Menoci: lightweight extensible web portal enhancing data management for biomedical research projects

Abstract Background Biomedical research projects deal with data management requirements from multiple sources like funding agencies’ guidelines, publisher policies, discipline best practices, and their own users’ needs. We describe functional and quality requirements based on many years of experience implementing data management for the CRC 1002 and CRC 1190. A fully equipped data management software should improve documentation of experiments and materials, enable data storage and sharing according to the FAIR Guiding Principles while maximizing usability, information security, as well as software sustainability and reusability. Results We introduce the modular web portal software menoci for data collection, experiment documentation, data publication, sharing, and preservation in biomedical research projects. Menoci modules are based on the Drupal content management system which enables lightweight deployment and setup, and creates the possibility to combine research data management with a customisable project home page or collaboration platform. Conclusions Management of research data and digital research artefacts is transforming from individual researcher or groups best practices towards project- or organisation-wide service infrastructures. To enable and support this structural transformation process, a vital ecosystem of open source software tools is needed. Menoci is a contribution to this ecosystem of research data management tools that is specifically designed to support biomedical research projects.

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Analysis of Harvard Medical School Countway Library’s MOOC Course, Best Practices for Biomedical Research Data Management: Focus on the effects of COVID-19

10.31219/osf.io/9qbg4 ◽

2021 ◽

Author(s):

Kai Fay ◽

Julie Goldman

Keyword(s):

Best Practices ◽

Medical School ◽

Data Management ◽

Biomedical Research ◽

Harvard Medical School ◽

Research Data ◽

Massive Open Online Course ◽

Research Data Management ◽

Reported Data ◽

Potential Shifts

The Harvard Medical School Countway Library’s Massive Open Online Course (MOOC) Best Practices for Biomedical Research Data Management launched on Canvas in January 2018. This report analyzes student reported data and course generated analytics from January 2018, through July 8, 2020, for the course Best Practices for Biomedical Research Data Management. By comparing the findings from the enrollment period through March 8, 2020 (pre-pandemic) to the period through July 8, 2020 (during-pandemic), the main goal is to investigate potential shifts due to the COVID-19 pandemic.

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Research Data Management Initiatives at University of Edinburgh

International Journal of Digital Curation ◽

10.2218/ijdc.v6i2.199 ◽

2011 ◽

Vol 6 (2) ◽

pp. 232-244 ◽

Cited By ~ 6

Author(s):

Robin Rice ◽

Jeff Haywood

Keyword(s):

Data Management ◽

Data Storage ◽

Academic Staff ◽

Research Data ◽

Lessons Learned ◽

The Public ◽

Research Data Management ◽

Online Tools ◽

University Of Edinburgh ◽

Future Direction

During the last decade, national and international attention has been increasingly focused on issues of research data management and access to publicly funded research data. The pressure brought to bear on researchers to improve their data management and data sharing practice has come from research funders seeking to add value to expensive research and solve cross-disciplinary grand challenges; publishers seeking to be responsive to calls for transparency and reproducibility of the scientific record; and the public seeking to gain and re-use knowledge for their own purposes using new online tools. Meanwhile higher education institutions have been rather reluctant to assert their role in either incentivising or supporting their academic staff in meeting these more demanding requirements for research practice, partly due to lack of knowledge as to how to provide suitable assistance or facilities for data storage and curation/preservation. This paper discusses the activities and drivers behind one institution’s recent attempts to address this gap, with reflection on lessons learned and future direction.

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Research Data Management: A proposed framework to boost research in Higher Educational Institutes.

IASSIST Quarterly ◽

10.29173/iq12 ◽

2017 ◽

Vol 41 (1-4) ◽

pp. 12

Author(s):

Bhojaraju Gunjal ◽

Panorea Gaitanou

Keyword(s):

Literature Review ◽

Best Practices ◽

Data Management ◽

Skill Development ◽

Research Process ◽

Research Data ◽

Research Data Management ◽

Research Activities ◽

Educational Institute ◽

Higher Educational

This paper attempts to present a brief overview of several Research Data Management (RDM) issues and a detailed literature review regarding the RDM aspects adopted in libraries globally. Furthermore, it will describe several tendencies concerning the management of repository tools for research data, as well as the challenges in implementing the RDM. The proper planned training and skill development for all stakeholders by mentors to train both staff and users are some of the issues that need to be considered to enhance the RDM process. An effort will be also made to present the suitable policies and workflows along with the adoption of best practices in RDM, so as to boost the research process in an organisation. This study will showcase the implementation of RDM processes in the Higher Educational Institute of India, referring particularly to the Central Library @ NIT Rourkela in Odisha, India with a proposed framework. Finally, this study will also propose an area of opportunities that can boost research activities in the Institute.

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Generic concepts for organising data management in research projects

10.5194/egusphere-egu21-8903 ◽

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. &#160;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>

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Publishing trends on research data management in Sub-Saharan Africa: A bibliometrics analysis

IASSIST Quarterly ◽

10.29173/iq996 ◽

2021 ◽

Vol 45 (3-4) ◽

Author(s):

Tom Kwanya

Keyword(s):

Best Practices ◽

Data Management ◽

Research Output ◽

Developed Countries ◽

Research Data ◽

Sub Saharan Africa ◽

Google Scholar ◽

Publish Or Perish ◽

Research Data Management ◽

Sub Saharan

Research data management is an umbrella term used to describe activities related to the creation, organisation, structuring, naming, backing up, storage, conservation, and sharing of research data as well as all actions that guarantee security of research data. As is often the case, researchers from Sub-Saharan Africa are lagging behind their counterparts in developed countries in embracing the best practices of research data management. One of the factors to which this slow pace of adoption of research data management could be attributed, is inadequate research on the subject. The purpose of this paper is to analyse the quantity, quality, visibility and authorship of publications on research data management in Sub-Saharan Africa. Bibliometrics approaches were used to analyse publications on research data management from, and on, Sub-Saharan Africa which are currently indexed in Google Scholar. The index was chosen because it is free and is reputed to have liberal selection criteria which do not favour, or discriminate, any discipline or geographic regions. Data was retrieved from Google Scholar using Harzing’s “Publish or Perish” software and analysed using VOSviewer. The findings of the study revealed that the quantity, quality, visibility and authorship collaboration of scholarly publications on research data management in Sub-Saharan Africa is low. The findings may be used by libraries and research institutions in Sub-Saharan Africa to develop and promote best practices in research data management as a means of enhancing their research output and impact.

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Foundational Practices of Research Data Management

Research Ideas and Outcomes ◽

10.3897/rio.6.e56508 ◽

2020 ◽

Vol 6 ◽

Author(s):

Kristin Briney ◽

Heather Coates ◽

Abigail Goben

Keyword(s):

Data Analysis ◽

Best Practices ◽

Data Management ◽

Management Practices ◽

Research Data ◽

Data Reuse ◽

Data Handling ◽

Good Data ◽

Research Data Management ◽

The Future

The importance of research data has grown as researchers across disciplines seek to ensure reproducibility, facilitate data reuse, and acknowledge data as a valuable scholarly commodity. Researchers are under increasing pressure to share their data for validation and reuse. Adopting good data management practices allows researchers to efficiently locate their data, understand it, and use it throughout all of the stages of a project and in the future. Additionally, good data management can streamline data analysis, visualization, and reporting, thus making publication less stressful and time-consuming. By implementing foundational practices of data management, researchers set themselves up for success by formalizing processes and reducing common errors in data handling, which can free up more time for research. This paper provides an introduction to best practices for managing all types of data.

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Research Data Management Exercise

10.31229/osf.io/ehg5j ◽

2017 ◽

Author(s):

Chealsye Bowley

Keyword(s):

Best Practices ◽

Data Management ◽

Role Playing ◽

Research Data ◽

Research Data Management

Role playing exercise for student workshops on data management and sharing best practices.

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Research Data Sharing and Reuse Through Open Data

Advances in Library and Information Science - Open Access Implications for Sustainable Social, Political, and Economic Development ◽

10.4018/978-1-7998-5018-2.ch015 ◽

2021 ◽

pp. 284-306

Author(s):

Abel Christopher M'kulama ◽

Akakandelwa Akakandelwa

Keyword(s):

Data Management ◽

Data Sharing ◽

Data Storage ◽

Mixed Methods Research ◽

Open Data ◽

Research Process ◽

Research Data ◽

Research Data Management ◽

Inadequate Knowledge ◽

Self Administered Questionnaire

Research data management is considered a critical step in the research process among researchers. Researchers are required to submit RDM plans with details about data storage, data sharing, and reuse procedures when submitting research proposals for grants. This chapter presents findings of an investigation into the perceptions and practices of ZARI researchers towards research data management. Mixed methods research using a self-administered questionnaire was adopted for data collection. Fifty-one researchers were sampled and recruited for participation into the study. The study established that the majority of the researchers were not depositing their research data in central repositories; data was kept on individual's devices and was therefore not readily available for sharing. The major challenges being faced by researchers included lack of a policy, lack of a repository, and inadequate knowledge in RDM. The study concludes that research data at ZARI was not being professionally managed. The study recommends for formulation of policies, establishment of repository and staff training.

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Pengelolaan Data Penelitian pada Repositori Pengetahuan di Perpustakaan Khusus Lembaga Pemerintah Non Kementerian

Media Pustakawan ◽

10.37014/medpus.v27i3.1036 ◽

2020 ◽

Vol 27 (3) ◽

pp. 195-211

Author(s):

Tupan Tupan ◽

Mohamad Djaenudin

Keyword(s):

Data Management ◽

Data Storage ◽

Government Regulation ◽

Research Work ◽

Research Data ◽

Knowledge Repository ◽

Research Technology ◽

Research Data Management ◽

Knowledge Repositories ◽

Special Library

This study focuses on the analysis of research data management in the knowledge repository in a special library of non-ministerial government institutions consisting of LIPI, BPPT, BATAN, BAPETEN, LAPAN and BSN.The research was conducted using descriptive methods, namely by describing and interpreting a phenomenon that develops by using scientific procedures to actually answer the problem. Data collection was carried out through interviews and surveys of repository managers. The results showed that the LPNK Special Library of the Ministry of Research, Technology and Higher Education had mostly collected research data stored in the knowledge repository by means of direct input in the national scientific repository (RIN). Developing a knowledge repository in a special library is done because of the need to store data and research work in one place. The knowledge repository serves as a digital storage provider for long-term data storage and scientific work. The knowledge repository can make it easier for users to browse or reference data and the work of other researchers. The availability of knowledge repositories can also facilitate interdisciplinary learning and research. The obstacle in managing research data is that researchers have so far not paid enough attention, especially in terms of research data backup. There is a lack of trust from data owners to share their data because there is no legality, infrastructure and clear management. Libraries do not require researchers to store data in knowledge repositories and there is no government regulation that regulates inter-institutional research data management.

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