Session 4: Impact and sustainability through accessible, reusable and open software

09:00 - 09:30 BigDataEurope - The collaborative creation of an open software platform for researchers addressing Europe's societal challenges

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.

09:30 - 10:00 Software sustainability - guidelines for the selfish scientist

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.

10:00 - 10:30 How to tidy up the jungle of mathematical models? A prerequisite for sustainable research software

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.

10:30 - 11:00 Jupyter and IPython facilitating open access and reproducible research

Jupyter notebooks provide a document-based interactive environment for performing and recording computation. Notebook documents contain not only the code that is run, but prose and mathematics for describing the analysis, as well as recording the outputs of the computation, from plain text output to rich interactive media, such as HTML and javascript or images and video. Jupyter notebooks are being deployed widely as computational companions for publications, facilitation reproduction of results, and interactive exploration and modification of analyses, including by prominent scientific discoveries such as the LIGO experiment. Being freely available, open source software, Jupyter and IPython aim to improve the accessibility of reproducible practices in computational science.