scholarly journals Data management and sharing in neuroimaging: Practices and perceptions of MRI researchers

2018 ◽  
Author(s):  
John A. Borghi ◽  
Ana E. Van Gulick
Keyword(s):  
Data Collection ◽  
Data Management ◽  
Data Storage ◽  
Online Survey ◽  
Ad Hoc ◽  
Open Access Publishing ◽  
Complex Data ◽  
Data Collection And Analysis ◽  
Neuroimaging Data ◽  
Magnetic Resonance Imaging Mri

ABSTRACTNeuroimaging methods such as magnetic resonance imaging (MRI) involve complex data collection and analysis protocols, which necessitate the establishment of good research data management (RDM). Despite efforts within the field to address issues related to rigor and reproducibility, information about the RDM-related practices and perceptions of neuroimaging researchers remains largely anecdotal. To inform such efforts, we conducted an online survey of active MRI researchers that covered a range of RDM-related topics. Survey questions addressed the type(s) of data collected, tools used for data storage, organization, and analysis, and the degree to which practices are defined and standardized within a research group. Our results demonstrate that neuroimaging data is acquired in multifarious forms, transformed and analyzed using a wide variety of software tools, and that RDM practices and perceptions vary considerably both within and between research groups, with trainees reporting less consistency than faculty. Ratings of the maturity of RDM practices from ad-hoc to refined were relatively high during the data collection and analysis phases of a project and significantly lower during the data sharing phase. Perceptions of emerging practices including open access publishing and preregistration were largely positive, but demonstrated little adoption into current practice.

Producing Pathways to Proficient Pronunciation with Learner-Designed Pronunciation Stations

2014 ◽  
pp. 231-262
Author(s):  
James M. Perren
Keyword(s):  
Data Collection ◽  
Online Survey ◽  
Educational Innovation ◽  
Student Responsibility ◽  
Design Based Research ◽  
Analysis Methodology ◽  
Data Collection And Analysis ◽  
Poststructural Theory ◽  
Survey Results ◽  
Technology Resources

The chapter reports on a study examining learning stations designed by English as a second language students in order to improve pronunciation. This on-going Design-Based Research study focuses on promoting, sustaining, and understanding an educational innovation (Bell, 2004). The longitudinal study identifies favorable and unfavorable aspects of learner-designed pronunciation station teaching. Results extend previous iterations of data collection and analysis of student assignments with reference to technology resources and online survey results as part of strategic (re)designing of the activity. This pedagogy fosters student responsibility for learning and utilizing learning opportunities they create. Discussion is provided about how poststructural theory corresponds with design-based research as data collection and analysis methodology to illuminate discourses of autonomy as agency, motivation and investment, and resistance. Design-based research frames the postmodern and action oriented design based research goals of “examining the assumptions underlying contemporary educational programs and practices” (Reeves, McKenney, & Herrington, 2011, pp. 60-61).

Data Management at the University of Iowa: A University Libraries Report on Campus Research Data Needs

2020 ◽  
Author(s):  
Shawn Averkamp ◽  
Xiaomei Gu ◽  
Ben Rogers
Keyword(s):  
Data Collection ◽  
Data Management ◽  
Data Storage ◽  
Analysis Data ◽  
Data Publishing ◽  
Second Phase ◽  
Sensitive Data ◽  
University Of Iowa ◽  
Challenges And Opportunities ◽  
The University

<p>This data management report was commissioned by the University of Iowa Libraries with the intention of performing a survey of the campus landscape and identifying gaps in data management services. The first stage of data collection consisted of a survey conducted during summer 2012 to which 784 responses were received. The second phase of data collection consisted of approximately 40 in-depth interviews with individuals from the campus and were completed during summer 2013. Findings are presented as challenges and opportunities within five broad areas of data management: data management planning, data storage, data organization and analysis, data publishing and dissemination and sensitive data and compliance, with additional findings reported in the areas of research culture and funding models.</p>

scholarly journals Is there a problem with methods skills in cognitive neuroscience? Evidence from an online survey

2018 ◽  
Author(s):  
Olaf Hauk
Keyword(s):  
Data Analysis ◽  
Linear Algebra ◽  
Cognitive Neuroscience ◽  
Signal Analysis ◽  
Online Survey ◽  
Complex Data ◽  
Multiple Choice Questions ◽  
Neuroimaging Data ◽  
The Difference ◽  
Training Programmes

AbstractCognitive neuroscience increasingly relies on complex data analysis methods. Researchers in this field come from highly diverse scientific backgrounds, such as psychology, engineering and medicine. This poses challenges with respect to acquisition of appropriate scientific computing and data analysis skills, as well as communication among researchers with different knowledge and skills sets. Are researchers in cognitive neuroscience adequately equipped to address these challenges? Here, we present evidence from an online survey of methods skills. Respondents (n=305) mainly comprised students and post-doctoral researchers working in the cognitive neurosciences. Multiple choice questions addressed a variety of basic and fundamental aspects of neuroimaging data analysis, such as signal analysis, linear algebra, and statistics. We analysed performance with respect to the following factors: undergraduate degree (grouped into Psychology, Methods, Biology), current researcher status (undergraduate student, PhD student, post-doctoral researcher), gender, and self-rated expertise levels. Overall accuracy was 72%. Not surprisingly, the Methods group performed best (87%), followed by Biology (73%) and Psychology (66%). Accuracy increased from undergraduate (59%) to PhD (74%) level, but not from PhD to post-doctoral (74%) level. The difference in performance for the Methods versus non-methods (Psychology/Biology) groups was particularly striking for questions related to signal analysis and linear algebra, two areas especially relevant to neuroimaging research. Self-rated methods expertise was not strongly predictive of performance. The majority of respondents (93%) indicated they would like to receive at least some additional training on the topics covered in this survey. In conclusion, methods skills among junior researchers in cognitive neuroscience can be improved, researchers are aware of this, and there is strong demand for more skills-oriented training opportunities. We hope that this survey will provide an empirical basis for the development of bespoke skills-oriented training programmes in cognitive neuroscience institutions.

Mulligan Concept Use and Clinical Profile From the Perspective of American Certified Mulligan Practitioners

2015 ◽  
Vol 24 (4) ◽  
pp. 337-341 ◽  
Author(s):  
James May ◽  
Ryan Krzyzanowicz ◽  
Alan Nasypany ◽  
Russell Baker ◽  
Jeffrey Seegmiller
Keyword(s):  
Data Collection ◽  
Broad Spectrum ◽  
Online Survey ◽  
Clinical Care ◽  
Intervention Strategy ◽  
Survey Instrument ◽  
Clinical Profile ◽  
Clinical Practices ◽  
Data Collection And Analysis ◽  
Mulligan Concept

Context:Although randomized controlled trials indicate that the Mulligan Concept (MC) of mobilization with movement can improve pain-free grip strength and pressure pain threshold in patients with lateral epicondylalgia of the elbow, improve ankle dorsiflexion in patients with subacute ankle sprains, and decrease the signs and symptoms of patients with cervicogenic headache, little is known about the clinical application, use, and profile of certified Mulligan practitioners (CMPs) in America.Objective:To better understand the use and value of applying the MC philosophy in clinical-care environments from the perspective of American CMPs while establishing a clinical profile of a CMP.Design:Quantitative descriptive design. Setting: Online survey instrument.Participants:American CMPs.Data Collection and Analysis:Online survey instrument.Results:CMPs use the MC to treat a broad spectrum of spinal and peripheral clinical pathologies in primarily outpatient clinics with an active and athletic population. American CMPs also find value in the MC.Conclusions:American CMPs continue to use and find value in the MC intervention strategy to treat a broad spectrum of spinal and peripheral conditions in their clinical practices.

scholarly journals Young New Zealanders' Beliefs About Youth Suicide and How It Can Be Prevented

2019 ◽  
Author(s):  
Mikayla Holman ◽  
Matt Williams
Keyword(s):  
Mental Health ◽  
New Zealand ◽  
Mental Health Services ◽  
Data Collection ◽  
Health Services ◽  
Online Survey ◽  
Counselling Service ◽  
Youth Suicide ◽  
Data Collection And Analysis ◽  
The University

Objective: New Zealand has the highest suicide rate amongst youth (ages 15-24) in the OECD. In this study, we aimed to conduct a conceptual replication of two previous studies (Heled &amp; Read, 2005; Curtis, 2010), examining the views that youth in New Zealand hold about the causes of youth suicide, potential solutions, and help-seeking.Method: A detailed data collection and analysis plan was preregistered prior to data collection. One hundred university students aged 18 to 24 completed a mixed-methods online survey; 89% were female.Results: Just one of four hypotheses formulated based on the findings of Curtis (2010) was supported: Students who were personally aware of another student's suicidality were more willing to seek help for others from the university counselling service. Qualitative findings indicated that bullying and stigma were the most commonly perceived causes of youth suicide. Improvement of mental health services was the most frequently recommended solution for reducing the youth suicide rate.Conclusions: The views of youth should be included in the future development of mental health services and policies aimed at reducing suicide rates for this population.

scholarly journals Collaboration in RDM activities – Practices and development at Aalto University

2017 ◽  
Author(s):  
Maria Söderholm ◽  
Anne Sunikka
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Research Data ◽  
Service Planning ◽  
Open Access Publishing ◽  
Service Development ◽  
It Services ◽  
Data Services ◽  
Service Portfolio ◽  
Starting Point

Watch the VIDEO here. Presenter – Maria SöderholmResearch data management (RDM) is a complex and dynamic topic, and demands diverse expertise, skills and knowledge. The RDM expertise includes subtopics like collection/provision of data; storage and processing of data; long-term preservation requirements of the data; and funders’ demands and solutions to share, re-find and re-use research data. Usually the expertise related to these RDM subtopics is spread to several university units, both academic and administrative. Therefore, many tasks related to RDM, for example, day-to-day practices, the supply of services and the development work are best carried out in a network-based cooperation.In the presentation, we will introduce our RDM related partnership and networking of Aalto University. As a starting point, we introduce the internal service development working principles that our RDM network work is based on. However, the focus will be on describing our RDM working group and development activities.Aalto’s Research Data Management Programme forms the backbone for RDM work. It establishes seven separate action points for RDM activities: 1) open access  publishing; 2) implementation of data management planning tool; 3) metadata catalogue for open data; 4) data publishing; 5) comprehensive repository service for storage, back-up and collaboration; 6) combining openness and innovation; and 7) RDM awareness building activities. The actors in the RDM network consist of Research and Innovation Services (leading the group), IT Services, and Learning Centre (previously Library).In the presentation, we will introduce the core actors in more detail, paying attention to the complementarity of the roles; and the activities and the aims, which steer the work. We also discuss the meaning and consequences of the network-based cooperation for the working group.First, the RDM group acts as a joint platform for comprehensive RDM information. Important means of data gathering are surveys and informal discussion with researcher. In the future, formal group discussions on RDM needs are hosted. The previous discussions with researchers have underlined the importance of arranging services for both disciplinary and data specific needs in addition to common university level service needs.Second, the group is a messenger of the RDM topics. Our task is to rise internal RDM awareness and disseminate national and international information and development trends in the university.The third and the most challenging aim is the RDM service planning and delivery. Our task is to identify the existing in-house services, to map the suitable services provided by national and international agents as well as to recognize the needs for new services. Our service portfolio covers both consultation/informational services and technical, hands-on services. However, many of our research data services are still in the planning or piloting stage, thus cooperation with researchers is essential.In our experience, the network-based collaboration model that foster individuals’ interconnectedness is crucial for surviving with the built-in dynamism of RDM. This model provides a non-hierarchical and flexible environment for actions to meet the increasing expectations for research data services we face from the funders, governments, and researchers.

Electronic Data Collection Methods

2007 ◽  
pp. 28-43 ◽  
Author(s):  
M. Singh ◽  
S. Burgess
Keyword(s):  
Data Collection ◽  
Online Survey ◽  
New Technologies ◽  
Virtual Community ◽  
Research Process ◽  
Survey Method ◽  
Online Data ◽  
Electronic Data Collection ◽  
Focus Group Research ◽  
Data Collection And Analysis

This chapter discusses the application of new technologies to scholarly research. It highlights the process, benefits and challenges of online data collection and analysis with three case studies, the online survey method, online focus groups and email interviews. The online survey method is described as it was undertaken to collect and collate data for the evaluation of e-business in Australia. The online focus group research is described as it was applied to complete research on e-commerce with small business. The email interviews applied to collect information from a virtual community of global respondents to assess the impact of interaction between members on B2C e-commerce. The research process, its advantages and disadvantages are elaborated for all three e-research methods.

scholarly journals Replica Dissemination and Update Strategies in Cluster-Based Mobile Ad Hoc Networks

2006 ◽  
Vol 2 (4) ◽  
pp. 193-209 ◽  
Author(s):  
Mieso K. Denko ◽  
Hua Lu
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Ad Hoc ◽  
Data Access ◽  
Reliable Data ◽  
Data Consistency ◽  
Data Accessibility ◽  
Message Queue ◽  
Replica Allocation ◽  
Mobile Ad Hoc

A mobile ad hoc network (MANET) is a collection of wireless mobile nodes that forms a temporary network without the aid of a fixed communication infrastructure. Since every node can be mobile and network topology changes can occur frequently, node disconnection is a common mode of operation in MANETs. Providing reliable data access and message delivery is a challenge in this dynamic network environment. Caching and replica allocation within the network can improve data accessibility by storing the data and accessing them locally. However, maintaining data consistency among replicas becomes a challenging problem. Hence, balancing data accessibility and consistency is an important step toward data management in MANETs. In this paper, we propose a replica-based data-storage mechanism and undelivered-message queue schemes to provide reliable data storage and dissemination. We also propose replica update strategies to maintain data consistency while improving data accessibility. These solutions are based on a clustered MANET where nodes in the network are divided into small groups that are suitable for localized data management. The goal is to reduce communication overhead, support localized computation, and enhance scalability. A simulation environment was built using an NS-2 network simulator to evaluate the performance of the proposed schemes. The results show that our schemes distribute replicas effectively, provide high data accessibility rates and maintain consistency.

scholarly journals INCloud: integrated neuroimaging cloud for data collection, management, analysis and clinical translations

2021 ◽  
Vol 34 (6) ◽  
pp. e100651
Author(s):  
Qingfeng Li ◽  
Lijuan Jiang ◽  
Kaini Qiao ◽  
Yang Hu ◽  
Bing Chen ◽  
...  
Keyword(s):  
Data Mining ◽  
Mental Disorders ◽  
Data Collection ◽  
Data Management ◽  
Large Scale ◽  
Image Features ◽  
Collection Management ◽  
Technical Requirements ◽  
Neuroimaging Data ◽  
The Brain

BackgroundNeuroimaging techniques provide rich and accurate measures of brain structure and function, and have become one of the most popular methods in mental health and neuroscience research. Rapidly growing neuroimaging research generates massive amounts of data, bringing new challenges in data collection, large-scale data management, efficient computing requirements and data mining and analyses.AimsTo tackle the challenges and promote the application of neuroimaging technology in clinical practice, we developed an integrated neuroimaging cloud (INCloud). INCloud provides a full-stack solution for the entire process of large-scale neuroimaging data collection, management, analysis and clinical applications.MethodsINCloud consists of data acquisition systems, a data warehouse, automatic multimodal image quality check and processing systems, a brain feature library, a high-performance computing cluster and computer-aided diagnosis systems (CADS) for mental disorders. A unique design of INCloud is the brain feature library that converts the unit of data management from image to image features such as hippocampal volume. Connecting the CADS to the scientific database, INCloud allows the accumulation of scientific data to continuously improve the accuracy of objective diagnosis of mental disorders.ResultsUsers can manage and analyze neuroimaging data on INCloud, without the need to download them to the local device. INCloud users can query, manage, analyze and share image features based on customized criteria. Several examples of 'mega-analyses' based on the brain feature library are shown.ConclusionsCompared with traditional neuroimaging acquisition and analysis workflow, INCloud features safe and convenient data management and sharing, reduced technical requirements for researchers, high-efficiency computing and data mining, and straightforward translations to clinical service. The design and implementation of the system are also applicable to imaging research platforms in other fields.

scholarly journals A Survey on Using Biometrics for Cloud Security

2018 ◽  
Vol 7 (2.32) ◽  
pp. 307
Author(s):  
K Ruth Ramya ◽  
D N.V.Saikrishna ◽  
T Sravya Nandini ◽  
R Tanmai Gayatri
Keyword(s):  
Cloud Computing ◽  
Data Management ◽  
Data Storage ◽  
Cloud Security ◽  
Processing Technology ◽  
Public Key ◽  
Primary Concern ◽  
Complex Data ◽  
Cloud Data ◽  
Attribute Based Encryption

Cloud computing the most emerging data storage and processing technology. Today many organizations are using cloud-based data storage because of their complex data management. Even though cloud is attracting many users towards using it but there is a requirement of security concerns to be taken care of because cloud is untrusted, the data which individual stores on cloud will be transparent to cloud administrator also which may be confidential. So, while using cloud security is the primary concern. In this paper, we proposed a scheme to encrypt cloud data using user attribute-based encryption. Which is a public key crypto technique in which key will be based on the attributes of user. The attributes we used are biometrics of user who is going to upload the data.  

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