"Open science, data sharing, software sharing", are you ready?

2016 ◽  
Vol 24 (6) ◽  
pp. 995
Author(s):  
Ying ZHU
Keyword(s):  
Data Sharing ◽  
Open Science ◽  
Science Data

scholarly journals Open Science, Data Analysis, and Data Sharing

2021 ◽  
Author(s):  
Daniel Richard Isbell
Keyword(s):  
Data Analysis ◽  
Best Practices ◽  
Data Sharing ◽  
Open Science ◽  
Science Data ◽  
Recommended Practices ◽  
Science Framework

Collecting and analyzing data can be arduous, time-consuming labor. Our first instincts might not be to give the data away and reveal the steps behind the ‘magic’ of analyses. Nonetheless, sharing data and analysis steps increases the credibility and utility of our work, and ultimately contributes to a more efficient, cumulative science. Of course, recognizing the value of data and analysis sharing is one thing – actually doing the sharing is another. Sharing data and analyses is fraught with uncertainties (e.g., What should I share? What can I share? Will my data spreadsheet and analysis script even make sense to someone else?) and, at the end of the day, amounts to additional tasks to be completed. This chapter goes beyond persuading readers to share and presents answers to common questions, advice for best practices, and practical steps for sharing that can be integrated into your research workflow. Easy-to-use, free resources like R, RStudio, and the Open Science Framework are introduced for implementing recommended practices.

scholarly journals Open science, data sharing and solidarity: who benefits?

2021 ◽  
Vol 43 (4) ◽  
Author(s):  
Ciara Staunton ◽  
Carlos Andrés Barragán ◽  
Stefano Canali ◽  
Calvin Ho ◽  
Sabina Leonelli ◽  
...  
Keyword(s):  
Social Studies ◽  
Data Sharing ◽  
Personal Data ◽  
Open Science ◽  
Cold Spring Harbor Laboratory ◽  
Science Data ◽  
Biennial Conference ◽  
Cold Spring ◽  
Social Studies Of Biology ◽  
Science Movement

AbstractResearch, innovation, and progress in the life sciences are increasingly contingent on access to large quantities of data. This is one of the key premises behind the “open science” movement and the global calls for fostering the sharing of personal data, datasets, and research results. This paper reports on the outcomes of discussions by the panel “Open science, data sharing and solidarity: who benefits?” held at the 2021 Biennial conference of the International Society for the History, Philosophy, and Social Studies of Biology (ISHPSSB), and hosted by Cold Spring Harbor Laboratory (CSHL).

Introduction to the special section on Increasing Replicability, Transparency, and Openness in Clinical Psychology

2019 ◽  
Author(s):  
Jennifer L Tackett ◽  
Josh Miller
Keyword(s):  
Empirical Evidence ◽  
Data Sharing ◽  
Clinical Psychology ◽  
Special Section ◽  
Psychological Research ◽  
Open Science ◽  
Clinical Psychologists ◽  
Existing Problems

As psychological research comes under increasing fire for the crisis of replicability, attention has turned to methods and practices that facilitate (or hinder) a more replicable and veridical body of empirical evidence. These trends have focused on “open science” initiatives, including an emphasis on replication, transparency, and data sharing. Despite this broader movement in psychology, clinical psychologists and psychiatrists have been largely absent from the broader conversation on documenting the extent of existing problems as well as generating solutions to problematic methods and practices in our area (Tackett et al., 2017). The goal of the current special section was to bring together psychopathology researchers to explore these and related areas as they pertain to the types of research conducted in clinical psychology and allied disciplines.

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 Data Papers as a New Form of Knowledge Organization in the Field of Research Data

2019 ◽  
Vol 46 (8) ◽  
pp. 622-638
Author(s):  
Joachim Schöpfel ◽  
Dominic Farace ◽  
Hélène Prost ◽  
Antonella Zane
Keyword(s):  
Business Models ◽  
Open Science ◽  
Research Data ◽  
Data Driven ◽  
Academic Publishing ◽  
Science Data ◽  
Research Data Management ◽  
Fair Principles ◽  
New Form ◽  
Machine Readable

Data papers have been defined as scholarly journal publications whose primary purpose is to describe research data. Our survey provides more insights about the environment of data papers, i.e., disciplines, publishers and business models, and about their structure, length, formats, metadata, and licensing. Data papers are a product of the emerging ecosystem of data-driven open science. They contribute to the FAIR principles for research data management. However, the boundaries with other categories of academic publishing are partly blurred. Data papers are (can be) generated automatically and are potentially machine-readable. Data papers are essentially information, i.e., description of data, but also partly contribute to the generation of knowledge and data on its own. Part of the new ecosystem of open and data-driven science, data papers and data journals are an interesting and relevant object for the assessment and understanding of the transition of the former system of academic publishing.

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