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In 2017 an online survey of University of Reading staff active in or supporting research and registered PhD students was undertaken to assess the nature and extent of research programming and software development activities in the University, and to understand how the University might provide guidance, training and support. The survey was a administered by the Research Data Manager on behalf of the University's Research Data Management Steering Group. The survey ran from 1st November to 15th December 2017 and collected a total of 170 responses. The survey sought responses from anyone in the University who was involved in any of the following activities: writing code and using software for numerical and statistical analysis; creating and contributing to computational models or simulations; conducting Text and Data Mining (TDM) and content analysis; creating and contributing to software distributed as a product or implemented as a service; creating data visualisations; using markup languages to structure and render content. The survey was distributed using the Bristol Online Survey. A dataset of anonymised survey responses and a PDF of the survey questions are here included.
code, Research Data Management, research software, programming
code, Research Data Management, research software, programming
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 10 | |
| downloads | 9 |

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