Session 4: Impact and sustainability through accessible, reusable and open software
May 11, 2017 : 09:00 - 11:00
Moderator: Timo Borst (German National Library of Economics (ZBW), Germany)
Sören Auer (University of Bonn / Fraunhofer IAIS, Germany)
The management and analysis of large-scale datasets - described by the term Big Data - involves the three classic dimensions volume, velocity and variety. While the former two are well supported by a variety of software components, the variety dimension is still rather neglected but crucial for the integration and analysis of heterogeneous scientific data. In this talk we discuss the principles of Linked Research Data and practical approaches for their implementation using semantic technologies such as the Data Spaces or Knowledge Graphs. As a concrete example, we discuss the collaborative creation of the BigDataEurope Platform, an open software stack for researchers addressing Europe's societal challenges.
Neil Chue Hong (Software Sustainability Institute, United Kingdom)
Software is fundamental to all areas of research and science. The move towards Open Science has made it even more important that software is made accessible, reusable and maintainable: all facets of software sustainability. However we still face the challenge of translating the enthusiasm of the Open Access, Open Data and Open Science vanguards to the wider community of researchers who may lack access to infrastructure, skills and effort. This talk will draw on the experiences of the Software Sustainability Institute in working with the long tail of researchers, including the formation of the Journal of Open Research Software, to present a different perspective of software for Open Science.
Thomas Koprucki (Weierstrass Institute (WIAS), Germany)
Mathematical modeling and simulation (MMS) has now been established as an essential part of the scientific work in many disciplines.
It is common to categorize the involved numerical data and to some extend the corresponding scientific software as research data. Both have their origin in mathematical models. A holistic approach to research data in MMS should cover all three aspects: models, software, and data.
Yet it is unclear, whether a suitable management of the mathematical knowledge related to models is possible and how it would look like.
In this talk, we outline an approach to address this problem based on a flexiformal representation of the mathematical knowledge in publications and research software. We will discuss how this can improve the sustainability of research obtained by mathematical modeling and numerical simulations.
Benjamin Ragan-Kelley (Simula Research Laboratory / Jupyter, Norway)