4 – 5 April 2018
Software in astronomy
More information about this Symposium will be available in October, but mark it on your calendar now because you will want to be there!
Aims and scope
Though astronomy research is now dependent on software, software development, best practices, and management are skills often left to the astronomer to learn and hone on her own. Despite the proliferation of computational methods in the field, software contributions to astronomy are often not considered for reward or promotion.
The explosion of giant and/or complex and/or high throughput data sets in astronomy has led to the need to adopt advanced machine learning and data mining techniques, such as convolutional neural networks, decision trees, support vector machines, and Gaussian mixture models.
Further, to maximise scientific return and reach out to new global communities of participants in the work of cosmic discovery, the establishment and implementation of archival data services in astronomy and space science is increasingly important.
This Symposium will provide information on software engineering skills that are useful for and reasonably attainable by astronomy researchers and cover some of the best practices in software development.
It will cover the issues that arise from having a poor rewards system for software contributions and efforts to improve this situation and will present useful codes that are available for use by researchers.
It will analyse and discuss the problems of balancing the incoming data deluge with well-proportioned Astroinformatics solutions, based on robust and efficient processing/simulation environments and scalable data analytics methods.
It will also invite engagement between the widest European community of astronomers and space scientists with the agencies large and small that provide archival data and associated services.
Some of the topics this Symposium will cover are:
We invite oral and poster presentation proposals.
- Software engineering practices and sustainability
- Impact, recognition, and credit for software contributions
- Software packages for research
- Open and transparent data and software services
- Machine learning and data mining techniques and practices in astronomy
More coming soon!
- Mike Croucher, EPSRC Research Software Engineering Fellow, University of Sheffield, UK
- Bruce Berriman, IPAC, Caltech, US
Alice Allen, Astrophysics Source Code Library (US)
Rein H. Warmels, European Southern Observatory (DE)
Amruta Jaodand, ASTRON (NL)
Matteo Bachetti, Osservatorio Astronomico di Cagliari (IT)
Stephen Serjeant, Open University (UK)
Ofer Lahav, University College London (UK)
A.M.T. Pollock, University of Sheffield (UK)
Paolo Giommi, Agenzia Spaziale Italiana (IT)
Alice Allen, aallen @ ascl.net
Amruta Jaodand, amruta.jaodand @ gmail.com
Stephen Serjeant, stephen.serjeant @ open.ac.uk
Andrew Pollock, a.m.pollock @ sheffield.ac.uk
Updated on Thu Sep 21 17:44:31 CEST 2017