Open Access Business Models for Research Funders and Universities

This briefing paper offers insight into various open access business models, from institutional to subject repositories, from open access journals to research data and monographs. This overview shows that there is a considerable variety in business models within a common framework of public funding. Open access through institutional repositories requires funding from particular institutions to set up and maintain a repository, while subject repositories often require contributions from a number of institutions or funding agencies to maintain a subject repository hosted at one institution. Open access through publication in open access journals generally requires a mix of funding sources to meet the cost of publishing. Public or charitable research funding bodies may contribute part of the cost of publishing in an open access journal but institutions also meet part of the cost, particularly when the author does not have a research grant from a research funding body

KE Workshop report: Report Knowledge Exchange workshop Making data count - Research Data and Research Assessment

The possibilities of digital research have altered the production, publication and use of research results. Academic research practice and culture are changing or have already been transformed, but to a large degree the system of academic recognition has not yet adapted to the practices and possibilities of digital research. This applies especially to research data, which are increasingly produced, managed, published and archived, but play hardly a role yet in practices of research assessment. The aim of the workshop was to bring experts and stakeholders from research institutions, universities, scholarly societies and funding agencies together in order to review, discuss and build on possibilities to implement the culture of sharing and to integrate publication of data into research assessment procedures. The report 'The Value of Research Data - Metrics for datasets from a cultural and technical point of view' was presented and discussed. Some of the key finding were that data sharing should be considered normal research practice, in fact not sharing should be considered malpractice. Research funders and universities should support and encourage data sharing. There are a number of important aspects to consider when making data count in research and evaluation procedures. Metrics are a necessary tool in monitoring the sharing of data sets. However, data metrics are at present not very well developed and there is not yet enough experience in what these metrics actually mean. It is important to implement the culture of sharing through codes of conducts in the scientific communities. For further key findings please read the report.