scholarly journals Online Library Reference Tools: A Proportional Learning of Open Research Data Repositories

2021 ◽  
Vol 7 (3) ◽  
pp. 146
Author(s):  
Dr. Bhalachandra S. Deshpande
Keyword(s):  
Research Data ◽  
Data Repositories ◽  
Open Research ◽  
Online Library ◽  
Reference Tools

scholarly journals DataverseNO: A National, Generic Repository and its Contribution to the Increased FAIRness of Data from the Long Tail of Research

Ravnetrykk ◽  
2020 ◽  
Author(s):  
Philipp Conzett
Keyword(s):  
Open Source Software ◽  
Crucial Role ◽  
Research Data ◽  
Background Information ◽  
Data Repositories ◽  
Long Tail ◽  
Open Research ◽  
Research Organizations ◽  
Digital Objects ◽  
Organizational Features

Research data repositories play a crucial role in the FAIR (Findable, Accessible, Interoperable, Reusable) ecosystem of digital objects. DataverseNO is a national, generic repository for open research data, primarily from researchers affiliated with Norwegian research organizations. The repository runs on the open-source software Dataverse. This article presents the organization and operation of DataverseNO, and investigates how the repository contributes to the increased FAIRness of small and medium sized research data. Sections 1 to 3 present background information about the FAIR Data Principles (section 1), how FAIR may be turned into reality (section 2), and what these principles and recommendations imply for data from the so-called long tail of research, i.e. small and medium-sized datasets that are often heterogenous in nature and hard to standardize (section 3). Section 4 gives an overview of the key organizational features of DataverseNO, followed by an evaluation of how well DataverseNO and the repository application Dataverse as such support the FAIR Data Principles (section 5). Section 6 discusses how sustainable and trustworthy the repository is. The article is rounded up in section 7 by a brief summary including a look into the future of the repository.

scholarly journals The State of Dissemination of Open Research Data in Ukraine and the World: Bibliometric Analysis

2021 ◽  
Vol 29 (4) ◽  
pp. 209-217
Author(s):  
Anton Boiko ◽  
Olha Kramarenko ◽  
Sardar Shabanov
Keyword(s):  
Bibliometric Analysis ◽  
Data Exchange ◽  
Open Science ◽  
Research Data ◽  
The State ◽  
Research Institutions ◽  
Data Repositories ◽  
Open Research ◽  
The World ◽  
Data Files

Purpose: To determine the current state of development of open science in the paradigm of open research data in Ukraine and the world, as well as to analyze the representation of Ukraine in the world research space, in terms of research data exchange. Design / Method / Research Approach: Methods of synthesis, logical and comparative analysis used to determine the dynamics of the number of research data journals and data files in the world, as well as to quantify the share of research data repositories in Ukraine and the world. Trend and bibliometric analysis were used to determine the share of publications with their open primary data; analysis of their thematic structures; identification of the main scientific clusters of such publications; research of geographic indicators and share of publications by research institutions. Findings: The study found a tendency to increase both the number of data logs and data files in Dryad (open data repository). The results of the analysis of the share of data repositories indexed in re3data (register of research data repositories) show that 51% of the total number are repositories of data from European countries, with Germany leading with 460 repositories, followed by the United Kingdom (302 repositories) and France (116 repositories). Ukraine has only 2 data repositories indexed in re3data. The trend of relevance of data exchange is confirmed by the increase of publications with datasets for the last 10 years (2011-2020) in 5 times. Research institutions and universities are the main sources of research data, which are mainly focused on the fields of knowledge in chemistry (23.3%); biochemistry, genetics and molecular biology (13.8%); medicine (12.9%). An analysis of the latest thematic groups formed on the basis of publications with datasets shows that there is a significant correlation between publications with open source data and COVID-19 studies. More than 50% of publications with datasets both in Ukraine and around the world are aimed at achieving the goal of SDG 3 Good Health. Theoretical Implications: It is substantiated that in Ukraine there is a need to implement specific tactical and strategic plans for open science and open access to research data. Practical Implications: The results of the study can be used to support decision-making in the management of research data at the macro and micro levels. Future Research: It should be noted that the righteous bibliometric analysis of the state of the dissemination of data underlying the research results did not include the assessment of quality indicators and compliance with the FAIR principles, because accessibility and reusability are fundamental components of open science, which may be an area for further research. Moreover, it is advisable to investigate the degree of influence of the disclosure of the data underlying the research result on economic indicators, as well as indicators of ratings of higher education, etc. Research Limitations: Since publications with datasets in Scopus-indexed journals became the information base of the analysis for our study, it can be assumed that the dataset did not include publications with datasets published in editions that the Scopus bibliographic database does not cover. Paper type: Theoretical

scholarly journals A survey of funders’ and institutions’ needs for understanding researchers’ open research practices

2021 ◽  
Author(s):  
Iain Hrynaszkiewicz ◽  
Lauren Cadwallader
Keyword(s):  
Research Data ◽  
Data Availability ◽  
Personal Contact ◽  
Research Practices ◽  
Data Repositories ◽  
Use Of Data ◽  
Current State ◽  
Open Research ◽  
Level Of Satisfaction ◽  
Funding Agencies

A growing number of research-performing organisations (institutions) and funding agencies have policies that support open research practices -- sharing of research data, code and software. However, funders and institutions lack sufficient tools, time or resources to monitor compliance with these policies.To better understand funder and institution needs related to understanding open research practices of researchers, we targeted funders and institutions with a survey in 2020 and received 122 completed responses. Our survey assessed and scored, (from 0-100), the importance of and satisfaction with 17 factors associated with understanding open research practices. This includes things such as knowing if a research paper includes links to research data in a repository; knowing if a research grant made code available in a public repository; knowing if research data were made available in a reusable form; and knowing reasons why research data are not publicly available. Half of respondents had tried to evaluate researchers’ open research practices in the past and 78% plan to do this in the future. The most common method used to find out if researchers are practicing open research was personal contact with researchers and the most common reason for doing it was to increase their knowledge of researchers’ sharing practices (e.g. determine current state of sharing; track changes in practices over time; compare different departments/disciplines). The results indicate that nearly all of the 17 factors we asked about in the survey were underserved. The mean importance of all factors to respondents was 71.7, approaching the 75 threshold of “very important”. The average satisfaction of all factors was 41.3, indicating a negative level of satisfaction with ability to complete these tasks. The results imply an opportunity for better solutions to meet these needs.The growth of policies and requirements for making research data and code available does not appear to be matched with solutions for determining if these policies have been complied with. We conclude that publishers can better support some of the needs of funders and institutions by introducing simple solutions such as:-Mandatory data availability statements (DAS) in research articles -Not permitting generic “data available on request” statements-Enabling and encouraging the use of data repositories and other methods that make data available in a more reusable way-Providing visible links to research data on publications-Making information available on data and code sharing practices in publications available to institutions and funding agencies-Extending policies that require transparency in sharing of research data, to sharing of code

scholarly journals Crosswalk among Prominent Open Research Data Repositories

Webology ◽  
2021 ◽  
Vol 18 (2) ◽  
pp. 60-67
Author(s):  
Dr.M. Krishnamurthy ◽  
Dr. Bhalachandra S. Deshpande ◽  
Dr.C. Sajana
Keyword(s):  
Open Access ◽  
Open Data ◽  
Research Data ◽  
Data Repositories ◽  
Digital Repositories ◽  
Open Research ◽  
Global Movement ◽  
Access To Knowledge ◽  
Metadata Harvesting ◽  
Data Upload

Open Access is a synergised global movement using Internet to provide equal access to knowledge that once hid behind the subscription paywalls. Many new models for scholarly communication have emerged in recent past. One among them is institutional or digital repositories which archive the scholarly content of an organization. While the concept of Open Access opened new arena for institutional or digital repositories in the form of Open repositories. Likewise, the Open repositories for Research Data Management (RDM) are initiative to organize, store, cite, preserve, and share the collected data derived from the research. There are many multidisciplinary and subject specific open repositories for RDM offering exquisite features for perpetual management of research data. The objective of the present study is to evaluate features of popular Open Data Repositories-Zenodo, FigShare, Harvard Dataverse and Mendeley Data. The evaluation provided insights about the key features of the selected Open Data Repositories and which enable us to select the best among them. Zenodo provides maximum data upload limit. While the major features required by a researcher like DOI, File Types, citation support, licenses, search (metadata harvesting) are provided by all three repositories.

scholarly journals Open Research Data and Open Peer Review: Perceptions of a Medical and Health Sciences Community in Greece

Publications ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 14
Author(s):  
Eirini Delikoura ◽  
Dimitrios Kouis
Keyword(s):  
Peer Review ◽  
Evaluation System ◽  
Early Stage ◽  
Open Science ◽  
Health Sciences ◽  
Research Data ◽  
Stage Of Development ◽  
Open Research ◽  
Proper Training ◽  
To Receive

Recently significant initiatives have been launched for the dissemination of Open Access as part of the Open Science movement. Nevertheless, two other major pillars of Open Science such as Open Research Data (ORD) and Open Peer Review (OPR) are still in an early stage of development among the communities of researchers and stakeholders. The present study sought to unveil the perceptions of a medical and health sciences community about these issues. Through the investigation of researchers` attitudes, valuable conclusions can be drawn, especially in the field of medicine and health sciences, where an explosive growth of scientific publishing exists. A quantitative survey was conducted based on a structured questionnaire, with 179 valid responses. The participants in the survey agreed with the Open Peer Review principles. However, they ignored basic terms like FAIR (Findable, Accessible, Interoperable, and Reusable) and appeared incentivized to permit the exploitation of their data. Regarding Open Peer Review (OPR), participants expressed their agreement, implying their support for a trustworthy evaluation system. Conclusively, researchers need to receive proper training for both Open Research Data principles and Open Peer Review processes which combined with a reformed evaluation system will enable them to take full advantage of the opportunities that arise from the new scholarly publishing and communication landscape.

Improvements for research data repositories: The case of text spam

2021 ◽  
pp. 016555152199863
Author(s):  
Ismael Vázquez ◽  
María Novo-Lourés ◽  
Reyes Pavón ◽  
Rosalía Laza ◽  
José Ramón Méndez ◽  
...  
Keyword(s):  
Web Application ◽  
Research Data ◽  
Data Sets ◽  
Data Repositories ◽  
Software Applications ◽  
Public Data ◽  
Protection Mechanisms ◽  
Experimental Protocols ◽  
Learning Research ◽  
Processing Steps

Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the results of their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through other approximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements for the development of experimental protocols and test benches. This study has analysed a significant number of CS/ML ( Computer Science/ Machine Learning) research data repositories and data sets and detected some limitations that hamper their utility. Particularly, we identify and discuss the following demanding functionalities for repositories: (1) building customised data sets for specific research tasks, (2) facilitating the comparison of different techniques using dissimilar pre-processing methods, (3) ensuring the availability of software applications to reproduce the pre-processing steps without using the repository functionalities and (4) providing protection mechanisms for licencing issues and user rights. To show the introduced functionality, we created STRep (Spam Text Repository) web application which implements our recommendations adapted to the field of spam text repositories. In addition, we launched an instance of STRep in the URL https://rdata.4spam.group to facilitate understanding of this study.

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