This practice paper describes an ongoing research project to test the effectiveness and relevance of the FAIR Data Principles. Simultaneously, it will analyse how easy it is for data archives to adhere to the principles. The research took place from November 2016 to January 2017, and will be underpinned with feedback from the repositories. The FAIR Data Principles feature 15 facets corresponding to the four letters of FAIR - Findable, Accessible, Interoperable, Reusable. These principles have already gained traction within the research world. The European Commission has recently expanded its demand for research to produce open data. The relevant guidelines1are explicitly written in the context of the FAIR Data Principles. Given an increasing number of researchers will have exposure to the guidelines, understanding their viability and suggesting where there may be room for modification and adjustment is of vital importance. This practice paper is connected to a dataset(Dunning et al.,2017) containing the original overview of the sample group statistics and graphs, in an Excel spreadsheet. Over the course of two months, the web-interfaces, help-pages and metadata-records of over 40 data repositories have been examined, to score the individual data repository against the FAIR principles and facets. The traffic-light rating system enables colour-coding according to compliance and vagueness. The statistical analysis provides overall, categorised, on the principles focussing, and on the facet focussing results. The analysis includes the statistical and descriptive evaluation, followed by elaborations on Elements of the FAIR Data Principles, the subject specific or repository specific differences, and subsequently what repositories can do to improve their information architecture. (1) H2020 Guidelines on FAIR Data Management:http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf

This document aims to agree on a broad, international strategy for the implementation of open scholarship that meets the needs of different national and regional communities but works globally.Scholarly research can be idealised as an inspirational process for advancing our collective knowledge to the benefit of all humankind. However, current research practices often struggle with a range of tensions, in part due to the fact that this collective (or “commons”) ideal conflicts with the competitive system in which most scholars work, and in part because much of the infrastructure of the scholarly world is becoming largely digital. What is broadly termed as Open Scholarship is an attempt to realign modern research practices with this ideal. We do not propose a definition of Open Scholarship, but recognise that it is a holistic term that encompasses many disciplines, practices, and principles, sometimes also referred to as Open Science or Open Research. We choose the term Open Scholarship to be more inclusive of these other terms. When we refer to science in this document, we do so historically and use it as shorthand for more general scholarship.The purpose of this document is to provide a concise analysis of where the global Open Scholarship movement currently stands: what the common threads and strengths are, where the greatest opportunities and challenges lie, and how we can more effectively work together as a global community to recognise and address the top strategic priorities. This document was inspired by the Foundations for OER Strategy Development and work in the FORCE11 Scholarly Commons Working Group, and developed by an open contribution working group.Our hope is that this document will serve as a foundational resource for continuing discussions and initiatives about implementing effective strategies to help streamline the integration of Open Scholarship practices into a modern, digital research culture. Through this, we hope to extend the reach and impact of Open Scholarship into a global context, making sure that it is truly open for all. We also hope that this document will evolve as the conversations around Open Scholarship progress, and help to provide useful insight for both global co-ordination and local action. We believe this is a step forward in making Open Scholarship the norm.Ultimately, we expect the impact of widespread adoption of Open Scholarship to be diverse. We expect novel research practices to accelerate the pace of innovation, and therefore stimulate critical industries around the world. We could also expect to see an increase in public trust of science and scholarship, as transparency becomes more normative. As such, we expect interest in Open Scholarship to increase at multiple levels, due to its inherent influence on society and global economics.

Wiki4R will create an innovative virtual research environment (VRE) for Open Science at scale, engaging both professional researchers and citizen data scientists in new and potentially transformative forms of collaboration. It is based on the realizations that (1) the structured parts of the Web itself can be regarded as a VRE, (2) such environments depend on communities, (3) closed environments are limited in their capacity to nurture thriving communities. Wiki4R will therefore integrate Wikidata, the multilingual semantic backbone behind Wikipedia, into existing research processes to enable transdisciplinary research and reduce fragmentation of research in and outside Europe. By establishing a central shared information node, research data can be linked and annotated into knowledge. Despite occasional uses of Wikipedia or Wikidata in research, significant barriers to broader adoption in the sciences or digital humanities exist, including lack of integration into existing research processes and inadequate handling of provenances. The proposed actions include providing best practices and tools for semantic mapping, adoption of citation and author identifiers, interoperability layers for integration with existing ‡

Research data management (RDM) is increasingly important in scholarship. Many researchers are, however, unaware of the benefits of good RDM and unsure about the practical steps they can take to improve their RDM practices. Delft University of Technology (TU Delft) addresses this cultural barrier by appointing Data Stewards at every faculty. By providing expert advice and increasing awareness, the Data Stewardship project focuses on incremental improvements in current data and software management and sharing practices. This cultural change is accelerated by the Data Champions who share best practices in data management with their peers. The Data Stewards and Data Champions build a community that allows a discipline-specific approach to RDM. Nevertheless, cultural change also requires appropriate rewards and incentives. While local initiatives are important, and we discuss several examples in this paper, systemic changes to the academic rewards system are needed. This will require collaborative efforts of a broad coalition of stakeholders and we will mention several such initiatives. This article demonstrates that community building is essential in changing the code and data management culture at TU Delft.

In this paper, we explain our strategy for developing research data management policies at TU Delft. Policies can be important drivers for research institutions in the implementation of good data management practices. As Rans and Jones note (Rans and Jones 2013), "Policies provide clarity of purpose and may help in the framing of roles, responsibilities and requisite actions. They also legitimise making the case for investment". However, policy development often tends to place the researchers in a passive position, while they are the ones managing research data on a daily basis. Therefore, at TU Delft, we have taken an alternative approach: a policy needs to go hand in hand with practice. The policy development was initiated by the Research Data Services at TU Delft Library, but as the process continued, other stakeholders, such as legal and IT departments, got involved. Finally, the faculty-based Data Stewards have played a key role in leading the consultations with the research community that led to the development of the faculty-specific policies. This allows for disciplinary differences to be reflected in the policies and to create a closer connection between policies and day-today research practice. Our primary intention was to keep researchers and research practices at the centre of our strategy for data management. We did not want to introduce and mandate requirements before adequate infrastructure and professional support were available to our research community and before our researchers were themselves willing to discuss formalisation of data management practices. This paper describes the key steps taken and the most important decisions made during the development of RDM policies at TU Delft.