SPLAT-VO: Spectral Analysis Tool
SPLAT is a graphical tool for displaying, comparing, modifying and analysing astronomical spectra stored in several file formats. Spectra can be read from local files or retrieved through VO protocols.
Download
SPLAT latest release:
- 3.15.1
- Source code: https://github.com/Starlink/starjava
GAVO beta versions:
- 4-beta (with with LineTap implementation)
- 3.15-3 (with ssap data product type)
Starlink/STARJAVA version:
Description
SPLAT is part of the STARJAVA collection. The main page of SPLAT-VO is maintained by Peter Draper, SPLAT's original developer.
The original SPLAT offered basic VO functionality for searching and selecting spectra using the SSAP protocol.
SPLAT is now being developed by the GAVO (German Astrophysical Virtual Observatory) team, in cooperation with the Astronomical Institute of the Academy of Sciences of the Czech Republic. Our goal is to update SPLAT to keep up with the changing requirements of both end users and data providers. Some of the features present in the latest release are:
- exploring more aspects of the SSAP Protocol (e.g. supporting all available metadata parameters)
- implementation of other/new VO standards like ObsCore, SODA/DataLink, SLAP.
- more flexibility on service selection (tagging a set of services, manually adding new service)
- limited access for non authenticated users
Contact Information
- Contact: Margarida Castro Neves
- Mailing list: http://lists.g-vo.org/cgi-bin/mailman/listinfo/splat-users
- Report Issues: https://github.com/SPLAT-VO/starjava/issues
Developers
The SPLAT Development team at the University of Heidelberg/GAVO:
- Margarida Castro Neves
- Markus Demleitner
Contributors from the Astronomical Institute of the Academy of Sciences of the Czech Republic:
- Petr Skoda (Scientific advisor)
- David Andresic
Original SPLAT developers:
- Peter Draper
- Mark Taylor
SPLAT-VO is in part supported by the ESCAPE project (the European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures) that has received funding from the European Union's Horizon 2020 research and innovation programme under the Grant Agreement n. 824064.