scholarly journals Using cloud-based, open-source technology to evaluate, improve, and rapidly disseminate community-based intervention data

2020 ◽  
Vol 27 (11) ◽  
pp. 1741-1746
Author(s):  
Carlene A Mayfield ◽  
Margaret E Gigler ◽  
Leslie Snapper ◽  
Jainmary Jose ◽  
Jackie Tynan ◽  
...  
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Formative Evaluation ◽  
Time Lapse ◽  
Data Governance ◽  
Governance System ◽  
Electronic Data Collection ◽  
Community Initiative ◽  
Collaborative Engagement ◽  
Stage 1

Abstract Building Uplifted Families (BUF) is a cross-sector community initiative to improve health and economic disparities in Charlotte, North Carolina. A formative evaluation strategy was used to support iterative process improvement and collaborative engagement of cross-sector partners. To address challenges with electronic data collection through REDCap Cloud, we developed the BUF Rapid Dissemination (BUF-RD) model, a multistage data governance system supplemented by open-source technologies, such as: Stage 1) data collection; Stage 2) data integration and analysis; and Stage 3) dissemination. In Stage 3, results were disseminated through an interactive dashboard developed in RStudio using RShiny and Shiny Server solutions. The BUF-RD model was successfully deployed in a 6-month beta test to reduce the time lapse between data collection and dissemination from 3 months to 2 weeks. Having up-to-date preliminary results led to improved BUF implementation, enhanced stakeholder engagement, and greater responsiveness and alignment of program resources to specific participant needs.

scholarly journals Electronic Data Management for Vaccine Trials in Low Resource Settings: Upgrades, Scalability, and Impact of ODK

2021 ◽  
Vol 9 ◽  
Author(s):  
Michael Marks ◽  
Sham Lal ◽  
Hannah Brindle ◽  
Pierre-Stéphane Gsell ◽  
Matthew MacGregor ◽  
...  
Keyword(s):  
Data Collection ◽  
Clinical Research ◽  
Data Management ◽  
Open Source ◽  
Large Scale ◽  
Democratic Republic Of Congo ◽  
World Health ◽  
Electronic Data ◽  
Diverse Range ◽  
Electronic Data Collection

Background: ODK provides software and standards that are popular solutions for off-grid electronic data collection and has substantial code overlap and interoperability with a number of related software products including CommCare, Enketo, Ona, SurveyCTO, and KoBoToolbox. These tools provide open-source options for off-grid use in public health data collection, management, analysis, and reporting. During the 2018–2020 Ebola epidemic in the North Kivu and Ituri regions of Democratic Republic of Congo, we used these tools to support the DRC Ministère de la Santé RDC and World Health Organization in their efforts to administer an experimental vaccine (VSV-Zebov-GP) as part of their strategy to control the transmission of infection.Method: New functions were developed to facilitate the use of ODK, Enketo and R in large scale data collection, aggregation, monitoring, and near-real-time analysis during clinical research in health emergencies. We present enhancements to ODK that include a built-in audit-trail, a framework and companion app for biometric registration of ISO/IEC 19794-2 fingerprint templates, enhanced performance features, better scalability for studies featuring millions of data form submissions, increased options for parallelization of research projects, and pipelines for automated management and analysis of data. We also developed novel encryption protocols for enhanced web-form security in Enketo.Results: Against the backdrop of a complex and challenging epidemic response, our enhanced platform of open tools was used to collect and manage data from more than 280,000 eligible study participants who received VSV-Zebov-GP under informed consent. These data were used to determine whether the VSV-Zebov-GP was safe and effective and to guide daily field operations.Conclusions: We present open-source developments that make electronic data management during clinical research and health emergencies more viable and robust. These developments will also enhance and expand the functionality of a diverse range of data collection platforms that are based on the ODK software and standards.

scholarly journals Implementing automated subject selection methodology in an epidemiological survey using open source application, Open Data Kit (ODK) (Preprint)

2018 ◽  
Author(s):  
Ganeshkumar Parasuraman ◽  
Sabarinathan Ramasamy ◽  
Chokkalingam D ◽  
Vinay Urs ◽  
Ritvik Amarchand ◽  
...  
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Open Source ◽  
Enterprise Architecture ◽  
Open Data ◽  
Application Framework ◽  
Selection Algorithm ◽  
Electronic Data Collection ◽  
Subject Selection ◽  
Open Data Kit

BACKGROUND Data collection in field-based public health research influences the quality and outcome of the research which in turn aids in developing evidence-based policymaking. As conventional data collection methods are either consume more time or more resources, usage of the cost-effective technology solution is required. Open Data Kit (ODK), the open-source application being designed for an Android-based platform is one such solution to electronic data collection. OBJECTIVE To demonstrate the functionality of ODK in implementing subject selection algorithm Kish methodology in epidemiological research studies METHODS Subject selection algorithms in field-based surveys are done manually and one such algorithm is Kish algorithm. Incorporating subject selection algorithm electronically in ODK application was not either tested or reported in the literature. We developed an application framework to build-in Kish grid algorithm in ODK application RESULTS The process and steps for setting up subject selection Kish algorithm to embed in ODK application are explained with syntax function. The application displayed the selected eligible adult on the screen after it runs the syntax function based on the Kish algorithm in the backend CONCLUSIONS ODK is an enterprise architecture, which is identified to develop a mobile application for a community based public health survey. The application would reduce the time taken for selecting and completing the interview of study participants. Ever a minor change like spell check on form mandates complete XML generation in ODK application and requires to update the existing entire application

scholarly journals Managing a Community Data Collection with Open Source Software

2020 ◽  
Author(s):  
Roland Schweitzer ◽  
Ethan Davis ◽  
Sean Arms ◽  
Robert Simons ◽  
Kevin O'Brien ◽  
...  
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Open Source Software ◽  
Community Data

Industry 4.0 Digital Technologies for data collection and control

2021 ◽  
pp. 43-58
Author(s):  
S. S. Yudachev ◽  
P. A. Monakhov ◽  
N. A. Gordienko
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Software Defined Radio ◽  
Block Diagram ◽  
Data Access ◽  
Gnu Radio ◽  
Time Data ◽  
Object A ◽  
Data Propagation ◽  
And Control

This article describes an attempt to create open source LabVIEW software, equivalent to data collection and control software. The proposed solution uses GNU Radio, OpenCV, Scilab, Xcos, and Comedi in Linux. GNU Radio provides a user-friendly graphical interface. Also, GNU Radio is a software-defined radio that conducts experiments in practice using software rather than the usual hardware implementation. Blocks for data propagation, code deletion with and without code tracking are created using the zero correlation zone code (ZCZ, a combination of ternary codes equal to 1, 0, and –1, which is specified in the program). Unlike MATLAB Simulink, GNU Radio is open source, i. e. free, and the concepts can be easily accessed by ordinary people without much programming experience using pre-written blocks. Calculations can be performed using OpenCV or Scilab and Xcos. Xcos is an application that is part of the Scilab mathematical modeling system, and it provides developers with the ability to design systems in the field of mechanics, hydraulics and electronics, as well as queuing systems. Xcos is a graphical interactive environment based on block modeling. The application is designed to solve problems of dynamic and situational modeling of systems, processes, devices, as well as testing and analyzing these systems. In this case, the modeled object (a system, device or process) is represented graphically by its functional parametric block diagram, which includes blocks of system elements and connections between them. The device drivers listed in Comedi are used for real-time data access. We also present an improved PyGTK-based graphical user interface for GNU Radio. English version of the article is available at URL: https://panor.ru/articles/industry-40-digital-technology-for-data-collection-and-management/65216.html

scholarly journals ImageJ and 3D Slicer: open source 2/3D morphometric software

2019 ◽  
Author(s):  
Fiona Pye ◽  
Nussaȉbah B Raja ◽  
Bryan Shirley ◽  
Ádám T Kocsis ◽  
Niklas Hohmann ◽  
...  
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Programming Languages ◽  
Quality Data ◽  
Software Projects ◽  
High Quality Data ◽  
3D Slicer ◽  
Data Collection And Analysis ◽  
Digital Methods ◽  
Imagej Plugin

In a world where an increasing number of resources are hidden behind paywalls and monthly subscriptions, it is becoming crucial for the scientific community to invest energy into freely available, community-maintained systems. Open-source software projects offer a solution, with freely available code which users can utilise and modify, under an open source licence. In addition to software accessibility and methodological repeatability, this also enables and encourages the development of new tools. As palaeontology moves towards data driven methodologies, it is becoming more important to acquire and provide high quality data through reproducible systematic procedures. Within the field of morphometrics, it is vital to adopt digital methods that help mitigate human bias from data collection. In addition,m mathematically founded approaches can reduce subjective decisions which plague classical data. This can be further developed through automation, which increases the efficiency of data collection and analysis. With these concepts in mind, we introduce two open-source shape analysis software, that arose from projects within the medical imaging field. These are ImageJ, an image processing program with batch processing features, and 3DSlicer which focuses on 3D informatics and visualisation. They are easily extensible using common programming languages, with 3DSlicer containing an internal python interactor, and ImageJ allowing the incorporation of several programming languages within its interface alongside its own simplified macro language. Additional features created by other users are readily available, on GitHub or through the software itself. In the examples presented, an ImageJ plugin “FossilJ” has been developed which provides semi-automated morphometric bivalve data collection. 3DSlicer is used with the extension SPHARM-PDM, applied to synchrotron scans of coniform conodonts for comparative morphometrics, for which small assistant tools have been created.

Sign in / Sign up

Export Citation Format

Share Document