The focus of the session will be on concepts, tools, and services for handling, maintaining, and using mathematical software or mathematical knowledge more generally. Mathematical software is indispensible for scientific research but also plays a central role mediating between mathematics and applications. It embodies a great deal of mathematical knowledge, and sometimes directly requires developing more. Key technologies use mathematical software for computer simulations. But the development of an efficient infrastructure for mathematical software is challenging: software development is distributed, software has a life cycle, usage conditions vary, and standards for handling of software information are lacking. In addition, the incorporation of software into the scientific record brings to the fore questions of replicability and reproducibility that now extend to mathematical knowledge. With the change in trust for science, and even within it, it is imperative to have clear standards for truth and tools that support them.
The session will cover different aspects and types of software
knowledge management, especially the development of standards,
tools, and services for software, concepts for content analysis,
and semantic interfaces. These are requirements for both improved
facilities for search on mathematical software and automated,
semantically controlled, use of mathematics. The contexts for
mathematical software, especially models, algorithms, and data
and its embedding into the existing information infrastructure of mathematics will be part of discussion. The aim to define the framework for best practices in mathematical software and knowledge management.
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