scholarly journals PsychData – Experiences from 12 Years of Research Data Archiving

2015 ◽  
Author(s):  
Peter Weiland ◽  
Ina Dehnhard
Keyword(s):  
Data Sharing ◽  
Large Scale ◽  
Research Data ◽  
Data Reuse ◽  
German Research Foundation ◽  
Cross Sectional ◽  
Data Archiving ◽  
Wide Range ◽  
Domain Specific Knowledge ◽  
Meta Analyses

See video of the presentation.The benefits of making research data permanently accessible through data archives is widely recognized: costs can be reduced by reusing existing data, research results can be compared and validated with results from archived studies, fraud can be more easily detected, and meta-analyses can be conducted. Apart from that, authors may gain recognition and reputation for producing the datasets. Since 2003, the accredited research data center PsychData (part of the Leibniz Institute for Psychology Information in Trier, Germany) documents and archives research data from all areas of psychology and related fields. In the beginning, the main focus was on datasets that provide a high potential for reuse, e.g. longitudinal studies, large-scale cross sectional studies, or studies that were conducted during historically unique conditions. Presently, more and more journal publishers and project funding agencies require researchers to archive their data and make them accessible for the scientific community. Therefore, PsychData also has to serve this need.In this presentation we report on our experiences in operating a discipline-specific research data archive in a domain where data sharing is met with considerable resistance. We will focus on the challenges for data sharing and data reuse in psychology, e.g.large amount of domain-specific knowledge necessary for data curationhigh costs for documenting the data because of a wide range on non-standardized measuressmall teams and little established infrastructures compared with the "big data" disciplinesstudies in psychology not designed for reuse (in contrast to the social sciences)data protectionresistance to sharing dataAt the end of the presentation, we will provide a brief outlook on DataWiz, a new project funded by the German Research Foundation (DFG). In this project, tools will be developed to support researchers in documenting their data during the research phase.

scholarly journals Taming the chaos: NHS professionals’ perspective of using video consulting during COVID-19 in Wales

2021 ◽  
Vol 10 (4) ◽  
pp. e001318
Author(s):  
Gemma Johns ◽  
Sara Khalil ◽  
Mike Ogonovsky ◽  
Markus Hesseling ◽  
Allan Wardhaugh ◽  
...  
Keyword(s):  
National Health Service ◽  
Large Scale ◽  
Future Research ◽  
Local Health ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Wide Range ◽  
Early Use ◽  
Observational Study Design ◽  
The Uk

The use of video consulting (VC) in the UK has expanded rapidly during the COVID-19 pandemic. Technology Enabled Care (TEC) Cymru, the Welsh Government and Local Health boards began implementing the National Health Service (NHS) Wales VC Service in March 2020. This has been robustly evaluated on a large-scale All-Wales basis, across a wide range of NHS Wales specialities.AimsTo understand the early use of VC in Wales from the perspective of NHS professionals using it. NHS professionals were approached by TEC Cymru to provide early data.MethodsUsing an observational study design with descriptive methods including a cross-sectional survey, TEC Cymru captured data on the use, benefits and challenges of VC from NHS professionals in Wales during August and September 2020. This evidence is based on the rapid adoption of VC in Wales, which mirrors that of other nations.ResultsA total of 1256 NHS professionals shared their VC experience. Overall, responses were positive, and professionals expressed optimistic views regarding the use and benefit of VC, even when faced with challenges on occasions.ConclusionsThis study provides evidence of general positivity, acceptance and the success of the VC service in Wales. Future research studies will now be able to explore and evaluate the implementation methods used within this study, and investigate their effectiveness in being able to achieve better outcomes through VC.

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 Community-curated and standardised metadata of published ancient metagenomic samples with AncientMetagenomeDir

2020 ◽  
Author(s):  
James A. Fellows Yates ◽  
Aida Andrades Valtueña ◽  
Ashild J. Vågene ◽  
Becky Cribdon ◽  
Irina M. Velsko ◽  
...  
Keyword(s):  
Large Scale ◽  
Genetic Data ◽  
Data Retrieval ◽  
Data Sources ◽  
Valuable Data ◽  
Dna And Rna ◽  
Wide Range ◽  
Evolutionary Studies ◽  
Meta Analyses ◽  
Microbial Samples

ABSTRACTAncient DNA and RNA are valuable data sources for a wide range of disciplines. Within the field of ancient metagenomics, the number of published genetic datasets has risen dramatically in recent years, and tracking this data for reuse is particularly important for large-scale ecological and evolutionary studies of individual microbial taxa, microbial communities, and metagenomic assemblages. AncientMetagenomeDir (archived at https://doi.org/10.5281/zenodo.3980833) is a collection of indices of published genetic data deriving from ancient microbial samples that provides basic, standardised metadata and accession numbers to allow rapid data retrieval from online repositories. These collections are community-curated and span multiple sub-disciplines in order to ensure adequate breadth and consensus in metadata definitions, as well as longevity of the database. Internal guidelines and automated checks to facilitate compatibility with established sequence-read archives and term-ontologies ensure consistency and interoperability for future meta-analyses. This collection will also assist in standardising metadata reporting for future ancient metagenomic studies.

scholarly journals A survey of researchers' needs and priorities for data sharing

2021 ◽  
Author(s):  
Iain Hrynaszkiewicz ◽  
James Harney ◽  
Lauren Cadwallader
Keyword(s):  
Data Sharing ◽  
Research Impact ◽  
Open Science ◽  
Research Data ◽  
Data Reuse ◽  
Data Availability ◽  
Data Repositories ◽  
Use Of Data ◽  
Share Data ◽  
Do So

PLOS has long supported Open Science. One of the ways in which we do so is via our stringent data availability policy established in 2014. Despite this policy, and more data sharing policies being introduced by other organizations, best practices for data sharing are adopted by a minority of researchers in their publications. Problems with effective research data sharing persist and these problems have been quantified by previous research as a lack of time, resources, incentives, and/or skills to share data. In this study we built on this research by investigating the importance of tasks associated with data sharing, and researchers’ satisfaction with their ability to complete these tasks. By investigating these factors we aimed to better understand opportunities for new or improved solutions for sharing data. In May-June 2020 we surveyed researchers from Europe and North America to rate tasks associated with data sharing on (i) their importance and (ii) their satisfaction with their ability to complete them. We received 728 completed and 667 partial responses. We calculated mean importance and satisfaction scores to highlight potential opportunities for new solutions to and compare different cohorts.Tasks relating to research impact, funder compliance, and credit had the highest importance scores. 52% of respondents reuse research data but the average satisfaction score for obtaining data for reuse was relatively low. Tasks associated with sharing data were rated somewhat important and respondents were reasonably well satisfied in their ability to accomplish them. Notably, this included tasks associated with best data sharing practice, such as use of data repositories. However, the most common method for sharing data was in fact via supplemental files with articles, which is not considered to be best practice.We presume that researchers are unlikely to seek new solutions to a problem or task that they are satisfied in their ability to accomplish, even if many do not attempt this task. This implies there are few opportunities for new solutions or tools to meet these researcher needs. Publishers can likely meet these needs for data sharing by working to seamlessly integrate existing solutions that reduce the effort or behaviour change involved in some tasks, and focusing on advocacy and education around the benefits of sharing data. There may however be opportunities - unmet researcher needs - in relation to better supporting data reuse, which could be met in part by strengthening data sharing policies of journals and publishers, and improving the discoverability of data associated with published articles.

scholarly journals Large scale research data archiving: Training for an inconvenient technology

2019 ◽  
Vol 36 ◽  
pp. 100523
Author(s):  
S. Patrick Calhoun ◽  
David Akin ◽  
Brett Zimmerman ◽  
Henry Neeman
Keyword(s):  
Large Scale ◽  
Research Data ◽  
Data Archiving

scholarly journals Data sharing practices and data availability upon request differ across scientific disciplines

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Leho Tedersoo ◽  
Rainer Küngas ◽  
Ester Oras ◽  
Kajar Köster ◽  
Helen Eenmaa ◽  
...  
Keyword(s):  
Data Sharing ◽  
Large Scale ◽  
Modern Science ◽  
Research Data ◽  
Data Availability ◽  
Research Articles ◽  
Scientific Disciplines ◽  
Funding Agencies ◽  
Share Data ◽  
Bonus Points

AbstractData sharing is one of the cornerstones of modern science that enables large-scale analyses and reproducibility. We evaluated data availability in research articles across nine disciplines in Nature and Science magazines and recorded corresponding authors’ concerns, requests and reasons for declining data sharing. Although data sharing has improved in the last decade and particularly in recent years, data availability and willingness to share data still differ greatly among disciplines. We observed that statements of data availability upon (reasonable) request are inefficient and should not be allowed by journals. To improve data sharing at the time of manuscript acceptance, researchers should be better motivated to release their data with real benefits such as recognition, or bonus points in grant and job applications. We recommend that data management costs should be covered by funding agencies; publicly available research data ought to be included in the evaluation of applications; and surveillance of data sharing should be enforced by both academic publishers and funders. These cross-discipline survey data are available from the plutoF repository.

scholarly journals Data policies and data archives as prerequisites of reproducible published research in economics journals

2014 ◽  
Author(s):  
Sven Vlaeminck
Keyword(s):  
Social Sciences ◽  
Data Sharing ◽  
Research Data ◽  
Technical Solution ◽  
German Research Foundation ◽  
Scholarly Journals ◽  
Related Data ◽  
The Social ◽  
Economics Journals ◽  
Published Research

>> See video of presentation (19 min.) In economics - as in many other branches of the social sciences- collaboratively working on data and sharing data is not very common, yet. This is also reflected in the professions’ journals, where policies on data management and data sharing currently exist for a small minority of journals only.I would like to introduce the presentation with some empirical results of a survey, in which economists working for the project EDaWaX (European Data Watch, a project funded by the German Research Foundation) analysed the data sharing behaviour of 488 US and European applied economists. Subsequently we give an overview on data policies of journals in economics and business studies. In the course of the EDaWaX project, the data policies in a sample of more than 300 economics journals have been analysed. The talk suggests guidelines for data policies aiming to foster replication of published research and presents some characteristics of journals equipped with those data policies as well as the status quo in disseminating underlying research data of empirically based articles.Against this analytical background the talk identifies some challenges associated with the current e-infrastructure for providing publication-related research data by journals. The presentation also shows a technical solution for some of these challenges. In particular, the talk presents a pilot application for a publication-related data archive for scholarly journals in the social sciences, which has been developed in the first funding phase of the EDaWaX-project. The aim of this open source tool is to empower editors of scholarly journals to easily manage research data for empirically based articles in their journals. The application mainly targets open research data but is also capable of interlinking data and publications even in the case of confidential or proprietary data.In conclusion the talk outlines the further development of our application and sketches other tasks of the project’s second funding phase.More information on the project is available on www.edawax.de  

scholarly journals A review of data sharing statements in observational studies published in the BMJ: A cross-sectional study

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1708 ◽  
Author(s):  
Laura McDonald ◽  
Anna Schultze ◽  
Alex Simpson ◽  
Sophie Graham ◽  
Radek Wasiak ◽  
...  
Keyword(s):  
Medical Journal ◽  
Data Sharing ◽  
Exploratory Study ◽  
Observational Studies ◽  
Cross Sectional Study ◽  
Research Data ◽  
Observational Research ◽  
Sectional Study ◽  
Cross Sectional ◽  
Current State

In order to understand the current state of data sharing in observational research studies, we reviewed data sharing statements of observational studies published in a general medical journal, the British Medical Journal. We found that the majority (63%) of observational studies published between 2015 and 2017 included a statement that implied that data used in the study could not be shared. If the findings of our exploratory study are confirmed, room for improvement in the sharing of real-world or observational research data exists.

scholarly journals Responding to Reality: Evolving Curation Practices and Infrastructure at the University of Illinois at Urbana-Champaign

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Hoa Q. Luong ◽  
Colleen Fallaw ◽  
Genevieve Schmitt ◽  
Susan M. Braxton ◽  
Heidi Imker
Keyword(s):  
Data Sharing ◽  
Positive Impact ◽  
Data Bank ◽  
Research Data ◽  
Data Reuse ◽  
Data Repository ◽  
Data Service ◽  
University Of Illinois ◽  
Service Offering ◽  
The University

Objective: The Illinois Data Bank provides Illinois researchers with the infrastructure to publish research data publicly. During a five-year review of the Research Data Service at the University of Illinois at Urbana-Champaign, it was recognized as the most useful service offering in the unit. Internal metrics are captured and used to monitor the growth, document curation workflows, and surface technical challenges faced as we assist our researchers. Here we present examples of these curation challenges and the solutions chosen to address them. Methods: Some Illinois Data Bank metrics are collected internally by within the system, but most of the curation metrics reported here are tracked separately in a Google spreadsheet. The curator logs required information after curation is complete for each dataset. While the data is sometimes ambiguous (e.g., depending on researcher uptake of suggested actions), our curation data provide a general understanding about our data repository and have been useful in assessing our workflows and services. These metrics also help prioritize development needs for the Illinois Data Bank. Results and Conclusions: The curatorial services polish and improve the datasets, which contributes to the spirit of data reuse. Although we continue to see challenges in our processes, curation makes a positive impact on datasets. Continued development and adaptation of the technical infrastructure allows for an ever-better experience for the curators and users. These improvements have helped our repository more effectively support the data sharing process by successfully fostering depositor engagement with curators to improve datasets and facilitating easy transfer of very large files.

Diminished recall and the cohort effect of major depression: a simulation study

1994 ◽  
Vol 24 (2) ◽  
pp. 375-383 ◽  
Author(s):  
Luis A. Giuffra ◽  
Neil Risch
Keyword(s):  
Simulation Study ◽  
Large Scale ◽  
Cohort Effect ◽  
Secular Trends ◽  
Cross Sectional ◽  
Total Period ◽  
Cohort Differences ◽  
Epidemiological Surveys ◽  
Wide Range ◽  
Cross Sectional Studies

SynopsisSeveral large-scale epidemiological surveys have reported increasing lifetime rates of psychopathology among recently born cohorts. In the case of Major Depressive Disorder (MDD) younger cohorts tend to manifest higher lifetime prevalences of the condition than older cohorts, at any given age. In some studies, cohort differences are so large that the youngest cohort exceeds the lifetime prevalence of the oldest cohort well before passing through their total period of risk. The data on lifetime prevalences that support the existence of secular differences, however, has typically been collected in cross-sectional studies. Thus, individuals are interviewed at a single point in time and asked to recall all prior psychopathology. Due to poor recall, this design may greatly underestimate earlier experiences. In fact, cohort differences are not limited to MDD; similar results have been reported for a wide range of psychopathology, suggesting methodological problems at data collection. We have conducted a simulation study to examine the magnitude of annual rates of forgetting that could produce the secular trends reported for MDD. Small, but constant annual rates produce striking, ‘cohort effect-like’ curves. The rates needed to reconstruct the reported effect are compatible with published values for test–retest studies of lifetime recall of MDD.This simulation study does not rule out the existence of a cohort effect in some psychiatric disorders, but stresses the possible limitations of using cross-sectional studies to investigate secular trends.

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