This is an exciting opportunity to make a significant contribution to the University’s research strategy by communicating the benefits of, and enabling, open research practices across the range of disciplines at the University of Surrey. You will work across the University, and nationally with the UK Reproducibility Network (UKRN), to accelerate the uptake of Open Research practices. Open Research refers to research which is practiced in a way that is suitably transparent for others to contribute and collaborate, and that enables research to be reproduced. It engenders research improvement and ensures public trust in research.
The UK higher education sector has invested approximately £1bn in academic publishing over the last decade (i). In our view, the principles guiding interactions between UK institutions and academic publishers should be:
Value for money.
Availability of output to all readers without subscription (e.g., open licensing).
Transparency in agreements (e.g., making costs openly available).
Support for and implementation of initiatives such as DORA.
Support for transparent research practices (e.g., around data and code).
Support for text and data mining (at no extra cost).
Active and transparent engagement with expressions of concern.
The UK higher education sector should take these factors into account in discussions with academic publishers, on the understanding that our continuing support of those who do not meet an acceptable standard is not in the long-term interests of the sector.
An Open Research Action Plan is a funded, medium-term programme of cultural change within a research organisation to promote and embed more accessible, transparent and reproducible ways of conducting and communicating research.
The Checklist for an Open Research Action Plan is a practical guide for stakeholders seeking to develop such a programme. It is based on the experience of creating and implementing an Open Research Action Plan at the University of Reading, but it also draws on a range of resources and activities undertaken to promote the growth of Open Research culture in higher education institutions. While its main frame of reference is the UK university sector, the Checklist can be adapted to any local context.
“Scientific knowledge should not be locked behind paywalls, or only available to those who can read and write in English.
Scientific ideas and findings should be shared as quickly as possible.
Scientific work should be judged on its merits, and not on how good a “story” it tells: and so should scientific researchers.
These principles underlie the design of Octopus: a new way to share scientific work that recognises and rewards good practice, and serves the needs of both scientists and science itself….
In Octopus you publish work in units smaller than a “paper”.
You can write and share one of 8 kinds of publication (though we support custom types for different fields and research types):
Problem – a neatly defined scientific problem
Hypothesis/Theoretical Rationale – an original hypothesis relating to an existing published Problem or the rationale for how you think the Problem could be addressed
Method/Protocol – a practical method of testing an existing published Hypothesis
Data/Results – raw data or summarised results collected according to an existing published Method (can be linked to a data repository)
Analysis – a statistical or thematic analysis of existing published Data or Results
Interpretation – a discussion around an existing published Analysis
Translation/Application – “real world” applications arising from an existing published Interpretation
Review – a considered, detailed review of any of the above kinds of publication …”
“We are offering a one-day short course on data management skills for Open Research online in November 2020. It is open to researchers at all career stages, and across all quantitative disciplines in the biomedical sciences (broadly defined). The workshop is free, supported by Cancer Research UK. We especially encourage researchers funded by CRUK to apply. The course aims to teach researchers how to make their work more reproducible, open and robust through the use of data management tools such as R and Git. Attendees will come away with an overview of how open/reproducible data pipelines work, and why they are important, as well as hands-on experience delving into specific tools. The workshop will include four main components:…”