scholarly journals “You say potato, I say potato“ Mapping Digital Preservation and Research Data Management Concepts towards Collective Curation and Preservation Strategies

2020 ◽  
Vol 15 (1) ◽  
pp. 26
Author(s):  
Michelle Lindlar ◽  
Pia Rudnik ◽  
Sarah Jones ◽  
Laurence Horton
Keyword(s):  
Data Management ◽  
Digital Preservation ◽  
Holistic Approach ◽  
Research Data ◽  
Research Data Management ◽  
Management Concepts ◽  
Professional Field

This paper explores models, concepts and terminology used in the Research Data Management and Digital Preservation communities. In doing so we identify several overlaps and mutual concerns where the advancements of one professional field can apply to and assist another. By focusing on what unites rather than divides us, and by adopting a more holistic approach we advance towards collective curation and preservation strategies.  

scholarly journals Teaching Practical Research Data Management Skills through Online Training and Data Management Plan Creation

2019 ◽  
Author(s):  
Beth Montague-Hellen ◽  
Holly Ranger
Keyword(s):  
Data Management ◽  
Academic Research ◽  
Management Plan ◽  
Research Data ◽  
Early Career ◽  
Research Data Management ◽  
Effective Manner ◽  
Management Concepts ◽  
Design Paradigm ◽  
Professional Support Staff

Introduction: Research Data Management is growing in importance as a field as the amount of data which researchers must manage increases. It is important to ensure that postgraduate researchers are trained through engaging courses which practically prepare them to fulfil the data management requirements of funders and Universities, and to carry out their research in a transparent and effective manner. Description of program: We present a case study of the development and delivery of a new Research Data Management (RDM) online course for postgraduates and early career researchers. The course implements pedagogical theory and a reverse design paradigm in the development of library training provision enabling the creation of a course vastly more relevant to academic research practice than our previous offering. The course uses a simplified Data Management Plan to introduce students to Research Data Management Concepts, and by asking them to apply this knowledge, lifts the course from one which simply asks students to remember knowledge to one which shows them how to apply this knowledge in a way that is applicable to their own research. The course has been evaluated for effectiveness and student engagement at 3 months. Next steps: Although some analysis of the effectiveness of the new course has been undertaken, the course will continue to be evaluated. Although the course was developed for PGRs it has been popular with ECRs and Professional support staff and we will investigate how we can further meet the needs of these groups. The platform used will allow for the topics most often accessed to be identified and the course, and the University’s training provision will be adjusted based on this evidence. We hope that other institutions will be able to learn from our experience and implement similar courses.

Managing collaborative research data for integrated, interdisciplinary environmental research

2020 ◽  
Author(s):  
Michael Finkel ◽  
Albrecht Baur ◽  
Tobias K.D. Weber ◽  
Karsten Osenbrück ◽  
Hermann Rügner ◽  
...  
Keyword(s):  
Data Management ◽  
Collaborative Research ◽  
Large Scale ◽  
Full Range ◽  
Research Data ◽  
Environmental Research ◽  
Data Types ◽  
Research Data Management ◽  
Management Concepts

<p>The consistent management of research data is crucial for the success of long-term and large-scale collaborative research. Research data management is the basis for efficiency, continuity, and quality of the research, as well as for maximum impact and outreach, including the long-term publication of data and their accessibility. Both funding agencies and publishers increasingly require this long term and open access to research data. Joint environmental studies typically take place in a fragmented research landscape of diverse disciplines; researchers involved typically show a variety of attitudes towards and previous experiences with common data policies, and the extensive variety of data types in interdisciplinary research poses particular challenges for collaborative data management.We present organizational measures, data and metadata management concepts, and technical solutions to form a flexible research data management framework that allows for efficiently sharing the full range of data and metadata among all researchers of the project, and smooth publishing of selected data and data streams to publicly accessible sites. The concept is built upon data type-specific and hierarchical metadata using a common taxonomy agreed upon by all researchers of the project. The framework’s concept has been developed along the needs and demands of the scientists involved, and aims to minimize their effort in data management, which we illustrate from the researchers’ perspective describing their typical workflow from the generation and preparation of data and metadata to the long-term preservation of data including their metadata.</p>

scholarly journals Collaborative Approaches to Undergraduate Research Training: Information Literacy and Data Management

2014 ◽  
Vol 15 (2) ◽  
pp. 368-389 ◽  
Author(s):  
Hailey Mooney ◽  
W. Aaron Collie ◽  
Shawn Nicholson ◽  
Marya R. Sosulski
Keyword(s):  
Data Management ◽  
Undergraduate Students ◽  
Research Training ◽  
Undergraduate Research ◽  
Meaningful Work ◽  
Holistic Approach ◽  
Research Data ◽  
Research Experience ◽  
Research Data Management ◽  
Faculty Mentors

The undergraduate research experience (URE) provides an opportunity for students to engage in meaningful work with faculty mentors on research projects. An increasingly important component of scholarly research is the application of research data management best practices, yet this often falls out of the scope of URE programs. This article presents a case study of faculty and librarian collaboration in the integration of a library and research data management curriculum into a social work URE research team. Discussion includes reflections on the content and learning outcomes, benefits of a holistic approach to introducing undergraduate students to research practice, and challenges of scale.

scholarly journals Essentials for Data Support: Training the Front Office

2015 ◽  
Vol 10 (1) ◽  
pp. 240-248 ◽  
Author(s):  
Marjan Grootveld ◽  
Ellen Verbakel
Keyword(s):  
Data Management ◽  
Digital Preservation ◽  
Research Data ◽  
Lessons Learned ◽  
Online Resources ◽  
Research Data Management ◽  
Data Support ◽  
Front Office ◽  
Library Staff ◽  
And Training

At the end of 2011 a Data Intelligence 4 Librarians course was developed to provide online resources and training for digital preservation practitioners, specifically library staff. Lessons learned during the first rounds of the course and developments in the Research Data Management landscape have led to a revision of the positioning, the structure and the content of the course. This paper describes both the three main drivers for the revision, the changes themselves and the lessons that can be drawn from them, after three training rounds in 2014 in the revised format under the new programmatic title of Essentials 4 Data Support.

scholarly journals Exploring digital preservation requirements

2017 ◽  
Vol 27 (2) ◽  
pp. 175-191 ◽  
Author(s):  
Jaana Pinnick
Keyword(s):  
Data Management ◽  
Digital Preservation ◽  
Management Training ◽  
Research Data ◽  
Content Type ◽  
Research Data Management ◽  
Mixed Methods Case Study ◽  
Management Processes ◽  
Digital Asset

Purpose The aim of this paper was to explore digital preservation requirements within the wider National Geoscience Data Centre (NGDC) organisational framework in preparation for developing a preservation policy and integrating associated preservation workflows throughout the existing research data management processes. This case study is based on an MSc dissertation research undertaken at Northumbria University. Design/methodology/approach This mixed methods case study used quantitative and qualitative data to explore the preservation requirements and triangulation to strengthen the design validity. Corporate and the wider scientific priorities were identified through literature and a stakeholder survey. Organisational preparedness was investigated through staff interviews. Findings Stakeholders expect data to be reliable, reusable and available in preferred formats. To ensure digital continuity, the creation of high-quality metadata is critical, and data depositors need data management training to achieve this. Recommendations include completing a risk assessment, creating a digital asset register and a technology watch to mitigate against risks. Research limitations/implications The main constraint in this study is the lack of generalisability of results. As the NGDC is a unique organisation, it may not be possible to generalise the organisational findings, although those relating to research data management may be transferrable. Originality/value This research examines the specific nature of geoscience data retention requirements and looks at existing NGDC procedures in terms of enhancing digital continuity, providing new knowledge on the preservation requirements for a number of national datasets.

scholarly journals Data meets history: A research data management strategy for the historically oriented humanities

2021 ◽  
pp. 155-178
Author(s):  
Fabian Cremer ◽  
Silvia Daniel ◽  
Marina Lemaire ◽  
Katrin Moeller ◽  
Matthias Razum ◽  
...  
Keyword(s):  
Data Management ◽  
Management Strategy ◽  
Research Data ◽  
Research Data Management

In defense of decentralized research data management

Neuroforum ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Michael Hanke ◽  
Franco Pestilli ◽  
Adina S. Wagner ◽  
Christopher J. Markiewicz ◽  
Jean-Baptiste Poline ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Management ◽  
Research Data ◽  
Data Archive ◽  
Individual Scientist ◽  
Computing Platform ◽  
Research Data Management ◽  
Cloud Computing Platform ◽  
Research Objects ◽  
Central Services

Abstract Decentralized research data management (dRDM) systems handle digital research objects across participating nodes without critically relying on central services. We present four perspectives in defense of dRDM, illustrating that, in contrast to centralized or federated research data management solutions, a dRDM system based on heterogeneous but interoperable components can offer a sustainable, resilient, inclusive, and adaptive infrastructure for scientific stakeholders: An individual scientist or laboratory, a research institute, a domain data archive or cloud computing platform, and a collaborative multisite consortium. All perspectives share the use of a common, self-contained, portable data structure as an abstraction from current technology and service choices. In conjunction, the four perspectives review how varying requirements of independent scientific stakeholders can be addressed by a scalable, uniform dRDM solution and present a working system as an exemplary implementation.

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