Research Software Sustainability: Report on Knowledge Exchange Workshop

The report introduces software sustainability, provides definitions, clearly demonstrates that software is not the same as data and illustrates aspects of sustainability in the software lifecycle. The recommendations state that improving software sustainability requires a number of changes: some technical and others societal, some small and others significant. We must start by raising awareness of researchers’ reliance on software. This goal will become easier if we recognise the valuable contribution that software makes to research – and reward those people who invest their time into developing reliable and reproducible software. The adoption of software has led to significant advances in research. But if we do not change our research practices, the continued rise in software use will be accompanied by a rise in retractions. Ultimately, anyone who is concerned about the reliability and reproducibility of research should be concerned about software sustainability. Beside highlighting the benefits of software sustainability and addressing the societal and technical barriers to software sustainability, the report provides access to expertise in software sustainability and outlines the role of funders. The report concludes with a short landscape of national activities in Europe and outside Europe. As a result of the workshop steps will be explored to establish European coordination and cooperation of national initiatives.

The Value of Research Data

Scientific research revolves around the production, analysis, storage, management, and re-use of data. Data sharing offers important benefits for scientific progress and advancement of knowledge. However, several limitations and barriers in the general adoption of data sharing are still in place. Probably the most important challenge is that data sharing is not yet very common among scholars and is not yet seen as a regular activity among scientists, although important efforts are being invested in promoting data sharing. In addition, there is a relatively low commitment of scholars to cite data. The most important problems and challenges regarding data metrics are closely tied to the more general problems related to data sharing. The development of data metrics is dependent on the growth of data sharing practices, after all it is nothing more than the registration of researchers’ behaviour. At the same time, the availability of proper metrics can help researchers to make their data work more visible. This may subsequently act as an incentive for more data sharing and in this way a virtuous circle may be set in motion. This report seeks to further explore the possibilities of metrics for datasets (i.e. the creation of reliable data metrics) and an effective reward system that aligns the main interests of the main stakeholders involved in the process. The report reviews the current literature on data sharing and data metrics. It presents interviews with the main stakeholders on data sharing and data metrics. It also analyses the existing repositories and tools in the field of data sharing that have special relevance for the promotion and development of data metrics. On the basis of these three pillars, the report presents a number of solutions and necessary developments, as well as a set of recommendations regarding data metrics. The most important recommendations include the general adoption of data sharing and data publication among scholars; the development of a reward system for scientists that includes data metrics; reducing the costs of data publication; reducing existing negative cultural perceptions of researchers regarding data publication; developing standards for preservation, publication, identification and citation of datasets; more coordination of data repository initiatives; and further development of interoperability protocols across different actors.

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.