The Research Data Working Group of the Digital Scientific Library (BSN10) launched in 2015 an inventory of French research data management services, which will be referenced in the future online catalog Cat OPIDoR. This initiative echoes the national and international political context, in which governments and funding agencies gradually implement open science policy frameworks, whereas research activities are also altered by the ubiquity of data and the computing capacities to generate, mine and distribute them. It aims to help research teams to identify services most able to provide them appropriate data management support and to inform political stakeholders about where resources investment is needed.
Research data management (RDM) services have become a high priority for government agencies and post-secondary institutions across Canada in recent years. There is a strong sense of urgency: Canada has lacked coherent national strategies such as those in Australia or the UK, and at the same time there are growing expectations for sound RDM practices. For example, Canada's Action Plan on Open Government includes deliverables aimed at improving access to publications and data resulting from federally funded scientific activities, and the federal research granting councils will be adopting a Statement of Principles on Digital Data Management in 2016 that will be reviewed and revised through continual stakeholder engagement. Amongst those stakeholders are the research universities of the country, including their libraries. Canadian university libraries have a long history of the kinds of collaborations required in the multi-stakeholder RDM environment, deep experience in developing programs to advance research, and critical expertise in preservation. In 2015, the Canadian Association of Research Libraries (CARL) launched a national research data management network, named Portage, to assist researchers and other RDM stakeholders through a university library-based network of expertise on RDM and through working with multiple stakeholders to develop national platforms for planning, preserving, and discovering research data. This work has proceeded in concert with the RDM priorities of university presidents and research administrators, as well as federal research granting councils and agencies responsible for advanced research computing and the national high-speed optical research network. This paper will describe approaches taken to aligning RDM services across multiple stakeholder groups in Canada and discuss various factors to be considered in such collaborations.
Good Research Data Management (RDM) is a key component of research integrity and reproducible research. Consequently, more and more funding bodies, governments, research institutions and other agencies have emphasised the value and importance of good data management and introduced policies on data management and sharing. However, in order to comply with these policies, researchers need support. So how to provide effective support for research data management? What are they key elements? What are the existing components which can be re-used and adapted from elsewhere? And finally, how to engage with researchers about research data and how to make them interested in these topics and use the tools and services developed for them? The aim of this interactive workshop is to address these questions and to provide the participants with tangible solutions they can take away with them to get started with RDM support at their institutions.
The Swedish National Data Service (SND) is a national infrastructure facilitating access to research data. SND supports accessibility, preservation, and re-use of data and related material. Research data from any subject area can be described in and published via the SND research data catalogue. This repository is CoreTrustSeal-certified, and published datasets are provided with DOI persistent identifier. The SND network: •SND is run by a consortium of nine universities, of which the Swedish University of Agricultural Sciences (SLU) is one. ( ) •The SND Network consists of 34 universities and governmental authorities, including the consortium members. ( ) •The network's purpose is to support Swedish researchers in making their data available and FAIR. •All members of the network have agreed to establish a local support function for researchers, a so-called Data Access Unit. The consortium universities contribute expert knowledge to SND in the form of domain specialists. The Swedish University of Agricultural Sciences (SLU) provides expertise in climate and environmental data. The domain specialists •act as a bridge between SND and researchers. •advice on domain specific matters such as standard vocabularies and metadata standards. •are involved in information and education initiatives. •monitor the research data development in their domain. •participate in national and international collaborations. •work towards an increased understanding, use, and publication of open research data. DCU - The Data Curation Unit at SLU DCU is a support organization for researchers and environmental analysts at SLU regarding research data management. DCU acts as the SLU Data Access Unit for SND. The unit assists in the publication and archiving of research data, mainly through education and support. DCU combines several areas of competence found at SLU: competence and expertise in matters regarding both library and archive as well as climate and environmental data. What does DCU do for researchers? •Assists in the preparation of ...
The ongoing digitalization of academic work processes has led to a shift in academic work culture where researchers are supposed to take on more responsibility in term of adequate data management. Third party funding institutions as well as high class journals are increasingly asking for standardized data management processes and started to set up policies which should guide researchers to manage their data properly. In this work, we deal with the highly IS relevant topic of research data management (RDM) and provide an overview of the different existing research data management guidelines of the eight biggest governmental funded institutions and the biggest politically-independent institution. All existing guidelines of those institutions were considered in a qualitative analysis, summarized and evaluated. It has been found that non-technical requirements evolve to non-technical barriers, which institutions need to address to a greater extent within their guidelines to promote scientific research. This work shows the shift in the understanding of RDM and provides the present perspective which help researchers to better understand the ongoing trend of RDM within science.
Research data management (RDM) is a major priority for many institutions as they struggle to cope with the plethora of pronouncements including funder policies, a G8 statement, REF2020 consultations, all stressing the importance of open data in driving everything from global innovation through to more accountable governance; not to mention the more direct possibility that non-compliance could result in grant income drying up. So, at the coalface, how do we become part of this global movement? In this article the author explains the approach being taken at the University of St Andrews, building on the research information management infrastructure (data, systems and people) that has evolved since 2006. Continuing to navigate through the rapidly evolving research policy and cultural landscape, they aim to establish services to support their research community as it moves to this 'open by default' requirement of funders and governments.
Collecting, processing and analyzing data are central activities for virtually every researcher. Hence, topics such as data sharing and the so-called FAIR data principles are becoming increasingly important. This course is meant to give a general, discipline-independent introduction to research data management with a special focus on questions related to data publication and open data. The presentation took place on 7 March 2022 and was part of the event series "Open for you! An introduction series to open science" organized by the 4EU+ University Alliance. ; Co-funded by the Erasmus+ Programme of the European Union.
This document is the first out of three iterations of the DMP that will be formally delivered during the project. Version 2 is due in month 24 and version 3 towards the end of the project. The DMP thus is not a fixed document; it evolves and gains more precision and substance during the lifespan of the project. In this first version we describe the planned research data sets related to the RAGE evaluation and validation activities, and the fifteen principles that will guide data management in RAGE. The former are described in the format of the EU data management template, and the latter in terms of their guiding principle, how we propose to implement them, and when they will be implemented. This document is thus first of all relevant to WP5 and WP8 members. ; This publication has been produced in the context of the RAGE project. The project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. However, this deliverable reflects only the author's view and the European Commission is not responsible for any use that may be made of the information it contains.
Election studies present a research data management challenge due to the size and diversity of the data they collect in a concentrated period. We consider how data infrastructure can support election studies to ensure the data they produce is good quality reusable comparative data. Election studies are critical large-scale data investments. When fully realised, election studies provide an unparalleled spatial and temporal resource for studying social attitudes and political behaviour. They have contemporary value for researchers but also as long-term data investments with prospective comparison across time and in comparative cross-national analyses. However, election studies operate under circumstances exceptional to other long-term longitudinal or repeated cross-sectional studies. Elections may occur at irregular intervals or as sudden 'snap' elections. Consequently, studies may have a concentrated period to design and collect data. Here the risk is that data management concerns are relegated to irrelevant or secondary consideration under the pressure to produce publications, with the result that data is not comparable across either time or spatial units. We seek to ensure election studies produce well-documented data, collected in compliance to recognised data harmonisation standards by ensuring data management planning and metadata are incorporated and implemented in the design and execution of the research.
What is ���research data��� for music researchers and performers? How can music librarians develop their knowledge and skills to better meet the research data needs of their constituents, and contribute to the data-intensive turn in academia? This panel will explore the research data movement in libraries and its relevance to music librarians. Panelists will examine the diversity of music research from a data-oriented perspective, and provide examples of these data as drawn from case studies of various music research projects. We will discuss who creates the data, and how it is used, reused, shared, and discovered, as well as the types of music data appropriate for deposit in an institutional repository. Examples of topics covered will include personal archiving, institutional repository guidelines for data, ethical and intellectual property rights considerations, and the role of research data in music digital humanities projects. Attendees will gain an understanding of how music librarians can participate in research data services at their institutions, as well an understanding of the expertise they can contribute to data-related conversations.
This paper charts the steps taken and possible ways forward for the University of Warwick in its approach to research data management, providing a typical example of a UK research university's approach in two strands: requirements and support. The UK government approach and funding landscape in relation to research data management provided drivers for the University of Warwick to set requirements and provide support, and examples of good practice at other institutions, support from a central national body (the UK Digital Curation Centre) and learning from other universities' experiences all proved valuable to the University of Warwick. Through interviews with researchers at Warwick, various issues and challenges are revealed: perhaps the biggest immediate challenges for Warwick going forward are overcoming scepticism amongst researchers, overcoming costs, and understanding the implications of involving third party companies in research data management. Building technical infrastructure could sit alongside and beyond those immediate steps, and beyond the challenges that face one University are those that affect academia as a whole. Researchers and university administrators need to work together to address the broader challenges, such as the accessibility of data for future use and the reward for researchers who practice data management in exemplary ways, and indeed it may be that a wider, national or international but disciplinary technical infrastructure affects what an individual university needs to achieve. As we take these steps, universities and institutions are all learning from each other.
In the last two decades, due to the vast quantities of born-digital data produced in a wide variety of forms (texts, images, audio and video recordings, codes a.s.o.) and file formats and to the evolution of tools for dealing with, research data management (RDM) became one of the main topics of interest for scientists and information professionals, as a part of good research practice. The preservation, sharing and re-use of research data are requested not only by scholars, but also by governmental agencies, public and private funders, or publishers. The possibility to verify the research findings is complemented, under the extension of open access movement, by the facilitation of new research based on the output of the existing one. The universities and their libraries are among the institutional stakeholders that have begun to address these issues, becoming engaged in developing policies, services, and infrastructure for RDM.
This paper addresses how working on research data management and data sharing gives libraries an unparalleled entrée into the research scholar's network. I believe libraries must grasp this opportunity to collaborate with faculty researchers because we are in the business of making research products accessible and shareable. In many countries of the PRDLA membership, government mandates on data management and data sharing, especially for sponsored research, makes it urgent that libraries gear up to provide a way to help researchers manage their data efficiently. This paper will address the opportunities, the challenges and ways we can engage in best practices among librarians and archivists in this dynamically changing field.
This document is the second out of three iterations of the DMP that will be formally delivered during the project. Version 3 is due towards the end of the project. The DMP thus is not a fixed document; it evolves and gains more precision and substance during the lifespan of the project. This version 2 of the DMP is informed by the following project results: 1) In January 2016 WP8 delivered D8.1 - RAGE Evaluation Framework and Guidelines including extensive guidelines on how to apply the principles of ethics, privacy and open access in the RAGE evaluations; 2) In July 2016 the Executive Management Board selected the OpenAIRE-Zenodo as the preferred open access repository to manage the consortium's research data. The selection of Zenodo addresses a number of issues that were left open in version 1 of this DMP; 3) In November 2016 WP8 delivered the MS8 - First Pilot Validation Instruments document, outlining procedures and tools to be used in the pilot evaluations, including a chapter on the use of Zenodo. The MS8-document provides an update of the data sets that will be generated as part of the pilot evaluations, as compared to the data sets initially specified in version 1 of this DMP. This document is thus first of all relevant to WP5 and WP8 members. ; This study is part of the RAGE project. The RAGE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.
The Council of European Social Science Data Archives (CESSDA) is an association of European nation archives working in cooperation to develop a European wide data infrastructure. Part of CESSDA's activities will be promoting Research Data Management training and support through and along with member archives. The aim of this panel is to provide a comparative forum, informing participants on funding environments and data sharing in different European countries thereby providing a cross-national perspective that can be sometimes ignored. This panel brings together representatives from CESSDA member archives to illustrate the social science data sharing requirements and reuse culture in their countries as well as display the work they are doing archiving data for reuse and providing Research Data Management support services. From this panel session we hope to identify commonalities, differences, obstacles, solutions, in the European experience and potential progress strategies for the CESSDA as it addresses the best way to coordinate European wide training and support on RDM, including support for European Union Horizon 2020 research projects. Although the session is focused on the European experience, it welcomes and strongly encourages international perspectives.
