scholarly journals Testing the FAIR metrics on data catalogs

2018 ◽  
Author(s):  
Jarno A A van Erp ◽  
Carolyn D Langen ◽  
Anca Boon ◽  
Kees van Bochove
Keyword(s):  
Scientific Community ◽  
Daily Practice ◽  
Open Science ◽  
White Paper ◽  
Scientific Data ◽  
Open Source Data ◽  
Starting Point ◽  
Important Solution ◽  
Public Money ◽  
The Moment

The introduction of the FAIR –Findable, Accessible, Interoperable, Reusable– principles has caused quite an uproar within the scientific community. Principles which, if everyone adheres to them, could result in new, revolutionary ways of performing research and fulfill the promise of open science. Furthermore, it allows for concepts such as personalized medicine and personal health monitoring to -finally- become implemented in daily practice. However, to bring about these changes, data users need to rethink the way they treat scientific data. Just passing a dataset along, without extensive metadata will not suffice anymore. Such new ways of executing research require a significantly different approach from the entire scientific community or, for that matter, anyone who wants to reap the benefits from going FAIR. Yet, how do you initiate behavioral change? One important solution is by changing the software scientists use and requiring data owners, or data stewards, to FAIRify their dataset. Data catalogs are a great starting point for FAIRifying data as the software already intends to make data Findable and Accessible, while the metadata is Interoperable and relying on users to provide sufficient metadata to ensure Reusability. In this paper we analyse how well the FAIR principles are implemented in several data catalogs. To determine how FAIR a catalog is, the FAIR metrics were created by the GO-FAIR initiative. These metrics help determine to what extend data can be considered FAIR. However, the metrics were only recently developed, being first released at the end of 2017. At the moment software does not come standard with a FAIR metrics review. Still, this insight is highly desired by the scientific community. How else can they be sure that (public) money is spend in a FAIR way? The Hyve has tested/evaluated three popular open source data catalogs based on the FAIR metrics: CKAN, Dataverse, and Invenio. Most data stewards will be familiar with at least one of these. Within this white paper we provide answers to the following questions: Which of the three data catalogs performs best in making data FAIR? Which data catalog utilizes FAIR datasets the most? Which one creates the most FAIR metadata? Which catalog has the highest potential to increase its FAIRness, and how? Which data catalog facilitates the FAIRifying process the best?

scholarly journals Testing the FAIR metrics on data catalogs

2018 ◽  
Author(s):  
Jarno A A van Erp ◽  
Carolyn D Langen ◽  
Anca Boon ◽  
Kees van Bochove
Keyword(s):  
Scientific Community ◽  
Daily Practice ◽  
Open Science ◽  
White Paper ◽  
Scientific Data ◽  
Open Source Data ◽  
Starting Point ◽  
Important Solution ◽  
Public Money ◽  
The Moment

The introduction of the FAIR –Findable, Accessible, Interoperable, Reusable– principles has caused quite an uproar within the scientific community. Principles which, if everyone adheres to them, could result in new, revolutionary ways of performing research and fulfill the promise of open science. Furthermore, it allows for concepts such as personalized medicine and personal health monitoring to -finally- become implemented in daily practice. However, to bring about these changes, data users need to rethink the way they treat scientific data. Just passing a dataset along, without extensive metadata will not suffice anymore. Such new ways of executing research require a significantly different approach from the entire scientific community or, for that matter, anyone who wants to reap the benefits from going FAIR. Yet, how do you initiate behavioral change? One important solution is by changing the software scientists use and requiring data owners, or data stewards, to FAIRify their dataset. Data catalogs are a great starting point for FAIRifying data as the software already intends to make data Findable and Accessible, while the metadata is Interoperable and relying on users to provide sufficient metadata to ensure Reusability. In this paper we analyse how well the FAIR principles are implemented in several data catalogs. To determine how FAIR a catalog is, the FAIR metrics were created by the GO-FAIR initiative. These metrics help determine to what extend data can be considered FAIR. However, the metrics were only recently developed, being first released at the end of 2017. At the moment software does not come standard with a FAIR metrics review. Still, this insight is highly desired by the scientific community. How else can they be sure that (public) money is spend in a FAIR way? The Hyve has tested/evaluated three popular open source data catalogs based on the FAIR metrics: CKAN, Dataverse, and Invenio. Most data stewards will be familiar with at least one of these. Within this white paper we provide answers to the following questions: Which of the three data catalogs performs best in making data FAIR? Which data catalog utilizes FAIR datasets the most? Which one creates the most FAIR metadata? Which catalog has the highest potential to increase its FAIRness, and how? Which data catalog facilitates the FAIRifying process the best?

scholarly journals Testing the FAIR metrics on data catalogs

2018 ◽  
Author(s):  
Jarno A A van Erp ◽  
Carolyn D Langen ◽  
Anca Boon ◽  
Kees van Bochove
Keyword(s):  
Scientific Community ◽  
Daily Practice ◽  
Open Science ◽  
White Paper ◽  
Scientific Data ◽  
Open Source Data ◽  
Starting Point ◽  
Important Solution ◽  
Public Money ◽  
The Moment

The introduction of the FAIR –Findable, Accessible, Interoperable, Reusable– principles has caused quite an uproar within the scientific community. Principles which, if everyone adheres to them, could result in new, revolutionary ways of performing research and fulfill the promise of open science. Furthermore, it allows for concepts such as personalized medicine and personal health monitoring to -finally- become implemented in daily practice. However, to bring about these changes, data users need to rethink the way they treat scientific data. Just passing a dataset along, without extensive metadata will not suffice anymore. Such new ways of executing research require a significantly different approach from the entire scientific community or, for that matter, anyone who wants to reap the benefits from going FAIR. Yet, how do you initiate behavioral change? One important solution is by changing the software scientists use and requiring data owners, or data stewards, to FAIRify their dataset. Data catalogs are a great starting point for FAIRifying data as the software already intends to make data Findable and Accessible, while the metadata is Interoperable and relying on users to provide sufficient metadata to ensure Reusability. In this paper we analyse how well the FAIR principles are implemented in several data catalogs. To determine how FAIR a catalog is, the FAIR metrics were created by the GO-FAIR initiative. These metrics help determine to what extend data can be considered FAIR. However, the metrics were only recently developed, being first released at the end of 2017. At the moment software does not come standard with a FAIR metrics review. Still, this insight is highly desired by the scientific community. How else can they be sure that (public) money is spend in a FAIR way? The Hyve has tested/evaluated three popular open source data catalogs based on the FAIR metrics: CKAN, Dataverse, and Invenio. Most data stewards will be familiar with at least one of these. Within this white paper we provide answers to the following questions: Which of the three data catalogs performs best in making data FAIR? Which data catalog utilizes FAIR datasets the most? Which one creates the most FAIR metadata? Which catalog has the highest potential to increase its FAIRness, and how? Which data catalog facilitates the FAIRifying process the best?

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.

L’absence chez Michel Butor. L’Emploi du temps et Degrés

2012 ◽  
pp. 66-80
Author(s):  
Michał Mrozowicki
Keyword(s):  
Human Memory ◽  
Point Of View ◽  
Narrative Discourse ◽  
The Novel ◽  
Michel Butor ◽  
Starting Point ◽  
One Year ◽  
The Moment ◽  
Narrative Mode ◽  
The City

Michel Butor, born in 1926, one of the leaders of the French New Novel movement, has written only four novels between 1954 and 1960. The most famous of them is La Modification (Second thoughts), published in 1957. The author of the paper analyzes two other Butor’s novels: L’Emploi du temps (Passing time) – 1956, and Degrés (Degrees) – 1960. The theme of absence is crucial in both of them. In the former, the novel, presented as the diary of Jacques Revel, a young Frenchman spending a year in Bleston (a fictitious English city vaguely similar to Manchester), describes the narrator’s struggle to survive in a double – spatial and temporal – labyrinth. The first of them, formed by Bleston’s streets, squares and parks, is symbolized by the City plan. During his one year sojourn in the city, using its plan, Revel learns patiently how to move in its different districts, and in its strange labyrinth – strange because devoid any centre – that at the end stops annoying him. The other, the temporal one, symbolized by the diary itself, the labyrinth of the human memory, discovered by the narrator rather lately, somewhere in the middle of the year passed in Bleston, becomes, by contrast, more and more dense and complex, which is reflected by an increasinly complex narration used to describe the past. However, at the moment Revel is leaving the city, he is still unable to recall and to describe the events of the 29th of February 1952. This gap, this absence, symbolizes his defeat as the narrator, and, in the same time, the human memory’s limits. In Degrees temporal and spatial structures are also very important. This time round, however, the problems of the narration itself, become predominant. Considered from this point of view, the novel announces Gerard Genette’s work Narrative Discourse and his theoretical discussion of two narratological categories: narrative voice and narrative mode. Having transgressed his narrative competences, Pierre Vernier, the narrator of the first and the second parts of the novel, who, taking as a starting point, a complete account of one hour at school, tries to describe the whole world and various aspects of the human civilization for the benefit of his nephew, Pierre Eller, must fail and disappear, as the narrator, from the third part, which is narrated by another narrator, less audacious and more credible.

scholarly journals Total SciComm: A Strategy for Communicating Open Science

Publications ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 31
Author(s):  
Manh-Toan Ho ◽  
Manh-Tung Ho ◽  
Quan-Hoang Vuong
Keyword(s):  
Social Media ◽  
Science Communication ◽  
Scientific Community ◽  
Open Data ◽  
Open Science ◽  
Central Idea ◽  
Retracted Article ◽  
Scientific Ideas

This paper seeks to introduce a strategy of science communication: Total SciComm or all-out science communication. We proposed that to maximize the outreach and impact, scientists should use different media to communicate different aspects of science, from core ideas to methods. The paper uses an example of a debate surrounding a now-retracted article in the Nature journal, in which open data, preprints, social media, and blogs are being used for a meaningful scientific conversation. The case embodied the central idea of Total SciComm: the scientific community employs every medium to communicate scientific ideas and engages all scientists in the process.

scholarly journals POS1391 MEASURING SUBCLINICAL INFLAMMATION IN HAND AND FOREFOOT IN PATIENTS WITH ARTHRALGIA USING 1.5T OR 3.0T MRI: DOES FIELD STRENGTH MATTER?

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 978.1-978
Author(s):  
D. Krijbolder ◽  
M. Verstappen ◽  
F. Wouters ◽  
L. R. Lard ◽  
P. D. De Buck ◽  
...  
Keyword(s):  
Field Strength ◽  
Scientific Evidence ◽  
Correlation Coefficients ◽  
Daily Practice ◽  
Scientific Data ◽  
Imaging Features ◽  
Subclinical Inflammation ◽  
The Individual ◽  
3.0T Mri ◽  
Inflammation Score

Background:Magnetic resonance imaging (MRI) of small joints sensitively detects inflammation. MRI-detected subclinical inflammation, and tenosynovitis in particular, has been shown predictive for RA development in patients with arthralgia. These scientific data are mostly acquired on 1.0T-1.5T MRI scanners. However, 3.0T MRI is nowadays increasingly used in practice. Evidence on the comparability of these field strengths is scarce and it has never been studied in arthralgia where subclinical inflammation is subtle. Moreover, comparisons never included tenosynovitis, which is, of all imaging features, the strongest predictor for progression to RA.Objectives:To determine if there is a difference between 1.5T and 3.0T MRI in detecting subclinical inflammation in arthralgia patients.Methods:2968 locations (joints, bones or tendon sheaths) in hands and forefeet of 28 arthralgia patients were imaged on both 1.5T and 3.0T MRI. Two independent readers scored for erosions, osteitis, synovitis (according to RAMRIS) and tenosynovitis (as described by Haavaardsholm et al.). Scores were also summed as total inflammation (osteitis, synovitis and tenosynovitis) and total RAMRIS (erosions, osteitis, synovitis and tenosynovitis) scores. Interreader reliability (comparing both readers) and field strength agreement (comparing 1.5T and 3.0T) was assessed with interclass correlation coefficients (ICCs). Next, field strength agreement was assessed after dichotomization into presence or absence of inflammation. Analyses were performed on patient- and location-level.Results:ICCs between readers were excellent (>0.90). Comparing 1.5 and 3.0T revealed excellent ICCs of 0.90 (95% confidence interval 0.78-0.95) for the total inflammation score and 0.90 (0.78-0.95) for the total RAMRIS score. ICCs for individual inflammation features were: tenosynovitis: 0.87 (0.74-0.94), synovitis 0.65 (0.24-0.84) and osteitis 0.96 (0.91-0.98). The field strength agreement on dichotomized scores was 83% for the total inflammation score and 89% for the total RAMRIS score. Of the individual features, agreement for tenosynovitis was the highest (89%). Analyses on location- level showed similar results.Conclusion:Agreement of subclinical inflammation scores on 1.5T and 3.0T were good to excellent, in particular for tenosynovitis. This suggests that scientific evidence on predictive power of MRI in arthralgia patients, obtained on 1.5T, can be generalized to 3.0T when this field strength would be used for diagnostic purposes in daily practice.Disclosure of Interests:None declared

scholarly journals WORCS: A workflow for open reproducible code in science

Data Science ◽  
2021 ◽  
pp. 1-21
Author(s):  
Caspar J. Van Lissa ◽  
Andreas M. Brandmaier ◽  
Loek Brinkman ◽  
Anna-Lena Lamprecht ◽  
Aaron Peikert ◽  
...  
Keyword(s):  
Best Practices ◽  
Source Code ◽  
R Package ◽  
Open Science ◽  
Research Projects ◽  
Tabular Data ◽  
Step Procedure ◽  
Starting Point ◽  
Conducting Research ◽  
And Training

Adopting open science principles can be challenging, requiring conceptual education and training in the use of new tools. This paper introduces the Workflow for Open Reproducible Code in Science (WORCS): A step-by-step procedure that researchers can follow to make a research project open and reproducible. This workflow intends to lower the threshold for adoption of open science principles. It is based on established best practices, and can be used either in parallel to, or in absence of, top-down requirements by journals, institutions, and funding bodies. To facilitate widespread adoption, the WORCS principles have been implemented in the R package worcs, which offers an RStudio project template and utility functions for specific workflow steps. This paper introduces the conceptual workflow, discusses how it meets different standards for open science, and addresses the functionality provided by the R implementation, worcs. This paper is primarily targeted towards scholars conducting research projects in R, conducting research that involves academic prose, analysis code, and tabular data. However, the workflow is flexible enough to accommodate other scenarios, and offers a starting point for customized solutions. The source code for the R package and manuscript, and a list of examplesof WORCS projects, are available at https://github.com/cjvanlissa/worcs.

scholarly journals Traditional Applications of Tannin Rich Extracts Supported by Scientific Data: Chemical Composition, Bioavailability and Bioaccessibility

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 251
Author(s):  
Maria Fraga-Corral ◽  
Paz Otero ◽  
Lucia Cassani ◽  
Javier Echave ◽  
Paula Garcia-Oliveira ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Chemical Nature ◽  
Scientific Evidence ◽  
Scientific Data ◽  
Attractive Alternative ◽  
Chemical Profile ◽  
Traditional Use ◽  
Starting Point ◽  
Scientific Approach ◽  
Food Applications

Tannins are polyphenolic compounds historically utilized in textile and adhesive industries, but also in traditional human and animal medicines or foodstuffs. Since 20th-century, advances in analytical chemistry have allowed disclosure of the chemical nature of these molecules. The chemical profile of extracts obtained from previously selected species was investigated to try to establish a bridge between traditional background and scientific data. The study of the chemical composition of these extracts has permitted us to correlate the presence of tannins and other related molecules with the effectiveness of their apparent uses. The revision of traditional knowledge paired with scientific evidence may provide a supporting background on their use and the basis for developing innovative pharmacology and food applications based on formulations using natural sources of tannins. This traditional-scientific approach can result useful due to the raising consumers’ demand for natural products in markets, to which tannin-rich extracts may pose an attractive alternative. Therefore, it is of interest to back traditional applications with accurate data while meeting consumer’s acceptance. In this review, several species known to contain high amounts of tannins have been selected as a starting point to establish a correlation between their alleged traditional use, tannins content and composition and potential bioaccessibility.

scholarly journals Influence of Nature at the Time of the Pandemic: An Experience-Based Survey at the Time of SARS-CoV-2 to Demonstrate How Even a Short Break in Nature Can Reduce Stress for Healthcare Staff

2021 ◽  
pp. 193758672199111
Author(s):  
Marco Gola ◽  
Monica Botta ◽  
Anna Lisa D’Aniello ◽  
Stefano Capolongo
Keyword(s):  
Scientific Community ◽  
Well Being ◽  
Hospital Staff ◽  
Green Spaces ◽  
Profile Of Mood States ◽  
Evidence Based ◽  
Healthcare Staff ◽  
Daily Lives ◽  
Multidisciplinary Working ◽  
The Moment

Aim: The current COVID-19 pandemic has been causing significant upheavals in the daily lives of citizens and consequently also their mood (stress, distraction, anxiety, etc.), especially during the lockdown phase. The aim of the investigation is to evaluate the benefits of 20–30 minutes in contact with nature. Background: The Scientific Community, also through the evidence-based design approach, has already demonstrated the importance of greenery and nature on the psychophysical well-being of people and, in a moment of emergency, contact with the nature can be therapeutic and quite influential on the mental health of staff subject to stress. Method: During the lockdown, an Italian multidisciplinary working group promoted an experience-based survey, based on the Profile of Mood States methodology, for measuring the psychophysical well-being of hospital staff. Results: The author collected 77 questionnaires. The benefits that users have obtained from the experience in nature have been investigated by comparing the type of stresses they were subjected to and highlighting various peculiarities in the data analysis associated with the type of green in which they carried out the survey, the healthcare areas in which they worked during the pandemic emergency, and the moment in which the survey was conducted. Conclusions: The study has highlighted that a short break in green spaces strongly influenced the mental and psychophysical well-being of hospital staff, emphasizing the importance of nearby green spaces in architectures for health. Even a brief break in nature can regenerate users, especially in times of a stressful health emergency.

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