scholarly journals A clustering algorithm to evaluate the attitude of Brazilian researchers regarding open access research data

2021 ◽  
Author(s):  
Bruna S. Freitas ◽  
Diego Bottero ◽  
Giancarlo Lucca ◽  
Eduardo N. Borges ◽  
Helida Santos ◽  
...  
Keyword(s):  
Open Access ◽  
Clustering Algorithm ◽  
Research Process ◽  
Initial Study ◽  
Research Data ◽  
Scientific Investigation ◽  
Digital Repositories ◽  
Core Point ◽  
The Core

The core point of the research process are data. They are records from scientific investigation, which support the results published in journals and conferences. Making research data available in open access digital repositories has many advantages, such as increasing the visibility of associated publications, reproducing experiments, and validating results. In Brazil, full and unrestricted sharing of them is not yet accepted by most researchers. This paper presents an initial study to describe a model analyzing the attitude of Brazilian researchers concerning open access research data. A clustering algorithm was used to identify different research profiles. The achieved results indicate the main reasons why the researchers object to share their data.

scholarly journals Modelling the Research Data Lifecycle

2018 ◽  
Vol 12 (2) ◽  
pp. 331-361 ◽  
Author(s):  
Stacy T Kowalczyk
Keyword(s):  
Data Management ◽  
Analytical Techniques ◽  
Research Process ◽  
Initial Study ◽  
Research Data ◽  
Management Support ◽  
File Formats ◽  
Metadata File ◽  
Data Lifecycle ◽  
Digital Research

This paper develops and tests a lifecycle model for the preservation of research data by investigating the research practices of scientists.  This research is based on a mixed-method approach.  An initial study was conducted using case study analytical techniques; insights from these case studies were combined with grounded theory in order to develop a novel model of the Digital Research Data Lifecycle.  A broad-based quantitative survey was then constructed to test and extend the components of the model.  The major contribution of these research initiatives are the creation of the Digital Research Data Lifecycle, a data lifecycle that provides a generalized model of the research process to better describe and explain both the antecedents and barriers to preservation.  The antecedents and barriers to preservation are data management, contextual metadata, file formats, and preservation technologies.  The availability of data management support and preservation technologies, the ability to create and manage contextual metadata, and the choices of file formats all significantly effect the preservability of research data.

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 Defining the role of libraries in the Open Science landscape: a reflection on current European practice

2018 ◽  
Vol 2 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Paul Ayris ◽  
Tiberius Ignat
Keyword(s):  
Open Access ◽  
Data Management ◽  
Case Studies ◽  
Publishing Research ◽  
Research Process ◽  
Open Science ◽  
Research Data ◽  
Step Test ◽  
Open Access Publishing ◽  
Research Data Management

Abstract This collaborative paper looks at how libraries can engage with and offer leadership in the Open Science movement. It is based on case studies and the results of an EU-funded research project on Research Data Management taken from European research-led universities and their libraries. It begins by analysing three recent trends in Science, and then links component parts of the research process to aspects of Open Science. The paper then looks in detail at four areas and identifies roles for libraries: Open Access and Open Access publishing, Research Data Management, E-Infrastructures (especially the European Open Science Cloud), and Citizen Science. The paper ends in suggesting a model for how libraries, by using a 4-step test, can assess their engagement with Open Science. This 4-step test is based on lessons drawn from the case studies.

scholarly journals The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Daniel Arend ◽  
Patrick König ◽  
Astrid Junker ◽  
Uwe Scholz ◽  
Matthias Lange
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Best Practice ◽  
Research Process ◽  
Research Data ◽  
Primary Data ◽  
Data Repository ◽  
Plant Genomics ◽  
Quality Of Data

Abstract Background The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. Results To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements a “bring the infrastructure to the data” approach, which allows research data to be kept in place and wrapped in a FAIR-aware software infrastructure. This article presents new features of the e!DAL infrastructure software and the PGP repository as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as means to lower technical barriers and to increase the visibility of research data. Conclusion The e!DAL software matured to a powerful and FAIR-compliant infrastructure, while keeping the focus on flexible setup and integration into existing infrastructures and into the daily research process.

A Novel Locality Sensitive K-Means Clustering Algorithm based on Core Clusters

2013 ◽  
Vol 321-324 ◽  
pp. 1939-1942
Author(s):  
Lei Gu
Keyword(s):  
Clustering Algorithm ◽  
Experimental Results ◽  
Clustering Method ◽  
Neighborhood Graph ◽  
The Core ◽  
Random Samples

The locality sensitive k-means clustering method has been presented recently. Although this approach can improve the clustering accuracies, it often gains the unstable clustering results because some random samples are employed for the initial centers. In this paper, an initialization method based on the core clusters is used for the locality sensitive k-means clustering. The core clusters can be formed by constructing the σ-neighborhood graph and their centers are regarded as the initial centers of the locality sensitive k-means clustering. To investigate the effectiveness of our approach, several experiments are done on three datasets. Experimental results show that our proposed method can improve the clustering performance compared to the previous locality sensitive k-means clustering.

scholarly journals Enhancing Postgraduate Learning and Teaching: Postgraduate Summer School in Dairy Science

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Pietro Celi ◽  
Gianfranco Gabai ◽  
Massimo Morgante ◽  
Luigi Gallo
Keyword(s):  
Summer School ◽  
Research Collaboration ◽  
Learning Experience ◽  
Scientific Investigation ◽  
Core Component ◽  
Learning And Teaching ◽  
Transferable Skills ◽  
The Core ◽  
Dairy Science ◽  
The University

Dairy science is a multidisciplinary area of scientific investigation and Ph.D. students aiming to do research in the field of animal and/or veterinary sciences must be aware of this. Ph.D. students often have vast spectra of research interests, and it is quite challenging to satisfy the expectation of all of them. The aim of this study was to establish an international Ph.D. training program based on research collaboration between the University of Sydney and the University of Padova. The core component of this program was a two-week Postgraduate Summer School in Dairy Science, which was held at the University of Padova, for Ph.D. students of both universities. Therefore, we designed a program that encompassed seminars, workshops, laboratory practical sessions, and farm visits. Participants were surveyed using a written questionnaire. Overall, participants have uniformly praised the Summer School calling it a rewarding and valuable learning experience. The Ph.D. Summer School in Dairy Science provided its participants a positive learning experience, provided them the opportunity to establish an international network, and facilitated the development of transferable skills.

scholarly journals Policy recommendations for Open Access to research data in Europe – Stakeholder values and ecosystems

2014 ◽  
Vol 34 (3-4) ◽  
pp. 331-333
Author(s):  
Thordis Sveinsdottir ◽  
Bridgette A. Wessels ◽  
Rod Smallwood ◽  
Peter Linde ◽  
Vasso Kala ◽  
...  
Keyword(s):  
Open Access ◽  
Research Data ◽  
Policy Recommendations ◽  
Stakeholder Values

scholarly journals Open Developmental Science: An Overview and Annotated Reading List

2021 ◽  
Author(s):  
Tamara Kalandadze ◽  
Sara Ann Hart
Keyword(s):  
Open Access ◽  
Open Data ◽  
Open Science ◽  
Science Practices ◽  
The Core ◽  
Reading List ◽  
Annotated List ◽  
Developmental Science ◽  
Starting Point

The increasing adoption of open science practices in the last decade has been changing the scientific landscape across fields. However, developmental science has been relatively slow in adopting open science practices. To address this issue, we followed the format of Crüwell et al., (2019) and created summaries and an annotated list of informative and actionable resources discussing ten topics in developmental science: Open science; Reproducibility and replication; Open data, materials and code; Open access; Preregistration; Registered reports; Replication; Incentives; Collaborative developmental science.This article offers researchers and students in developmental science a starting point for understanding how open science intersects with developmental science. After getting familiarized with this article, the developmental scientist should understand the core tenets of open and reproducible developmental science, and feel motivated to start applying open science practices in their workflow.

scholarly journals Examining virtual identity profiles of social network users with respect to certain variables

2020 ◽  
Vol 10 (2) ◽  
pp. 427-464
Author(s):  
Esra Barut Tuğtekin ◽  
Özcan Özgür Dursun
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Identity Management ◽  
Research Process ◽  
Research Data ◽  
Total Variance ◽  
Measurement Tool ◽  
Validity And Reliability ◽  
Cronbach Alpha ◽  
The Social

In the present study, a measurement tool was developed to determine the virtual identities of social network users, and the virtual identities of these social network users were examined with respect to gender, time spent on social networks, number of their social network profiles and visibility using the relational survey model. The study was carried out with a total of 671 social network users, 252 females and 419 males. The research data were collected using the Social Network Identity Management Scale developed within the scope of the study. The five-point Likert-type scale made up of four factors and 23 items was found to explain 55.29 % of the total variance (Cronbach Alpha =.93). At the end of the research process, a 23-item Social Network Identity Management Scale’s validity and reliability were confirmed. The finding obtained in the study demonstrated that the virtual identities of the users with more than one profile differed within the context of such sub-dimensions of the scale as liking and privacy. In addition, it was found that the changes in the virtual identities increased depending on the time spent on social networks.

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