scholarly journals Tutkimusaineiston avoin jakaminen – tutkimusorganisaatioiden jäsenten käsityksiä, kokemuksia ja mielipiteitä

2018 ◽  
Vol 37 (4) ◽  
Author(s):  
Heidi Enwald
Keyword(s):  
Data Sharing ◽  
Data Storage ◽  
Online Survey ◽  
Open Science ◽  
Research Data ◽  
Research Field ◽  
Open Research ◽  
Research Organizations ◽  
Data Collection Instrument ◽  
In The Beginning

Open research data is data that is free to access, reuse, and redistribute. This study focuses on the perceptions, opinions and experiences of staff and researchers of research institutes on topics related to open research data. Furthermore, the differences across gender, role in the research organization and research field were investigated. An international questionnaire survey, translated into Finnish and Swedish, was used as the data collection instrument. An online survey was distributed through an open science related network to Finnish research organizations. In the end, 469 responded to all 24 questions of the survey. Findings indicate that many are still unaware or uncertain about issues related to data sharing and long-term data storage. Women as well as staff and researchers of medical and health sciences were most concerned about the possible problems associated with data sharing. Those in the beginning of their scientific careers, hesitated about sharing their data.

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.

scholarly journals Práticas e percepções dos pesquisadores brasileiros sobre serviços de acesso aberto a dados de pesquisa | Practices and perceptions of Brazilian researchers on open access to research data

2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Sonia Elisa Caregnato ◽  
Samile Andrea de Souza Vanz ◽  
Caterina Groposo Pavão ◽  
Paula Caroline Jardim Schifino Passos ◽  
Eduardo Borges ◽  
...  
Keyword(s):  
Open Access ◽  
Data Sharing ◽  
Research Data ◽  
Exploratory Analysis ◽  
Data Reuse ◽  
Institutional Repositories ◽  
Open Research

RESUMO O artigo apresenta análise exploratória das práticas e das percepções a respeito do acesso aberto a dados de pesquisa embasada em dados coletados por meio de survey, realizada com pesquisadores brasileiros. As 4.676 respostas obtidas demonstram que, apesar do grande interesse pelo tema, evidenciado pela prevalência de variáveis relacionadas ao compartilhamento e ao uso de dados e aos repositórios institucionais, não há clareza por parte dos sujeitos sobre os principais tópicos relacionados. Conclui-se que, apesar da maioria dos pesquisadores afirmar que compartilha dados de pesquisa, a disponibilização desses dados de forma aberta e irrestrita ainda não é amplamente aceita.Palavras-chave: Dados Abertos de Pesquisa; Compartilhamento de Dados; Reuso de Dados.ABSTRACT This article presents an exploratory analysis of the practices and perceptions regarding open access to research data based on information collected by a survey with Brazilian researchers. The 4,676 responses show that, despite the great interest in the topic, evidenced by the prevalence of variables related to data sharing and use and to institutional repositories, there is no clarity on the part of the subjects on the main related topics. We conclude that, although the majority of the researchers share research data, the availability of this data in an open and unrestricted way is not yet widely accepted.Keywords: Open Research Data; Data Sharing; Data Reuse.

scholarly journals Towards Open Science for the Qualitative Researcher: From a Positivist to an Open Interpretation

2021 ◽  
Vol 20 ◽  
pp. 160940692110346
Author(s):  
Barbara Class ◽  
Miguel de Bruyne ◽  
Claire Wuillemin ◽  
Dimitri Donzé ◽  
Jean-Blaise Claivaz
Keyword(s):  
Open Science ◽  
Research Data ◽  
Decision Makers ◽  
Second Phase ◽  
Data Handling ◽  
Optimal Solutions ◽  
Qualitative Researcher ◽  
Open Research ◽  
Concrete Experience ◽  
Handling Practices

This reflection by a qualitative researcher stems from a concrete experience with data handling in a funded research project. The researcher followed Open Research Data guidelines and found optimal solutions to pseudonymise data, but this later evolved into a deep epistemological questioning on praxis. During the first phase of the project, a tailor-made software was developed with help from librarians and an IT professional to automate the pseudonymisation of the 150 data chunks generated by 16 students, 3 tutors and 3 decision makers. In the second phase of the project, this experience sparked questions about the meaning of such data handling and interpretations of Open Science, which led the researcher to suggest a framework for the professional development of qualitative researchers in their understanding of Open Science. The article raises awareness of normative frameworks in institutional data handling practices and calls for active contributions to defining qualitative research in an Open Science perspective, particularly taking as a reference the recent draft recommendation by UNESCO (2020)

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.

Opportunities for Adopting Open Research Data in Learning Analytics

2021 ◽  
pp. 29-60
Author(s):  
Katarzyna Biernacka ◽  
Niels Pinkwart
Keyword(s):  
Learning Analytics ◽  
Open Data ◽  
Publishing Research ◽  
Open Science ◽  
Research Data ◽  
Research Institutions ◽  
Open Research ◽  
Main Emphasis ◽  
Published Research ◽  
Made In

The relevance of open research data is already acknowledged in many disciplines. Demanded by publishers, funders, and research institutions, the number of published research data increases every day. In learning analytics though, it seems that data are not sufficiently published and re-used. This chapter discusses some of the progress that the learning analytics community has made in shifting towards open practices, and it addresses the barriers that researchers in this discipline have to face. As an introduction, the movement and the term open science is explained. The importance of its principles is demonstrated before the main focus is put on open data. The main emphasis though lies in the question, Why are the advantages of publishing research data not capitalized on in the field of learning analytics? What are the barriers? The authors evaluate them, investigate their causes, and consider some potential ways for development in the future in the form of a toolkit and guidelines.

scholarly journals Open-access policy and data-sharing practice in UK academia

2019 ◽  
Vol 46 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Yimei Zhu
Keyword(s):  
Open Access ◽  
Data Sharing ◽  
Secondary Data ◽  
Open Science ◽  
Research Data ◽  
Academic Disciplines ◽  
Free Access ◽  
Online Publishing ◽  
Institutional Repositories ◽  
Access To Data

Data sharing can be defined as the release of research data that can be used by others. With the recent open-science movement, there has been a call for free access to data, tools and methods in academia. In recent years, subject-based and institutional repositories and data centres have emerged along with online publishing. Many scientific records, including published articles and data, have been made available via new platforms. In the United Kingdom, most major research funders had a data policy and require researchers to include a ‘data-sharing plan’ when applying for funding. However, there are a number of barriers to the full-scale adoption of data sharing. Those barriers are not only technical, but also psychological and social. A survey was conducted with over 1800 UK-based academics to explore the extent of support of data sharing and the characteristics and factors associated with data-sharing practice. It found that while most academics recognised the importance of sharing research data, most of them had never shared or reused research data. There were differences in the extent of data sharing between different gender, academic disciplines, age and seniority. It also found that the awareness of Research Council UK’s (RCUK) Open-Access (OA) policy, experience of Gold and Green OA publishing, attitudes towards the importance of data sharing and experience of using secondary data were associated with the practice of data sharing. A small group of researchers used social media such as Twitter, blogs and Facebook to promote the research data they had shared online. Our findings contribute to the knowledge and understanding of open science and offer recommendations to academic institutions, journals and funding agencies.

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 Key Aspects of Open Data in Finnish RDI Cooperation between Higher Education and Businesses

2021 ◽  
pp. 1-13
Author(s):  
Seliina Päällysaho ◽  
Jaana Latvanen ◽  
Anttoni Lehto ◽  
Jaakko Riihimaa ◽  
Pekka Lahti ◽  
...  
Keyword(s):  
Higher Education ◽  
Open Data ◽  
Open Science ◽  
Research Data ◽  
General Level ◽  
Joint Research ◽  
Research Organizations ◽  
Universities Of Applied Sciences ◽  
Key Aspects ◽  
Five Phases

The article highlights aspects that should be considered during an open research, development, and innovation (RDI) process cycle to improve the utilization of research data and foster open cooperation between higher education and businesses. The viewpoint here is in publicly funded joint research projects of the universities of applied sciences (UAS), the concept is, however, applicable in other higher education and research organizations as well. There are various challenges related to research data management in general as well as to the openness and reuse of data and results. The findings of this article are based on the results of a two-day expert workshop, and these results are interlinked with five phases of an open RDI process cycle: planning, implementation, documentation, sharing, and commercialization. Various drivers and barriers can be identified in different stages of the process. On a general level, special attention must be paid to critical factors such as ownership and sharing of data and results, confidential information and business secrets as well as following the requirements of the open science policies of the participating organizations and funders. This article also highlights several best practices that should be considered in each phase of an open RDI process cycle with businesses.

scholarly journals A collective challenge: Open Science from the perspective of Science Europe

2019 ◽  
Vol 72 (2) ◽  
pp. 424-430
Author(s):  
Marie Timmermann
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Open Science ◽  
Research Data ◽  
Major Research ◽  
Research Data Management ◽  
Management Policies ◽  
Good Research ◽  
Quality Of Research

Open Science aims to enhance the quality of research by making research and its outputs openly available, reproducible and accessible. Science Europe, the association of major Research Funding Organisations and Research Performing Organisations, advocates data sharing as one of the core aspects of Open Science and promotes a more harmonised approach to data sharing policies. Good research data management is a prerequisite for Open Science and data management policies should be aligned as much as possible, while taking into account discipline-specific differences. Research data management is a broad and complex field with many actors involved. It needs collective efforts by all actors to work towards aligned policies that foster Open Science.

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