arXiv subjects

Caroline Jay

Publications and source records attributed to Caroline Jay.

25 records · Page 2Linked to original sources

arXiv2021

Understanding Equity, Diversity and Inclusion Challenges Within the Research Software Community

Research software -- specialist software used to support or undertake research -- is of huge importance to researchers. It contributes to significant advances in the wider world and requires collaboration between people with diverse skills and backgrounds. Analysis of recent survey data provides evidence for a lack of diversity in the Research Software Engineer community. We identify interventions which could address challenges in the wider research software community and highlight areas where the community is becoming more diverse. There are also lessons that are applicable, more generally, to the field of software development around recruitment from other disciplines and the importance of welcoming communities.

cs.SE↗

arXiv2020

Software must be recognised as an important output of scholarly research

Software now lies at the heart of scholarly research. Here we argue that as well as being important from a methodological perspective, software should, in many instances, be recognised as an output of research, equivalent to an academic paper. The article discusses the different roles that software may play in research and highlights the relationship between software and research sustainability and reproducibility. It describes the challenges associated with the processes of citing and reviewing software, which differ from those used for papers. We conclude that whilst software outputs do not necessarily fit comfortably within the current publication model, there is a great deal of positive work underway that is likely to make an impact in addressing this.

cs.CY↗

arXiv2020

Understanding scholarly Natural Language Processing system diagrams through application of the Richards-Engelhardt framework

We utilise Richards-Engelhardt framework as a tool for understanding Natural Language Processing systems diagrams. Through four examples from scholarly proceedings, we find that the application of the framework to this ecological and complex domain is effective for reflecting on these diagrams. We argue for vocabulary to describe multiple-codings, semiotic variability, and inconsistency or misuse of visual encoding principles in diagrams. Further, for application to scholarly Natural Language Processing systems, and perhaps systems diagrams more broadly, we propose the addition of "Grouping by Object" as a new visual encoding principle, and "Emphasising" as a new visual encoding type.

cs.HC↗

arXiv2019

Theory-Software Translation: Research Challenges and Future Directions

The Theory-Software Translation Workshop, held in New Orleans in February 2019, explored in depth the process of both instantiating theory in software - for example, implementing a mathematical model in code as part of a simulation - and using the outputs of software - such as the behavior of a simulation - to advance knowledge. As computation within research is now ubiquitous, the workshop provided a timely opportunity to reflect on the particular challenges of research software engineering - the process of developing and maintaining software for scientific discovery. In addition to the general challenges common to all software development projects, research software additionally must represent, manipulate, and provide data for complex theoretical constructs. Ensuring this process is robust is essential to maintaining the integrity of the science resulting from it, and the workshop highlighted a number of areas where the current approach to research software engineering would benefit from an evidence base that could be used to inform best practice. The workshop brought together expert research software engineers and academics to discuss the challenges of Theory-Software Translation over a two-day period. This report provides an overview of the workshop activities, and a synthesises of the discussion that was recorded. The body of the report presents a thematic analysis of the challenges of Theory-Software Translation as identified by workshop participants, summarises these into a set of research areas, and provides recommendations for the future direction of this work.

cs.SE↗

arXiv2019

A Methodology for Using GitLab for Software Engineering Learning Analytics

To bridge the digital skills gap, we need to train more people in Software Engineering techniques. This paper reports on a project exploring the way students solve tasks using collaborative development platforms and version control systems, such as GitLab, to find patterns and evaluation metrics that can be used to improve the course content and reflect on the most common issues the students are facing. In this paper, we explore Learning Analytics approaches that can be used with GitLab and similar tools, and discuss the challenges raised when applying those approaches in Software Engineering Education, with the objective of building a pipeline that supports the full Learning Analytics cycle, from data extraction to data analysis. We focus in particular on the data anonymisation step of the proposed pipeline to explore the available alternatives to satisfy the data protection requirements when handling personal information in academic environments for research purposes.

cs.SE↗

arXiv2019

What Makes Research Software Sustainable? An Interview Study With Research Software Engineers

Software is now a vital scientific instrument, providing the tools for data collection and analysis across disciplines from bioinformatics and computational physics, to the humanities. The software used in research is often home-grown and bespoke: it is constructed for a particular project, and rarely maintained beyond this, leading to rapid decay, and frequent `reinvention of the wheel'. Understanding how to develop sustainable research software, such that it is suitable for future reuse, is therefore of interest to both researchers and funders, but how to achieve this remains an open question. Here we report the results of an interview study examining how research software engineers -- the people actively developing software in an academic research environment -- subjectively define software sustainability. Thematic analysis of the data reveals two interacting dimensions: \emph{intrinsic sustainability}, which relates to internal qualities of software, such as modularity, encapsulation and testability, and \emph{extrinsic sustainability}, concerning cultural and organisational factors, including how software is resourced, supported and shared. Research software engineers believe an increased focus on quality and discoverability are key factors in increasing the sustainability of academic research software.

cs.SE↗

arXiv2018

The State of Sustainable Research Software: Results from the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1)

This article summarizes motivations, organization, and activities of the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1) held in Manchester, UK in September 2017. The WSSSPE series promotes sustainable research software by positively impacting principles and best practices, careers, learning, and credit. This article discusses the Code of Conduct, idea papers, position papers, experience papers, demos, and lightning talks presented during the workshop. The main part of the article discusses the speed-blogging groups that formed during the meeting, along with the outputs of those sessions.

cs.SE↗