Automating Finite Element Methods for Geodynamics via Firedrake

Firedrake is an automated system for solving partial differential equations using the finite element method. By applying sophisticated performance optimisations through automatic code-generation techniques, it provides a means to create accurate, efficient, flexible, easily extensible, scalable, transparent and reproducible research software, that is ideally suited to simulating a wide-range of problems in geophysical fluid dynamics. Here, we demonstrate the applicability of Firedrake for geodynamical simulation, with a focus on mantle dynamics. The accuracy and efficiency of the approach is confirmed via comparisons against a suite of analytical and benchmark cases of systematically increasing complexity, whilst parallel scalability is demonstrated up to 12288 compute cores, where the problem size and the number of processing cores are simultaneously increased. In addition, Firedrake's flexibility is highlighted via straightforward application to different physical (e.g. complex nonlinear rheologies, compressibility) and geometrical (2-D and 3-D Cartesian and spherical domains) scenarios. Finally, a representative simulation of global mantle convection is examined, which incorporates 230 Myr of plate motion history as a kinematic surface boundary condition, confirming its suitability for addressing research problems at the frontiers of global mantle dynamics research.

Documenting Research Software in Engineering Science

The reuse of research software needs good documentation, however, the documentation in particular is often criticized. Especially in non-IT specific disciplines, the lack of documentation is attributed to the lack of training, the lack of time or missing rewards. This article addresses the hypothesis that scientists do document but do not know exactly what they need to document, why, and for whom. In order to evaluate the actual documentation practice of research software, we examined existing recommendations, and we evaluated their implementation in everyday practice using a concrete example from the engineering sciences and compared the findings with best practice examples. In order to get a broad overview of what documentation of research software entailed, we defined categories and used them to conduct the research. Our results show that the big picture of what documentation of research software means is missing. Recommendations do not consider the important role of developers whose documentation takes mainly place in their research articles. Moreover, we show that research software always has a history that influences the documentation.

Software citation

Nearly all research today has a digital component, and typically, scholarly results are strongly dependent on software. For the research results to be fully understood, the software that is used must be uniquely identified. Research software is frequently developed by researchers themselves, often initially to solve a single problem, and then later generalized to solve additional problems. Ideally, the software is shared so that other researchers can also benefit and avoid the duplicate work required for development and maintenance. The researchers must expect and receive value for their contribution and sharing. Because publishing is a key element of our existing scholarly structures, the research that was done must be clearly explained in papers. This can be used to create incentives for researchers not only to share their software, but also to contribute to community software, in both cases through software citation. Contributors to software that is used in papers and is cited by those papers can become authors of the software as it is tracked by indexes, which also track how often the software is cited.

UCEasy: A software package for automating and simplifying the analysis of ultraconserved elements (UCEs)

The use of Ultraconserved Elements (UCEs) as genetic markers in phylogenomics has become popular and has provided promising results. Although UCE data can be easily obtained from targeted enriched sequencing, the protocol for in silico analysis of UCEs consist of the execution of heterogeneous and complex tools, a challenge for scientists without training in bioinformatics. Developing tools with the adoption of best practices in research software can lessen this problem by improving the execution of computational experiments, thus promoting better reproducibility. We present UCEasy, an easy-to-install and easy-to-use software package with a simple command line interface that facilitates the computational analysis of UCEs from sequencing samples, following the best practices of research software. UCEasy is a wrapper that standardises, automates and simplifies the quality control of raw reads, assembly and extraction and alignment of UCEs, generating at the end a data matrix with different levels of completeness that can be used to infer phylogenetic trees. We demonstrate the functionalities of UCEasy by reproducing the published results of phylogenomic studies of the bird genus Turdus (Aves) and of Adephaga families (Coleoptera) containing genomic datasets to efficiently extract UCEs.

Open Scholarly Metrics for the Journal of Open Source Software

The Journal of Open Source Software (JOSS) is a developer friendly, open access journal for research software packages published as open source software. JOSS started publishing in 2016, and has published more than 1,500 articles so far. ...

ELIXIR Software Management Plan for Life Sciences

Data Management Plans are now considered a key element of Open Science. They describe the data management life cycle for the data to be collected, processed and/or generated within the lifetime of a particular project or activity. A Software Manag ement Plan (SMP) plays the same role but for software. Beyond its management perspective, the main advantage of an SMP is that it both provides clear context to the software that is being developed and raises awareness. Although there are a few SMPs already available, most of them require significant technical knowledge to be effectively used. ELIXIR has developed a low-barrier SMP, specifically tailored for life science researchers, aligned to the FAIR Research Software principles. Starting from the Four Recommendations for Open Source Software, the ELIXIR SMP was iteratively refined by surveying the practices of the community and incorporating the received feedback. Currently available as a survey, future plans of the ELIXIR SMP include a human- and machine-readable version, that can be automatically queried and connected to relevant tools and metrics within the ELIXIR Tools ecosystem and beyond.

CP-DSL: Supporting Configuration and Parametrization of Ocean Models with UVic (2.9) and MITgcm (67w)

Ocean models are long-living software systems facing challenges with increasing complexity, architecture erosion, and managing legacy code. These challenges increase maintenance costs in development and use, which reduces the time and resources available for research. Software engineering addresses these challenges by separation of concerns and modularization. One particular approach is to separate concerns by tailor-made notations, i.e. Domain-Specific Languages (DSLs). Using DSLs, the model developer can focus on one concern at a time without the need to consider other concerns of a software system simultaneously. In ocean and climate models, DSL tooling, like PSyclone and Dusk/Dawn, is used for instance to separate scientific and technical code. CP-DSL complements this approach with a focus on configuration and parametrization, which play an important role in ocean models, especially in parameter optimization and scenario-based simulations. CP-DSL is designed to be model agnostic and provides a unified interface to different ocean models. Furthermore, the DSL can be integrated into tools and processes used by domain experts. In this paper we report on the DSL design, implementation, and the evaluation with scientists and research software engineers. The implementation of CP-DSL is available as open source software and a replication package for configuration and parameterization of UVic and MITgcm is provided.

Software Training in HEP

The long-term sustainability of the high-energy physics (HEP) research software ecosystem is essential to the field. With new facilities and upgrades coming online throughout the 2020s, this will only become increasingly important. Meeting the sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g., Unix, version control, C++, and continuous integration). The second is knowledge of domain-specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving specialized techniques, including parallel programming, machine learning and data science tools, and techniques to maintain software projects at all scales. This paper discusses the collective software training program in HEP led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients for the solution of HEP computing challenges. Beyond serving the community by ensuring that members are able to pursue research goals, the program serves individuals by providing intellectual capital and transferable skills important to careers in the realm of software and computing, inside or outside HEP.