Research data management and sharing awareness, attitude, and behavior of academic researchers

2021 ◽  
pp. 026666692110484
Author(s):  
Muhammad Rafiq ◽  
Kanwal Ameen
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Data File ◽  
Research Data ◽  
University Administrators ◽  
Research Data Management ◽  
Academic Researchers ◽  
Sharing Patterns ◽  
And Behavior ◽  
Structured Questionnaire

This study assesses the research data management (RDM) awareness, attitude, practices, and behaviors of Pakistan's academic researchers. By using an internationally designed structured questionnaire as a data collection instrument. Quantitative survey research method was opted to meet the research objectives and data was collected from academicians and researchers of four premier universities of Pakistan. The study reveals used and produced data file formats, data acquisition sources, data storage patterns, metadata and tagging practices, data sharing patterns, RDM awareness, attitude, and behavior of the respondents by investigating the self-opinion of respondents on extensive sets of structured questionnaire items. It is a comprehensive assessment of the phenomenon from a developing country's perspective where research data management policies are absent at national and institutional level. The findings have theoretical implications for researchers and practical implications for policymakers, university administrators, university library administrators, and educational trainers.

scholarly journals Research Data Management Initiatives at University of Edinburgh

2011 ◽  
Vol 6 (2) ◽  
pp. 232-244 ◽  
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.

Research Data Sharing and Reuse Through Open Data

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.

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

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.

scholarly journals Investigation of Non-Academic Data Management Practices to Inform Academic Research Data Management

2018 ◽  
Vol 4 ◽  
Author(s):  
Steven Van Tuyl ◽  
Amanda Whitmire
Keyword(s):  
Best Practices ◽  
Data Management ◽  
Management Practices ◽  
Academic Research ◽  
Research Data ◽  
Government Agencies ◽  
University Administrators ◽  
Academic Environments ◽  
Research Data Management ◽  
Funding Agencies

In recent years, the academic research data management (RDM) community has worked closely with funding agencies, university administrators, and researchers to develop best practices for RDM. The RDM community, however, has spent relatively little time exploring best practices used in non-academic environments (industry, government, etc.) for management, preservation, and sharing of data. In this poster, we present the results of a project wherein we approached a number of non-academic corporations and institutions to discuss how data is managed in those organizations and discern what the academic RDM community could learn from non-academic RDM practices. We conducted interviews with 10-20 companies including tech companies, government agencies, and consumer retail corporations. We present the results in the form of user stories, common themes from interviews, and summaries of areas where the RDM community might benefit from further understanding of non-academic data management practices.

How to Extend your Data Lifetime: Research Data Management in Indonesia’s Contexts

2018 ◽  
Author(s):  
Dasapta Erwin Irawan ◽  
Santirianingrum Soebandhi ◽  
Fierly Hayati ◽  
Cahyo Darujati ◽  
Deffy Ayu Puspito Sari
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Intellectual Property Rights ◽  
Research Data ◽  
The Other ◽  
Know How ◽  
Research Data Management ◽  
The World ◽  
Data Ownership ◽  
Data Lifetime

Data is the basis of research. On the other side, the world has a problem of replication. The first problem is we don’t really know how to manage our own data to able to reanalyze it at some point after the research has been finished. The lifetime of data is very short, in only one or two fiscal years. In this article we will describe on how to write a research data management in order to extend the lifetime of data. There are seven basic components to remember before writing a proper research data management: (1) Data storage and software, (2) Metadata, (3) Structure, (4) Persistent link, (5) Licensing, (6) Data maintainer, (7) Indexing. In several fields, including medicine, an anomyzation strategy will be needed. We also need to put into account the Intellectual Property Rights and data ownership in to the equation, as Indonesian scientists are not properly exposed to those subjects.

Applying FAIRness: Redesigning a Biomedical Informatics Research Data Management Pipeline

2019 ◽  
Vol 58 (06) ◽  
pp. 229-234 ◽  
Author(s):  
Marcel Parciak ◽  
Theresa Bender ◽  
Ulrich Sax ◽  
Christian Robert Bauer
Keyword(s):  
Data Integration ◽  
Data Management ◽  
Data Storage ◽  
Biomedical Informatics ◽  
Software Tools ◽  
Research Data ◽  
Research Results ◽  
Data Usage ◽  
Research Data Management ◽  
Guiding Principles

Abstract Background Managing research data in biomedical informatics research requires solid data governance rules to guarantee sustainable operation, as it generally involves several professions and multiple sites. As every discipline involved in biomedical research applies its own set of tools and methods, research data as well as applied methods tend to branch out into numerous intermediate and output data objects, making it very difficult to reproduce research results. Objectives This article gives an overview of our implementation status applying the Findability, Accessibility, Interoperability and Reusability (FAIR) Guiding Principles for scientific data management and stewardship onto our research data management pipeline focusing on the software tools that are in use. Methods We analyzed our progress FAIRificating the whole data management pipeline, from processing non-FAIR data up to data usage. We looked at software tools for data integration, data storage, and data usage as well as how the FAIR Guiding Principles helped to choose appropriate tools for each task. Results We were able to advance the degree of FAIRness of our data integration as well as data storage solutions, but lack enabling more FAIR Guiding Principles regarding Data Usage. Existing evaluation methods regarding the FAIR Guiding Principles (FAIRmetrics) were not applicable to our analysis of software tools. Conclusion Using the FAIR Guiding Principles, we FAIRificated relevant parts of our research data management pipeline improving findability, accessibility, interoperability and reuse of datasets and research results. We aim to implement the FAIRmetrics to our data management infrastructure and—where required—to contribute to the FAIRmetrics for research data in the biomedical informatics domain as well as for software tools to achieve a higher degree of FAIRness of our research data management pipeline.

Research data management at a public university in Malawi: the role of “three hands”

2020 ◽  
Vol 41 (6/7) ◽  
pp. 467-485
Author(s):  
Winner Dominic Chawinga ◽  
Sandy Zinn
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Management Practices ◽  
Public University ◽  
Research Data ◽  
Raw Material ◽  
Content Type ◽  
Research Data Management ◽  
Research Activities ◽  
The University

PurposeConsidering that research data is increasingly hailed as an important raw material for current and future science discoveries, many research stakeholders have joined forces to create mechanisms for preserving it. However, regardless of generating rich research data, Africa lags behind in research data management thereby potentially losing most of this valuable data. Therefore, this study was undertaken to investigate the research data management practices at a Malawian public university with the aim to recommend appropriate data management strategies.Design/methodology/approachThe study is inspired by the pragmatic school of thought thereby adopting quantitative and qualitative research approaches. Quantitative data was collected using a questionnaire from 150 researchers and 25 librarians while qualitative data was collected by conducting an interview with the Director of Research.FindingsResearchers are actively involved in research activities thereby generating large quantities of research data. Although researchers are willing to share their data, only a handful follow through. Data preservation is poor because the university uses high risk data storage facilities, namely personal computers, flash disks, emails and external hard drives. Researchers and librarians lacked core research data-management competencies because of the lack of formal and information training opportunities. Challenges that frustrate research data-management efforts are many but the key ones include absence of research data management policies, lack of incentives, lack of skills and unavailability of data infrastructure.Research limitations/implicationsThe study's findings are based on one out of four public universities in the country; hence, the findings may not adequately address the status of research data management practices in the other universities.Practical implicationsConsidering that the university under study and its counterparts in Malawi and Africa in general operate somewhat in a similar economic and technological environment, these findings could be used as a reference point for other universities intending to introduce research data management initiatives.Originality/valueWith seemingly limited studies about research data management in Africa and particularly in Malawi, the study sets the tone for research data management debates and initiatives in the country and other African countries.

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

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
M. Suhr ◽  
C. Lehmann ◽  
C. R. Bauer ◽  
T. Bender ◽  
C. Knopp ◽  
...  
Keyword(s):  
Best Practices ◽  
Data Management ◽  
Data Storage ◽  
Biomedical Research ◽  
Content Management ◽  
Research Data ◽  
Research Projects ◽  
Web Portal ◽  
Multiple Sources ◽  
Research Data Management

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.

scholarly journals Research Data Management Practices: A Snapshot in Time

2015 ◽  
Vol 10 (2) ◽  
pp. 69-95 ◽  
Author(s):  
Mary Anne Kennan ◽  
Lina Markauskaite
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Management Practices ◽  
Management Plan ◽  
Research Data ◽  
Project Completion ◽  
Research Data Management ◽  
Secure Storage ◽  
South Wales ◽  
Research Organisations

There is increasing pressure from funders, publishers, the public, universities and other research organisations for researchers to improve their data management and sharing practices. However, little is known about researchers’ data management and sharing practices and concerns. The research reported in this paper seeks to address this by providing insight into the research data management and sharing practices of academics at ten universities in New South Wales, Australia. Empirical data was taken from a survey to which 760 academics responded, with 634 completing at least one section. Results showed that at the time of the survey there were a wide variety of research data in use, including analogue data, and that the challenges researchers faced in managing their data included finding safe and secure storage, particularly after project completion, but also during projects when data are used (and thus stored) on a wide variety of less-than-optimal temporary devices. Data sharing was not widely practiced and only a relatively small proportion of researchers had a research data management plan. Since the survey was completed much has changed: capacities and communities are being built around data management and sharing and policies, and guidelines are being constructed. Data storage and curation services are now more freely available. It will be interesting to observe how the findings of future studies compare with those reported here.

Research data management services for a multidisciplinary, collaborative research project

2015 ◽  
Vol 49 (4) ◽  
pp. 494-512 ◽  
Author(s):  
Constanze Curdt ◽  
Dirk Hoffmeister
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Research Data ◽  
Research Project ◽  
Content Type ◽  
Research Data Management ◽  
Metadata Schema ◽  
Interdisciplinary Research Project ◽  
Project Data ◽  
User Friendly

Purpose – Research data management (RDM) comprises all processes, which ensure that research data are well-organized, documented, stored, backed up, accessible, and reusable. RDM systems form the technical framework. The purpose of this paper is to present the design and implementation of a RDM system for an interdisciplinary, collaborative, long-term research project with focus on Soil-Vegetation-Atmosphere data. Design/methodology/approach – The presented RDM system is based on a three-tier (client-server) architecture. This includes a file-based data storage, a database-based metadata storage, and a self-designed user-friendly web-interface. The system is designed in cooperation with the local computing centre, where it is also hosted. A self-designed interoperable, project-specific metadata schema ensures the accurate documentation of all data. Findings – A RDM system has to be designed and implemented according to requirements of the project participants. General challenges and problems of RDM should be considered. Thus, a close cooperation with the scientists obtains the acceptance and usage of the system. Originality/value – This paper provides evidence that the implementation of a RDM system in the provided and maintained infrastructure of a computing centre offers many advantages. Consequently, the designed system is independent of the project funding. In addition, access and re-use of all involved project data is ensured. A transferability of the presented approach to another interdisciplinary research project was already successful. Furthermore, the designed metadata schema can be expanded according to changing project requirements.

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