280 research outputs found
Collaborations Workshop 2019 - Lightning talk - Neil Chue Hong
No full textLightning talk presented at Collaborations Workshop 2019 organised by the Software Sustainability Institute
Collaborations Workshop 2018 - Lightning talk - Neil Chue Hong
No full textPresentation during Collaborations Workshop 2018, https://www.software.ac.uk/cw18
Introduction to the Software Sustainability Institute
No full textNeil Chue Hong, Software Sustainability Institute Director, and Mario Antonioletti, Research Software Engineer, will give an overview of the important role that software plays in research and innovation and describe some of the Instituteʼs activities around the research software community in the UK and in Edinburgh. In particular, Neil & Mario will present different opportunities to collaborate with the Software Sustainability Institute and connect you to a wider research software community.The Software Sustainability Institute [www.software.ac.uk] is based at the Universities of Edinburgh, Manchester, Oxford and Southampton, and draws on a team of experts with a breadth of experience in software development, project and programme management, research facilitation, publicity and community engagement. Some of the most recentcommunity activities in Edinburgh include the Edinburgh Research Software Engineering Community meetings (CERSE) [github.com] and Edinburgh Carpentries (EdCarp) [edcarp.github.io] software engineering and data analysis training workshops.</div
Understanding critical software for UKRI digital research infrastructure
No full textThis scoping study explores key issues around the critical software required to deliver the UKRI digital research infrastructure (DRI), and recommends what help UKRI could provide to support their investments. It also suggests next steps for future research to support DRI.In a complex software ecosystem, understanding what software requires support and investment from UKRI is a complicated task. The Software Sustainability Institute (SSI) examined not just a list of software used by infrastructures, but considered a range of other issues. Our research questions were: What software is used by the UKRI DRI infrastructures researched?What should be considered as ‘critical software’ for UKRI Digital Research Infrastructure?What are the risks to critical software for UKRI Digital Research Infrastructures?How might audits support the infrastructures in preparing for and mitigating risks?To begin to address these questions, the SSI conducted a short study over the course of six months starting in November 2024, interviewing staff from 3 Compute infrastructures (ARCHER2, JASMIN, Isambard-AI) and 3 Data infrastructures (Seshat - part of iDAH, DARE-UK, PSDI) to ascertain details of their set up, funding, software stack, and audit/risk assessment processes, as well as their definitions of ‘critical software’ and opinions on the risks of disruption to the running of their infrastructures. Then, two focus groups were conducted with staff and users of the wider Compute and Data DRI community in order to corroborate and expand on the themes that arose in the interviews. The report explores the software stacks of the 6 infrastructures (Appendix B), and provides illustrations of different ‘critical software’. It looks at risks to software and also addresses the role of audits in understanding and preparing for risks to infrastructures. The report indicates how different parameters – types and size of infrastructure, users, available funding, and where the infrastructures were in their life cycle – influence the choices of software in use, and what this means for the risks to the infrastructures
Preliminary analysis of a survey of research software engineers in the UK.
No full textThis paper presents results from a survey conducted on a new role in academia: the Research Software Engineer (RSE). The survey provides much needed demographic information about the education, field, gender, job satisfaction and career plans of the people of RSEs. The community is found to be highly educated, derive mainly from the hard sciences, and to be predominantly male. Respondents report satisfaction in their jobs, but indicate that career progression is both difficult and opaque. This paper supports a continued discussion about the experience of RSEs and recommends further investigation into this important community.<br/
Dataset - Understanding the software and data used in the social sciences
No full textThis is a repository for a UKRI Economic and Social Research Council (ESRC) funded project to understand the software used to analyse social sciences data. Any software produced has been made available under a BSD 2-Clause license and any data and other non-software derivative is made available under a CC-BY 4.0 International License. Note that the software that analysed the survey is provided for illustrative purposes - it will not work on the decoupled anonymised data set. Exceptions to this are: Data from the UKRI ESRC is mostly made available under a CC BY-NC-SA 4.0 Licence. Data from Gateway to Research is made available under an Open Government Licence (Version 3.0). Contents Survey data &amp; analysis: esrc_data-survey-analysis-data.zip Other data: esrc_data-other-data.zip Transcripts: esrc_data-transcripts.zip Data Management Plan: esrc_data-dmp.zip Survey data &amp; analysis The survey ran from 3rd February 2022 to 6th March 2023 during which 168 responses were received. Of these responses, three were removed because they were supplied by people from outside the UK without a clear indication of involvement with the UK or associated infrastructure. A fourth response was removed as both came from the same person which leaves us with 164 responses in the data. The survey responses, Question (Q) Q1-Q16, have been decoupled from the demographic data, Q17-Q23. Questions Q24-Q28 are for follow-up and have been removed from the data. The institutions (Q17) and funding sources (Q18) have been provided in a separate file as this could be used to identify respondents. Q17, Q18 and Q19-Q23 have all been independently shuffled. The data has been made available as Comma Separated Values (CSV) with the question number as the header of each column and the encoded responses in the column below. To see what the question and the responses correspond to you will have to consult the survey-results-key.csv which decodes the question and responses accordingly. A pdf copy of the survey questions is available on GitHub. The survey data has been decoupled into: survey-results-key.csv - maps a question number and the responses to the actual question values. q1-16-survey-results.csv- the non-demographic component of the survey responses (Q1-Q16). q19-23-demographics.csv - the demographic part of the survey (Q19-Q21, Q23). q17-institutions.csv - the institution/location of the respondent (Q17). q18-funding.csv - funding sources within the last 5 years (Q18). Please note the code that has been used to do the analysis will not run with the decoupled survey data. Other data files included CleanedLocations.csv - normalised version of the institutions that the survey respondents volunteered. DTPs.csv - information on the UKRI Doctoral Training Partnerships (DTPs) scaped from the UKRI DTP contacts web page in October 2021. projectsearch-1646403729132.csv.gz - data snapshot from the UKRI Gateway to Research released on the 24th February 2022 made available under an Open Government Licence. locations.csv - latitude and longitude for the institutions in the cleaned locations. subjects.csv - research classifications for the ESRC projects for the 24th February data snapshot. topics.csv - topic classification for the ESRC projects for the 24th February data snapshot. Interview transcripts The interview transcripts have been anonymised and converted to markdown so that it's easier to process in general. List of interview transcripts: 1269794877.md 1578450175.md 1792505583.md 2964377624.md 3270614512.md 40983347262.md 4288358080.md 4561769548.md 4938919540.md 5037840428.md 5766299900.md 5996360861.md 6422621713.md 6776362537.md 7183719943.md 7227322280.md 7336263536.md 75909371872.md 7869268779.md 8031500357.md 9253010492.md Data Management Plan The study's Data Management Plan is provided in PDF format and shows the different data sets used throughout the duration of the study and where they have been deposited, as well as how long the SSI will keep these records.</span
CSE Webinar: Overview of the Software Citation Guidance for Authors and Journals by the FORCE11 Software Citation Implementation Working Group
No full textCiting software is developing as a common practice. Journals and editors need consistent guidance to provide authors. In this webinar for the Council of Science Editors (CSE), two of the FORCE11 Software Citation Implementation Working Group co-chairs (Daniel S. Katz and Neil P. Chue Hong) discuss the types of software citation, challenges, and recommended approaches. Panelists (Melissa Harrison, August Muench, and Jake Yeston; moderated by Shelley Stall) also share their own experiences around software citation
FAIR in practice reference list
No full textThis is a collection of information curated by the FAIR Practice Task Force of the EOSC FAIR Working Group.
It aims to provide a reading list of published information on efforts to apply the FAIR principles.
Please read the README tab in the spreadsheet for instructions on how to use this resource.Corresponding author for this deposit is Neil Chue Hon
research-software/resosuma-data: 0.4.1
No full textresosuma-data represents activities in the research software sustainability space in the CSV format, where column 1 contains actors in the space, column 2 contains activities, and column 3 contains actees. resosuma-0.4.1.csv fixes issues #3 and #4.Stephan Druskat, Neil Chue Hong, & Daniel S. Katz. (2018). research-software/resosuma-data: 0.4.1 (0.4.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.147345
Research software engineering accelerates the translation of biomedical research for health
No full textResearch software engineering is central to data-driven biomedical research, but its role is often undervalued and poorly understood
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