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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.

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.

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 paper describes the plans and strategies to develop Portage, a national network of sustainable, shared services for research data management (RDM) in Canada. A description of the RDM context in Canada is provided. This environment has heightened expectations around the Government of Canada's Open Science plans and includes deliverables aimed at improving access to publications and data resulting from federally funded scientific activities. At the same time, a recent environmental scan published by Canada's three federal research granting councils reveals significant gaps in services, infrastructure, and funding mechanisms to support RDM. In addition, Canada's RDM environment consists of stakeholders from a variety of communities with minimal ongoing coordination or cooperation. The Portage network was conceived as a collaborative network model based on libraries' strong connections with researchers across the disciplines, an ethos of curation and preservation, and experience with systems for managing data in all its forms. A pilot project provided Portage with a vision and set of principles, and identified several objectives as the small wins that would build the trust and shared understanding required for a successful network. Current services and activities of Portage, including a data management planning tool and an infrastructure project, are described in this paper. Portage now faces the challenge of moving from project to operational network, and the challenge of establishing a sustainable governance model. CARL appointed a Steering Committee that will be proposing a full governance model at the conclusion of this transition period. Using a framework of factors identified in the literature, several relevant collaborative and network governance models are being explored.This paper outlines experience to date with Portage and matters under consideration for long-term sustainability, with a goal of engaging international colleagues in discussion and furthering the concepts for the benefit of RDM networks everywhere.

This paper describes the plans and strategies to develop Portage, a national network of sustainable, shared services for research data management (RDM) in Canada. A description of the RDM context in Canada is provided. This environment has heightened expectations around the Government of Canada's Open Science plans and includes deliverables aimed at improving access to publications and data resulting from federally funded scientific activities. At the same time, a recent environmental scan published by Canada's three federal research granting councils reveals significant gaps in services, infrastructure, and funding mechanisms to support RDM. In addition, Canada's RDM environment consists of stakeholders from a variety of communities with minimal ongoing coordination or cooperation. The Portage network was conceived as a collaborative network model based on libraries' strong connections with researchers across the disciplines, an ethos of curation and preservation, and experience with systems for managing data in all its forms. A pilot project provided Portage with a vision and set of principles, and identified several objectives as the small wins that would build the trust and shared understanding required for a successful network. Current services and activities of Portage, including a data management planning tool and an infrastructure project, are described in this paper. Portage now faces the challenge of moving from project to operational network, and the challenge of establishing a sustainable governance model. CARL appointed a Steering Committee that will be proposing a full governance model at the conclusion of this transition period. Using a framework of factors identified in the literature, several relevant collaborative and network governance models are being explored. This paper outlines experience to date with Portage and matters under consideration for long-term sustainability, with a goal of engaging international colleagues in discussion and furthering the concepts for the benefit of RDM ...

Within the agreement on the establishment and promotion of a National Research Data Infrastructure (NFDI), the Federal German Government and the Länder are striving for a discipline-specific service structure for research data, which aims for their long-term storage, safeguarding and accessibility. In the field of the applied urban research, data from different sectors such as administration, buildings, environment, mobility, social affairs must be considered and linked. In this workshop the NFDI4City-initiative met and discussed its overall vision, conceptual solutions as well as data domains inside and across these sectors. The goal of NFDI4City is to create new databased overarching understandings of urban development through standardization and data analysis in the "Urban System".

In recent years, the academic research data management (RDM) community has worked closely with funding agencies, university administrators, and researchers to develop best practices for RDM. The RDM community, however, has spent relatively little time exploring best practices used in non-academic environments (industry, government, etc.) for management, preservation, and sharing of data. In this poster, we present the results of a project wherein we approached a number of non-academic corporations and institutions to discuss how data is managed in those organizations and discern what the academic RDM community could learn from non-academic RDM practices. We conducted interviews with 10-20 companies including tech companies, government agencies, and consumer retail corporations. We present the results in the form of user stories, common themes from interviews, and summaries of areas where the RDM community might benefit from further understanding of non-academic data management practices.

Recent advances in digital technology and the data-driven science paradigm has led to a proliferation of research data, which are becoming more important in scholarly communications. The sharing and reuse of research data can play a key role in enhancing the reusability and reproducibility of research, and data from publicly funded projects are assumed to be public goods. This is seen as a movement of open science and, more specifically, open research data. Many countries, such as the USA, UK, and Australia, are pushing ahead with implementing policies and infrastructure for open research data. In this paper, we present survey results pertaining to the creation, management, and utilization of data for researchers from government-funded research institutes of science and technology in Korea. We then introduce recent regulations stipulating a mandated data management plan for national R&D projects and on-going efforts to realize open research data in Korea.