The roles of academic libraries in propagating open science

2016 ◽  
Vol 34 (2) ◽  
pp. 113-121 ◽  
Author(s):  
John I. Ogungbeni ◽  
Amaka R. Obiamalu ◽  
Samuel Ssemambo ◽  
Charles M. Bazibu
Keyword(s):  
Literature Review ◽  
Academic Libraries ◽  
Scientific Collaboration ◽  
Scientific Research ◽  
Open Science ◽  
Scientific Data ◽  
Research Articles ◽  
Data Repositories ◽  
Qualitative Survey ◽  
Key Players

This study investigates the roles of academic libraries in propagating Open Science. The study is a qualitative survey based on literature review. Various definitions of open science from different scholars and schools of thought were examined. Research articles on the effects of open science on research and the place of academic libraries in scientific research were reviewed. Open science enhances collaborations and sharing of resources among researchers. Metadata related activities are more prevalent due to open science. Open science has increased the relevance of science to our environment and world issues like privacy and the rightful author of scientific data are still some of the challenges facing open science. Academic libraries continue to take steps to be involved as key players in the propagation of open science through advocacy, building of institutional data repositories and serving as hubs for scientific collaboration among others. Academic libraries have to do more in the area of advocacy and provision of data repositories.

scholarly journals Abordagens de reúso e a questão da reusabilidade dos dados científicos | Approaches for data reuse and the issue of scientific data reusability

2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Renata Curty
Keyword(s):  
Data Sharing ◽  
Data Science ◽  
Meta Analysis ◽  
Science Research ◽  
Open Science ◽  
Scientific Data ◽  
Data Reuse ◽  
Data Repositories ◽  
Documentation Quality ◽  
Data Documentation

RESUMO As diretivas governamentais e institucionais em torno do compartilhamento de dados de pesquisas financiadas com dinheiro público têm impulsionado a rápida expansão de repositórios digitais de dados afim de disponibilizar esses ativos científicos para reutilização, com propósitos nem sempre antecipados, pelos pesquisadores que os produziram/coletaram. De modo contraditório, embora o argumento em torno do compartilhamento de dados seja fortemente sustentado no potencial de reúso e em suas consequentes contribuições para o avanço científico, esse tema permanece acessório às discussões em torno da ciência de dados e da ciência aberta. O presente artigo de revisão narrativa tem por objetivo lançar um olhar mais atento ao reúso de dados e explorar mais diretamente esse conceito, ao passo que propõe uma classificação inicial de cinco abordagens distintas para o reúso de dados de pesquisa (reaproveitamento, agregação, integração, metanálise e reanálise), com base em situações hipotéticas acompanhadas de casos de reúso de dados publicados na literatura científica. Também explora questões determinantes para a condição de reúso, relacionando a reusabilidade à qualidade da documentação que acompanha os dados. Oferece discussão sobre os desafios da documentação de dados, bem como algumas iniciativas e recomendações para que essas dificuldades sejam contornadas. Espera-se que os argumentos apresentados contribuam não somente para o avanço conceitual em torno do reúso e da reusabilidade de dados, mas também reverberem em ações relacionadas à documentação dos dados de modo a incrementar o potencial de reúso desses ativos científicos.Palavras-chave: Reúso de Dados; Reprodutibilidade Científica; Reusabilidade; Ciência Aberta; Dados de Pesquisa. ABSTRACT The availability of scientific assets through data repositories has been greatly increased as a result of government and institutional data sharing policies and mandates for publicly funded research, allowing data to be reused for purposes not always anticipated by primary researchers. Despite the fact that the argument favoring data sharing is strongly grounded in the possibilities of data reuse and its contributions to scientific advancement, this subject remains unobserved in discussions about data science and open science. This paper follows a narrative review method to take a closer look at data reuse in order to better conceptualize this term, while proposing an early classification of five distinct data reuse approaches (repurposing, aggregation, integration, meta-analysis and reanalysis) based on hypothetical cases and literature examples. It also explores the determinants of what constitutes reusable data, and the relationship between data reusability and documentation quality. It presents some challenges associated with data documentation and points out some initiatives and recommendations to overcome such problems. It expects to contribute not only for the conceptual advancement around the reusability and effective reuse of the data, but also to result in initiatives related to data documentation in order to increase the reuse potential of these scientific assets.Keywords:Data Reuse; Scientific Reproducibility; Reusability; Open Science; Research Data.  

scholarly journals SSM: A Semantic Metasearch Platform for Scientific Data retrieval

2022 ◽  
Vol 29 (1) ◽  
pp. 91-101
Author(s):  
Gustavo Caetano Borges ◽  
Julio Cesar Dos Reis ◽  
Claudia Bauzer Medeiros
Keyword(s):  
Scientific Research ◽  
Data Retrieval ◽  
Scientific Data ◽  
Research Data ◽  
Use Case ◽  
Data Repositories ◽  
Metadata Standards ◽  
Public Repositories

Scientific research in all fields has advanced in complexity and in the amount of data generated. The heterogeneity of data repositories, data meaning and their metadata standards makes this problem even more significant. In spite of several proposals to find and retrieve research data from public repositories, there is still need for more comprehensive retrieval solutions. In this article, we specify and develop a mechanism to search for scientific data that takes advantage of metadata records and semantic methods. We present the conception of our architecture and how we have implemented it in a use case in the agriculture domain.

scholarly journals Semantic Search on Scientific Repositories: A Systematic Literature Review

2020 ◽  
Author(s):  
Thiago Gottardi ◽  
Claudia Bauzer Medeiros ◽  
Julio Cesar Dos Reis
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Scientific Collaboration ◽  
Open Data ◽  
Open Science ◽  
Semantic Search ◽  
High Quality ◽  
High Quality Research ◽  
Scientific Papers ◽  
The Web

Open Science has been recognized as one of the most important movements for leveraging scientific collaboration, helping scientists produce high quality research through sharing and reuse. It is usually defined as a combination of three factors: open access, open data and open processes, and relies on the corresponding publication of papers, data and software in repositories that can be publicly accessed on the Web. However, finding relevant papers, data and software has become one of the associated problems. Many search mechanisms – in particular semantic search – have risen as a means to solve this issue. Nevertheless, implementing these mechanisms and integrating them into scientific repositories presents many challenges. This paper presents a systematic literature review of research efforts on mechanisms for supporting search for scientific papers, data and processes, based on extracting and analyzing the entire contents of Scopus and IEEE Xplore.

scholarly journals Addressing search in scientific open data repositories: A semantic metasearch platform

2021 ◽  
Author(s):  
Gustavo Caetano Borges ◽  
Julio César dos Reis ◽  
Claudia Bauzer Medeiros
Keyword(s):  
Open Data ◽  
Scientific Research ◽  
Scientific Data ◽  
Research Data ◽  
Use Case ◽  
Data Repositories ◽  
Metadata Standards ◽  
Public Repositories

Scientific research in all fields has advanced in complexity and in the amount of data generated. The heterogeneity of data repositories, data meaning and their metadata standards makes this problem even more significant. In spite of several proposals to find and retrieve research data from public repositories, there is still need for more comprehensive retrieval solutions. In this article, we specify and develop a mechanism to search for scientific data that takes advantage of metadata records and semantic methods. We present the conception of our architecture and how we have implemented it in a use case in agriculture.

scholarly journals Preliminary Analysis of COVID-19 Academic Information Patterns: A Call for Open Science in the Times of Closed Borders

2020 ◽  
Author(s):  
Jan Homolak ◽  
Ivan Kodvanj ◽  
Davor Virag
Keyword(s):  
Scientific Community ◽  
Scientific Collaboration ◽  
R Package ◽  
Open Science ◽  
Efficient Solutions ◽  
Publication Rate ◽  
Scientific Data ◽  
Data Availability ◽  
Related Data ◽  
Academic Information

Introduction: The Pandemic of COVID-19, an infectious disease caused by SARS-CoV-2 motivated the scientific community to work together in order to gather, organize, process and distribute data on the novel biomedical hazard. Here, we analyzed how the scientific community responded to this challenge by quantifying distribution and availability patterns of the academic information related to COVID-19. The aim of our study was to assess the quality of the information flow and scientific collaboration, two factors we believe to be critical for finding new solutions for the ongoing pandemic. Materials and Methods: The RISmed R package, and a custom Python script were used to fetch metadata on articles indexed in PubMed and published on rXiv preprint server. Scopus was manually searched and the metadata was exported in BibTex file. Publication rate and publication status, affiliation and author count per article, and submission-to-publication time were analysed in R. Biblioshiny application was used to create a world collaboration map. Results: Our preliminary data suggest that COVID-19 pandemic resulted in generation of a large amount of scientific data, and demonstrates potential problems regarding the information velocity, availability, and scientific collaboration in the early stages of the pandemic. More specifically, our results indicate precarious overload of the standard publication systems, delayed adoption of the preprint publishing, significant problems with data availability and apparent deficient collaboration. Conclusion: In conclusion, we believe the scientific community could have used the data more efficiently in order to create proper foundations for finding new solutions for the COVID-19 pandemic. Moreover, we believe we can learn from this on the go and adopt open science principles and a more mindful approach to COVID-19-related data to accelerate the discovery of more efficient solutions. We take this opportunity to invite our colleagues to contribute to this global scientific collaboration by publishing their findings with maximal transparency.

scholarly journals Preliminary Analysis of COVID-19 Academic Information Patterns: A Call for Open Science in the Times of Closed Borders

2020 ◽  
Author(s):  
Jan Homolak ◽  
Ivan Kodvanj ◽  
Davor Virag
Keyword(s):  
Scientific Community ◽  
Scientific Collaboration ◽  
R Package ◽  
Open Science ◽  
Efficient Solutions ◽  
Publication Rate ◽  
Scientific Data ◽  
Data Availability ◽  
Related Data ◽  
Academic Information

Introduction: The Pandemic of COVID-19, an infectious disease caused by SARS-CoV-2 motivated the scientific community to work together in order to gather, organize, process and distribute data on the novel biomedical hazard. Here, we analyzed how the scientific community responded to this challenge by quantifying distribution and availability patterns of the academic information related to COVID-19. The aim of our study was to assess the quality of the information flow and scientific collaboration, two factors we believe to be critical for finding new solutions for the ongoing pandemic. Materials and methods: The RISmed R package, and a custom Python script were used to fetch metadata on articles indexed in PubMed and published on Rxiv preprint server. Scopus was manually searched and the metadata was exported in BibTex file. Publication rate and publication status, affiliation and author count per article, and submission-to-publication time were analysed in R. Biblioshiny application was used to create a world collaboration map. Results: Our preliminary data suggest that COVID-19 pandemic resulted in generation of a large amount of scientific data, and demonstrates potential problems regarding the information velocity, availability, and scientific collaboration in the early stages of the pandemic. More specifically, our results indicate precarious overload of the standard publication systems, significant problems with data availability and apparent deficient collaboration. Conclusion: In conclusion, we believe the scientific community could have used the data more efficiently in order to create proper foundations for finding new solutions for the COVID-19 pandemic. Moreover, we believe we can learn from this on the go and adopt open science principles and a more mindful approach to COVID-19-related data to accelerate the discovery of more efficient solutions. We take this opportunity to invite our colleagues to contribute to this global scientific collaboration by publishing their findings with maximal transparency.

scholarly journals Promoting Open Science: A Holistic Approach to Changing Behaviour

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Samuel G. Robson ◽  
Myriam A. Baum ◽  
Jennifer L. Beaudry ◽  
Julia Beitner ◽  
Hilmar Brohmer ◽  
...  
Keyword(s):  
Behaviour Change ◽  
Academic Libraries ◽  
Scientific Research ◽  
Holistic Approach ◽  
Open Science ◽  
Scientific Practices ◽  
Research Culture ◽  
Small Shift ◽  
Open Research ◽  
Shared Norms

In this article, we provide a toolbox of recommendations and resources for those aspiring to promote the uptake of open scientific practices. Open Science encompasses a range of behaviours that aim to improve the transparency of scientific research. This paper is divided into seven sections, each devoted to different groups or institutions in the research ecosystem: colleagues, students, departments and faculties, universities, academic libraries, journals, and funders. We describe the behavioural influences and incentives for each of these stakeholders as well as changes they can make to foster Open Science. Our primary goal, however, is to suggest actions that researchers can take to promote these behaviours, inspired by simple principles of behaviour change: make it easy, social, and attractive. In isolation, a small shift in one person’s behaviour may appear to make little difference, but when combined, many shifts can radically alter shared norms and culture. We offer this toolbox to assist individuals and institutions in cultivating a more open research culture.

scholarly journals Comparing Open Data Repositories

2021 ◽  
Author(s):  
Pedro H. M. Costa ◽  
André F. R. Cordeiro ◽  
Edson OliveiraJr
Keyword(s):  
Data Management ◽  
Open Data ◽  
Scientific Research ◽  
Open Science ◽  
Data Repositories ◽  
Data Format ◽  
Schema Versioning ◽  
Access Controls ◽  
Storage Limit ◽  
Data Collections

Open Data is one of the main concepts of Open Science, which has the purpose to make scientific research artifacts accessible for everyone. Open data provides recommendations and practices to get access and use data from scientific researches, in a free, permanent, citable, auditable and interchangeable way. To facilitate the data management, it is important to store them in a repository. Considering this context, this paper provides a comparison among five known open data repositories. We performed the comparison taking into account a set of criteria, such as, data format constraints, digital identifier, versioning of published datasets, curators of data collections, metadata schema, versioning and exportation, storage limit, paid services, redundancy and preservation, access controls and APIs. We present results and discussions, in terms of such criteria.

scholarly journals Nudging Open Science

2021 ◽  
Author(s):  
Samuel Gebhard Robson ◽  
Myriam A. Baum ◽  
Jennifer L Beaudry ◽  
Julia Beitner ◽  
Hilmar Brohmer ◽  
...  
Keyword(s):  
Academic Libraries ◽  
Culture Change ◽  
Scientific Practice ◽  
Scientific Research ◽  
Open Science ◽  
Research Culture ◽  
Small Shift ◽  
Open Research ◽  
The World

In this article, we provide a toolbox of resources and nudges for those who are interested in advancing open scientific practice. Open Science encompasses a range of behaviours that aim to include the transparency of scientific research and how widely it is communicated. The paper is divided into seven sections, each dealing with a different stakeholder in the world of research (researchers, students, departments and faculties, universities, academic libraries, journals, and funders). With two frameworks in mind — EAST and the Pyramid of Culture Change — we describe the influences and incentives that sway behaviour for each of these stakeholders, we outline changes that can foster Open Science, and suggest actions and resources for individuals to nudge these changes. In isolation, a small shift in one person’s behaviour may appear to make little difference, but when combined, these small shifts can lead to radical changes in culture. We offer this toolbox to assist individuals and institutions in cultivating a more open research culture.

scholarly journals Alignment of biomedical data repositories with open, FAIR, citable and trust-worthy principles

2021 ◽  
Author(s):  
Fiona Murphy ◽  
Michael Bar-Sinai ◽  
Maryann E. Martone
Keyword(s):  
Open Source ◽  
Open Science ◽  
Scientific Data ◽  
Information Network ◽  
Biomedical Data ◽  
Data Repositories ◽  
The World ◽  
Key Aspects ◽  
Biomedical Community

AbstractIncreasing attention is being paid to the operation of biomedical data repositories in light of efforts to improve how scientific data is handled and made available for the long term. Simultaneously, groups around the world have been coming together to formalize principles that govern different aspects of open science and data sharing.The most well known are the FAIR data principles. These are joined by principles and practices that govern openness, citation, credit and good stewardship (trustworthiness). Together, these define a framework for data repositories to support Open, FAIR, Citable and Trustworthy (OFCT) data. Here we developed an instrument using the open source PolicyModels toolkit that attempts to operationalize key aspects of OFCT principles and applied the instrument to eight biomedical community repositories listed by the NIDDK Information Network (dkNET.org). The evaluation was performed through inspection of documentation and interaction with the sites. Overall, there was little explicit acknowledgement of any of the OFCT principles, although the majority of repositories provided at least some support for their tenets.

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