scholarly journals Støttetenester for forskingsdatahandtering på UiT Noregs arktiske universitet – erfaringar og forslag til beste praksis

2018 ◽  
Vol 10 (1) ◽  
pp. 65-80 ◽  
Author(s):  
Philipp Conzett ◽  
Lene Østvand
Keyword(s):  
Support Services ◽  
Best Practice ◽  
Division Of Labour ◽  
Research Data ◽  
The Arctic ◽  
Skills Development ◽  
Research Data Management ◽  
Practice Recommendations ◽  
Areas Of Interest ◽  
Technical Solutions

This article describes how support services for research data management have been developed and are run at UiT The Arctic University of Norway (UiT). We go through several areas of interest: technical solutions, researcher involvement, division of labour between different units at our institution as well as co-operation with national and international stakeholders, data curation, skills development, training and curriculum development, dissemination, and policy making. Each section concludes with a set of best practice recommendations.

scholarly journals Research data management support

2019 ◽  
Author(s):  
Abdurhman Kelil Ali
Keyword(s):  
Data Management ◽  
Support Services ◽  
Research Data ◽  
The Arctic ◽  
Management Support ◽  
Research Data Management ◽  
Road Map ◽  
Senior Research ◽  
Research Meeting

Good management and sharing of research data is a key principle for UiT The Arctic University of Norway, rooted in the value of increased transparency, reproducibility and reuse as well as increased quality of research. Meeting this aspiration requires operational support services, infrastructure, competence and a road map for different stakeholders. In line with these requirements, UiT has taken important steps to implement the ambition of FAIR research data management. These include the establishment of UiT Open Research Data archive in September 2016. Since then, more than 600 datasets with more than 5000 files have been uploaded, curated and made openly available. Moreover, UiT has been conducting a senior research data project that aims to preserve research data from senior researchers and make them available for future use. Additionally, UiT has adopted a policy for research data management that came into effect in September 2017. The poster outlines and reviews these and other efforts by UiT The Arctic University of Norway to provide support services for FAIR research data management.

scholarly journals The value and impact of cross professional collaborations in developing student information and academic literacy skills at Sheffield Hallam University, UK.

2013 ◽  
Vol 5 (1) ◽  
pp. 38-43 ◽  
Author(s):  
Diane Rushton ◽  
Alison Lahlafi
Keyword(s):  
Best Practice ◽  
Academic Literacy ◽  
Academic Skills ◽  
Literacy Skills ◽  
Lessons Learned ◽  
Skills Development ◽  
Professional Collaboration ◽  
Practice Recommendations ◽  
E Learning ◽  
Student Information

The paper is jointly written by an academic and librarian and discusses the value and impact of two examples of cross professional collaboration at Sheffield Hallam University. The collaborations addressed information and academic literacy skills development of 640 students across four years and involved a librarian, an academic, an academic skills tutor and an e-learning expert. The paper includes analysis on the value and impact of cross-professional collaborations in developing student information literacy (IL) and academic literacy skills. It concludes with discussion of lessons learned and best practice recommendations.

scholarly journals Teaching Open Science

2020 ◽  
Author(s):  
Helene N. Andreassen ◽  
Erik Lieungh
Keyword(s):  
Open Access ◽  
Data Management ◽  
Teaching And Learning ◽  
Open Science ◽  
Research Data ◽  
Open Access Publishing ◽  
The Arctic ◽  
Learning Support ◽  
Research Data Management ◽  
The University

In this episode, we are discussing how to teach open science to PhD students. Helene N. Andreassen, head of Library Teaching and Learning Support at the University Library of UiT the Arctic University of Norway shares her experiences with the integration of open science in a special, tailor-made course for PhD's that have just started their project. An interdisciplinary, discussion-based course, "Take Control of Your PhD Journey: From (P)reflection to Publishing" consists of a series of seminars on research data management, open access publishing and other subject matters pertaining to open science. First published online February 26, 2020.

Generic concepts for organising data management in research projects

2021 ◽  
Author(s):  
Ivonne Anders ◽  
Swati Gehlot ◽  
Andrea Lammert ◽  
Karsten Peters-von Gehlen
Keyword(s):  
Project Management ◽  
Data Management ◽  
Best Practice ◽  
Research Data ◽  
Data Organization ◽  
Research Projects ◽  
General Application ◽  
Roles And Responsibilities ◽  
Research Data Management ◽  
Project Size

<p>Since few years Research Data Management is becoming an increasingly important part of scientific projects regardless of the number of topics or subjects, researchers or institutions involved. The bigger the project, the more are the data organization and data management requirements in order to assure the best outcome of the project. Despite this, projects rarely have clear structures or responsibilities for data management. The importance of clearly defining data management and also budgeting for it is often underestimated and/or neglected. A rather scarce number of reports and documentations explaining the research data management in certain projects and detailing best practice examples can be found in the current literature.  Additionally, these are often mixed up with topics of the general project management. Furthermore, these examples are very focused on the certain issues of the described projects and thus, a transferability (or general application) of provided methods is very difficult.</p><p>This contribution presents generic concepts of research data management with an effort to separate them from general project management tasks. Project size, details among the diversity of topics and the involved researcher, play an important role in shaping data management and determining which methods of data management can add value to the outcome of a project. We especially focus on different organisation types, including roles and responsibilities for data management in projects of different sizes. Additionally, we show how and when also education should be included, but also how important agreements in a project are.</p>

scholarly journals The Informatics Transform: Re-Engineering Libraries for the Data Decade

2012 ◽  
Vol 7 (1) ◽  
pp. 126-138 ◽  
Author(s):  
Liz Lyon
Keyword(s):  
Data Management ◽  
Support Services ◽  
Research Data ◽  
Institutional Research ◽  
Roles And Responsibilities ◽  
Research Data Management ◽  
Data Support

In this paper, Liz Lyon explores how libraries can re-shape to better reflect the requirements and challenges of today’s data-centric research landscape. The Informatics Transform presents five assertions as potential pathways to change, which will help libraries to re-position, re-profile, and re-structure to better address research data management challenges. The paper deconstructs the institutional research lifecycle and describes a portfolio of ten data support services which libraries can deliver to support the research lifecycle phases. Institutional roles and responsibilities for research data management are also unpacked, building on the framework from the earlier Dealing with Data Report. Finally, the paper examines critical capacity and capability challenges and proposes some innovative steps to addressing the significant skills gaps.

scholarly journals Is Democracy the Right System? Collaborative Approaches to Building an Engaged RDM Community

2017 ◽  
Author(s):  
Marta Teperek ◽  
Rosie Higman ◽  
Danny Kingsley
Keyword(s):  
Data Management ◽  
Community Engagement ◽  
Support Services ◽  
Cost Benefit Analysis ◽  
End Users ◽  
Research Data ◽  
Management Support ◽  
Initial Development ◽  
Positive Effects ◽  
Research Data Management

AbstractWhen developing new products, tools or services, one always need to think about the end users to ensure a wide-spread adoption. While this applies equally to services developed at higher education institutions, sometimes these services are driven by policies and not by needs of end users. This policy-driven approach can prove challenging for building effective community engagement. The initial development of Research Data Management support services at the University of Cambridge was policy-driven and subsequently failed in the first instance to engage the community of researchers for whom these services were created.In this practice paper we will describe the initial approach undertaken at Cambridge when developing RDM services, the results of this approach and lessons learnt. We will then provide an overview of alternative, democratic strategies employed and their positive effects on community engagement. We will summarise by performing a cost-benefit analysis of the two approaches. This paper might be a useful case study for any institutions aiming to develop central support services for researchers, with conclusions applicable to the wide sector, and extending beyond Research Data Management services.

scholarly journals Making Sense: Talking Data Management with Researchers

2011 ◽  
Vol 6 (2) ◽  
pp. 265-273 ◽  
Author(s):  
Catharine Ward ◽  
Lesley Freiman ◽  
Sarah Jones ◽  
Laura Molloy ◽  
Kellie Snow
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Ad Hoc ◽  
Research Data ◽  
Creative Commons ◽  
Digital Curation ◽  
Research Data Management ◽  
Making Sense ◽  
Raising Awareness ◽  
Technical Solutions

Incremental is one of eight projects in the JISC Managing Research Data programme funded to identify institutional requirements for digital research data management and pilot relevant infrastructure. Our findings concur with those of other Managing Research Data projects, as well as with several previous studies. We found that many researchers: (i) organise their data in an ad hoc fashion, posing difficulties with retrieval and re-use; (ii) store their data on all kinds of media without always considering security and back-up; (iii) are positive about data sharing in principle though reluctant in practice; (iv) believe back-up is equivalent to preservation. The key difference between our approach and that of other Managing Research Data projects is the type of infrastructure we are piloting. While the majority of these projects focus on developing technical solutions, we are focusing on the need for ‘soft’ infrastructure, such as one-to-one tailored support, training, and easy-to-find, concise guidance that breaks down some of the barriers information professionals have unintentionally built with their use of specialist terminology.We are employing a bottom-up approach as we feel that to support the step-by-step development of sound research data management practices, you must first understand researchers’ needs and perspectives. Over the life of the project, Incremental staff will act as mediators, assisting researchers and local support staff to understand the data management requirements within which they are expect to work, and will determine how these can be addressed within research workflows and the existing technical infrastructure.Our primary goal is to build data management capacity within the Universities of Cambridge and Glasgow by raising awareness of basic principles so everyone can manage their data to a certain extent. We will ensure our lessons can be picked up and used by other institutions. Our affiliation with the Digital Curation Centre and Digital Preservation Coalition will assist in this and all outputs will be released under a Creative Commons licence.

scholarly journals Here, KAPTUR This! Identifying and Selecting the Infrastructure Required to Support the Curation and Preservation of Visual Arts Research Data

2013 ◽  
Vol 8 (2) ◽  
pp. 68-88 ◽  
Author(s):  
Leigh Garrett ◽  
Marie-Therese Gramstadt ◽  
Carlos Silva
Keyword(s):  
Data Management ◽  
Visual Arts ◽  
Best Practice ◽  
Research Data ◽  
Data Management System ◽  
Research Centre ◽  
Research Knowledge ◽  
User Requirement ◽  
Research Data Management ◽  
The Arts

Research data is increasingly perceived as a valuable resource and, with appropriate curation and preservation, it has much to offer learning, teaching, research, knowledge transfer and consultancy activities in the visual arts. However, very little is known about the curation and preservation of this data: none of the specialist arts institutions have research data management policies or infrastructure and anecdotal evidence suggests that practice is ad hoc, left to individual researchers and teams with little support or guidance. In addition, the curation and preservation of such diverse and complex digital resources as found in the visual arts is, in itself, challenging. Led by the Visual Arts Data Service, a research centre of the University for the Creative Arts, in collaboration with the Glasgow School of Art; Goldsmiths College, University of London; and University of the Arts London, and funded by JISC, the KAPTUR project (2011-2013) seeks to address the lack of awareness and explore the potential of research data management systems in the arts by discovering the nature of research data in the visual arts, investigating the current state of research data management, developing a model of best practice applicable to both specialist arts institutions and arts departments in multidisciplinary institutions, and by applying, testing and piloting the model with the four institutional partners. Utilising the findings of the KAPTUR user requirement and technical review, this paper will outline the method and selection of an appropriate research data management system for the visual arts and the issues the team encountered along the way.

scholarly journals Is Democracy the Right System? Collaborative Approaches to Building an Engaged RDM Community

2018 ◽  
Vol 12 (2) ◽  
pp. 86-95 ◽  
Author(s):  
Marta Teperek ◽  
Rosie Higman ◽  
Danny Kingsley
Keyword(s):  
Data Management ◽  
Community Engagement ◽  
Support Services ◽  
Cost Benefit Analysis ◽  
End Users ◽  
Research Data ◽  
Management Support ◽  
Initial Development ◽  
Positive Effects ◽  
Research Data Management

When developing new products, tools or services, one always need to think about the end users to ensure a wide-spread adoption. While this applies equally to services developed at higher education institutions, sometimes these services are driven by policies and not by the needs of end users. This policy-driven approach can prove challenging for building effective community engagement. The initial development of Research Data Management support services at the University of Cambridge was policy-driven and subsequently failed in the first instance to engage the community of researchers for whom these services were created. In this practice paper, we describe the initial approach undertaken at Cambridge when developing RDM services, the results of this approach and lessons learnt. We then provide an overview of alternative, democratic strategies employed and their positive effects on community engagement. We summarise by performing a cost-benefit analysis of the two approaches. This paper might be a useful case study for any institutions aiming to develop central support services for researchers, with conclusions applicable to the wider sector, and extending beyond Research Data Management services.

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