data Mining Toolkit I: Archive Setup and User Usage |
| Volume: |
485, Astronomical Data Analysis Software and Systems XXIII |
| Page: |
147 |
| Authors: |
Teuben, P.; Pound, M.; Mundy, L.; Looney, L.; Friedel, D. N. |
| Abstract: |
We report on an ALMA development study and project where we employ a
novel approach to add data and data descriptors to ALMA archive data
and allowing further flexible data mining on retrieved data. We call
our toolkit ADMIT (the ALMA Data Mining Toolkit) that works within the Python based CASA environment. What is described here is a design
study, with some exiting toy code to prove the concept.
After ingestion of science ready datacubes, ADMIT will compute a
number of basic and advanced data products, and their
descriptors. Examples of such data products are cube statistics, line
identification tables, line cubes, moment maps, an integrated
spectrum, overlap integrals and feature extraction tables. Together
with a descriptive XML file, a small number of visual aids are added
to a ZIP file that is deposited into the archive. Large datasets
(such as line cubes) will have to be rederived by the user once they
have also downloaded the actual ALMA Data Products, or via VO services
if available. ADMIT enables the user to rederive all its products with
different methods and parameters, and compare archive product with
their own. |
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