Introduction. Research data management is a topic of ongoing discussion, particularly in academic institutions, where researchers strive to effectively handle diverse types of data. This study examines the practices of research data management in selected digital humanities projects at Uppsala University. The objective is to as- sess the impact that data management plans (DMPs) on these interdisciplinary projects and evaluate the applica- tion of the FAIR guiding principles. It is crucial to consider the researchers’ perspective on this matter. Universi- ties could invest in robust data management practices by taking into account the needs and skills of researchers. Method. Semi-structured interviews were conducted using purposive sampling targeting researchers from various departments within the Faculty of Arts who were involved in interdisciplinary digital humanities pro- jects. Eight interviews were carried out with principal investigators (PIs) and researchers. Analysis. The interviews, along with the provided DMPs, were thematically analysed to address the re- search questions regarding the effect of DMPs in the selected projects. Results. The study findings indicate that the PIs and researchers do not perceive the DMP as an integral part of their research work in digital humanities projects. Nonetheless, most participants recognise its signifi- cance and its role could be enhanced in research projects. Challenges typically arise during stages of the research data life cycle, such as data analysis, rather than in the development of the DMP itself. Moreover, the practical implementation of the FAIR principles often poses difficulties due to variations in data types and project goals. Conclusion. The results of this study highlight the need for more actionable DMPs in digital humanities projects and further training for researchers on data management issues. The interdisciplinary nature of these projects facilitates collaboration among researchers in the development of DMPs.

Introduction. This thesis analyzes how researchers views the data management plans, how they use them and how they interact with the data support functions at the university. Theory & Method.  The theoretical underpinnings of the study are Janken Myrdals theory of the research method as signifier of natural or humanistic research, and the research method is semi-structured interviews. The study’s empirical material consists of six interviews with researchers from four different scientific fields, which have been transcribed and processed through a qualitative thematic and comparative analysis. Results & Analysis. Five main themes have been identified: (1) bureaucratic demands, (2) a lack of support or a lack of interest?, (3) the data management plans connection to ethical review, (4) the impact of the method on the view of the data management plan, (5) time constraints and the plan as support in the research work. Conclusions. Researchers experience of working with data management plans does not give an unambiguous picture: some see it as an administrative burden or as something of a time sink. Others view it as something that benefits both their own work and when collaborating with colleagues. Moreover divided views exist regarding the support offered by the university when working with data management plans. Some respondents view it as adequate while others suggest that researchers needs to inform themselves on how to write the plan.

Submitted by Elizabete Cristina de Souza de Aguiar Monteiro null (beteaguia@yahoo.com.br) on 2017-03-16T13:34:19Z No. of bitstreams: 1 dissertação final repositorio.pdf: 2620985 bytes, checksum: 7f381cc199ed6199b0c4323398fde01a (MD5) / Approved for entry into archive by LUIZA DE MENEZES ROMANETTO (luizamenezes@reitoria.unesp.br) on 2017-03-16T13:44:52Z (GMT) No. of bitstreams: 1 monteiro_ecsa_me_mar.pdf: 2620985 bytes, checksum: 7f381cc199ed6199b0c4323398fde01a (MD5) / Made available in DSpace on 2017-03-16T13:44:52Z (GMT). No. of bitstreams: 1 monteiro_ecsa_me_mar.pdf: 2620985 bytes, checksum: 7f381cc199ed6199b0c4323398fde01a (MD5) Previous issue date: 2017-02-20 / A enchente de dados científicos nos últimos anos apresenta desafios e novas oportunidades. Os desafios incluem a otimização no uso e reuso de dados e as oportunidades, no desenvolvimento de infraestrutura com implementação de repositórios de dados e todas as atividades inerentes a eles como gerenciamento, descrição, disseminação, integração, direitos autorais, privacidade, quando devida, qualidade e preservação de conjunto de dados. O Plano de Gerenciamento de Dados é um documento composto por diretrizes que orientam os pesquisadores na articulação para liberarem seus conjuntos de dados que ficarão depositados nos repositórios. As diretrizes descritas no Plano de Gerenciamento de Dados precisam ser explícitas em relação às questões sobre direito autoral. O licenciamento de dados estabelece claramente os termos de uso evitando problemas jurídico futuros. As licenças Creative Commons e as Open Data Commons são usadas para licenciar dados e justificam o objetivo dessa pesquisa que consistem em investigar como os repositórios de dados das cem melhores universidades do mundo explicitam em seus Planos de Gerenciamento de Dados as recomendações relacionadas aos direitos autorais dos dados. A metodologia utilizada foi baseada na pesquisa quantitativa e qualitativa, incluindo estudo exploratório-descritivo. A coleta de dados foi realizada nos Planos de Gerenciamento de Dados dos repositórios implementados nas 100 melhores universidades do mundo. Os resultados demostram que a maioria das universidades analisadas implementaram repositório de dados, porém não são todos os repositórios que dispõe de PGDs e de orientações relacionadas aos direitos autorais. / The flood of scientific data in recent years presents challenges and new opportunities. Challenges include optimizing the use and reuse of data and opportunities, developing infrastructure with implementation of data repositories and all activities inherent to them such as management, description, dissemination, integration, copyright, privacy, where appropriate, quality and preservation of data set. The Data Management Plan is a document composed of guidelines that guide the researchers in the articulation to release their datasets that will be deposited in the repositories. The guidelines outlined in the Data Management Plan need to be explicit in relation to copyright issues. The licensing of data clearly establishes the terms of use avoiding future legal problems. Creative Commons and Open Data Commons licenses are used to license data and justify the aims of this research which consists of investigating how the data repositories of the world's top 100 universities spell out in their Data Management Plans the recommendations related to copyright of data. The methodology used was based on quantitative and qualitative research, including an exploratory-descriptive study. The data collection was done in the Data Management Plans of the repositories implemented in the 100 best universities in the world. The results show that most of the universities analyzed have implemented a data repository, but not all repositories have PGDs and copyright guidelines.

Introduction: The subject of research data management is highly topical and university libraries around the world are working hard to establish a well-functioning support as well as technical solutions to deal with sharing and storing research data. Swedish university libraries are no exception, and this study aims to give a clearer view on how these support functions have come to take the form they have today, what they look like now and what the plans are.  Method: For this study eight people working with research data support at six Swedish university libraries were interviewed about the work of the support groups they are part of. These interviews were recorded and transcribed, and then analysed thematically by colour coding themes in the text.  Analysis and results: The findings show that the persons working with data managing support at these six university libraries agree on many points of how the support needs to be developed to meet the students and researchers needs. One of the most important things of what the research data managing groups need to do are to supply more information sessions, workshops, and teaching to reach out with their knowledge and to make people more aware of their existence and competences. Another is making sure technical solutions are in place to store data throughout the different steps of the research data lifecycle. The training and development of the professionals working in the support groups is also a very important part, as this is a changing subject and the rules and regulations do change. Lastly the interviewees underline the importance of solid motivating factors for researchers to share their data. The data support groups can simplify the process of data sharing and make it easier and smoother for the researcher to do it, but if it is unclear why it should be done it will not happen.  Conclusions: The development of the research data support has been, and is, slow and still ongoing. There is still a fair amount of work to be done, especially when it comes to the technical solutions that will enable safe and FAIR data sharing and storing. But the work that needs to be done cannot come only from university libraries and other university support functions, it must come from publishers, funders and other organisations that have the power to change the norms of data sharing. One of the main blockers of open data today is the lack of motivation for researchers to share their data and to be able to reach the goal of open data 2026 the entire system of merits for researchers needs to change and somehow include data sharing as an important part.  This is a two-year master’s thesis in Library and Information Science.