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 How long can we build it? Ensuring usability of a scientific code base

2021 ◽  
Vol 16 (1) ◽  
pp. 11
Author(s):  
Klaus Rechert ◽  
Jurek Oberhauser ◽  
Rafael Gieschke
Keyword(s):  
Data Management ◽  
Source Code ◽  
Research Data ◽  
Scientific Contribution ◽  
Scientific Publications ◽  
Research Data Management ◽  
Code Base

Software and in particular source code became an important component of scientific publications and henceforth is now subject of research data management.  Maintaining source code such that it remains a usable and a valuable scientific contribution is and remains a huge task. Not all code contributions can be actively maintained forever. Eventually, there will be a significant backlog of legacy source-code. In this article we analyse the requirements for applying the concept of long-term reusability to source code. We use simple case study to identify gaps and provide a technical infrastructure based on emulator to support automated builds of historic software in form of source code.  

scholarly journals First InvenioRDM Long-Term Support (LTS) version released today ??? and Front Matter is joining as a participating partner

2021 ◽  
Author(s):  
Martin Fenner
Keyword(s):  
Data Management ◽  
Open Source ◽  
Research Data ◽  
Management Platform ◽  
Research Data Management ◽  
Data Management Platform

The open source research data management platform InvenioRDM today announced the first Long-Term Support (LTS) release, usable on production services. And I am joining the effort as a participating partner via Front Matter, ...

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.

scholarly journals Perception of Researchers & Academicians of Parul University towards Research Data Management System & Role of Library

2020 ◽  
Vol 40 (03) ◽  
pp. 139-146 ◽  
Author(s):  
Anjana R Bunkar ◽  
Dhaval D. Bhatt
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Developed Countries ◽  
Research Data ◽  
Data Management System ◽  
The Public ◽  
Research Data Management ◽  
Initial Stage

Research data management is a system that helps in archiving and retrieving of research data to reuse and preserving them for long term use. Many universities in developed countries have already started providing RDM services to their researchers and academicians. In India, it is still in the initial stage. The purpose of the present study is to investigate the perceptions of researchers and academicians of Parul University on research data management and research data sharing. It also explores the ways the researchers preserved their research data for future use. It also explores the ways the library can take initiatives to encourage and extend support to the researchers and academicians to the organisation, preservation, and sharing of research data. To investigate and study the problem 100 questionnaires were distributed. There are 88 responses we received out of 100. The study revealed that the majority of respondents were agreeing about the research data sharing and free accessibility of research data to browse and reuse. Researchers are very much interested and agreed in the library’s involvement in organizing and preservation of research data. Researchers and faculty members are more concerned about their intellectual property rights while sharing the data on the public domain.

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.  

Variability in academic research data management practices

2015 ◽  
Vol 49 (4) ◽  
pp. 382-407 ◽  
Author(s):  
Amanda L. Whitmire ◽  
Michael Boock ◽  
Shan C. Sutton
Keyword(s):  
Data Management ◽  
Online Survey ◽  
Management Practices ◽  
Academic Research ◽  
Research Data ◽  
Data Types ◽  
Content Type ◽  
Progressive Development ◽  
Research Data Management ◽  
Basic Services

Purpose – The purpose of this paper is to demonstrate how knowledge of local research data management (RDM) practices critically informs the progressive development of research data services (RDS) after basic services have already been established. Design/methodology/approach – An online survey was distributed via e-mail to all university faculty in the fall of 2013, and was left open for just over one month. The authors sent two reminder e-mails before closing the survey. Survey data were downloaded from Qualtrics survey software and analyzed in R. Findings – In this paper, the authors reviewed a subset of survey findings that included data types, volume, and storage locations, RDM roles and responsibilities, and metadata practices. The authors found that Oregon State University (OSU) researchers are generating a wide variety of data types, and that practices vary between colleges. The authors discovered that faculty are not utilizing campus-wide storage infrastructure, and are maintaining their own storage servers in surprising numbers. Faculty-level research assistants perform the majority of data-related tasks at OSU, with the exception of data sharing, which is primarily handled by the professorial ranks. The authors found that many faculty on campus are creating metadata, but that there is a need to provide support in how to discover and create standardized metadata. Originality/value – This paper presents a novel example of how to efficiently move from establishing basic RDM services to providing more focussed services that meet specific local needs. It provides an approach for others to follow when tackling the difficult question of, “What next?” with regard to providing academic RDS.

The Minimum Mandatory Metadata Sets for the KIM Project and RAIDmap

2017 ◽  
pp. 37-64
Author(s):  
Alexander Ball ◽  
Mansur Darlington ◽  
Christopher McMahon
Keyword(s):  
Data Management ◽  
Information Management ◽  
Mechanical Engineering ◽  
Research Data ◽  
Minimal Set ◽  
Life Project ◽  
Research Data Management ◽  
Metadata Record

A Minimum Mandatory Metadata Set (M3S) was devised for the KIM (Knowledge and Information Management Through Life) Project to address two challenges. The first was to ensure the project's documents were sufficiently self-documented to allow them to be preserved in the long term. The second was to trial the M3S and supporting templates and tools as a possible approach that might be used by the aerospace, defence and construction industries. A different M3S was devised along similar principles by a later project called REDm-MED (Research Data Management for Mechanical Engineering Departments). The aim this time was to help specify a tool for documenting research data records and the associations between them, in support of both preservation and discovery. In both cases the emphasis was on collecting a minimal set of metadata at the time of object creation, on the understanding that later processes would be able to expand the set into a full metadata record.

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