scholarly journals OPEN DATA IN HEALTH-GEOMATICS: MAPPING AND EVALUATING PUBLICLY ACCESSIBLE DEFIBRILLATORS

2019 ◽  
Vol XLII-4/W14 ◽  
pp. 63-70
Author(s):  
L. Gianquintieri ◽  
E. G. Caiani ◽  
P. Brambilla ◽  
A. Pagliosa ◽  
G. F. Villa ◽  
...  
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Open Data ◽  
Correlation Coefficients ◽  
Walking Distance ◽  
Mapping Technique ◽  
Limited Area ◽  
Automated External Defibrillators ◽  
Spatial Coverage

<p><strong>Abstract.</strong> To address the study of the deployment of publicly accessible Automated External Defibrillators (AED), Geomatics allows computing their limited area of effectiveness (i.e. ‘catchment area’, CA), traditionally set as circular surfaces with a 100m-radius. Exploiting open geospatial data related to roads network, also ‘realistic’ CAs, based on the effective walking distance, can be computed. Aim of this study (performed on the territory of Lombardy, Italy, total surface 23,863.65 km<sup>2</sup>, with open source software as QGIS, PostGIS, pgRouting) was to compare the two approaches, and to evaluate if the territory analysis could support case-by-case decision-making about the preferable mapping technique.</p><p>Setting a limit of 200&amp;thinsp;m, realistic CAs were computed for 7702 known AEDs on the territory (at 28/02/2018). The mean area obtained resulted close to that of the traditional 100m-radius circular area (33,665m<sup>2</sup> against 31,415m<sup>2</sup>), but the spatial coverage of 45043 OHCAs - Out-of-Hospital Cardiac Arrests (Lombardy, 1/1/2015 to 31/12/2018) is very different considering realistic or circular areas (15.35% vs 9.43%). The distribution of the mapping error (realistic-CA – circular-CA) and the computation failures of realistic areas were studied and correlated with the characteristics of the surrounding territory considering attributes related to streets, buildings, and land-use, computing linear correlation coefficients and performing Mann-Whitney U-tests. Results suggest that realistic CAs are not always correctly computable and circular areas are preferable when AEDs are far from the streets in less urbanized and more uniform territories. An automatized decision-making about the best case-by-case mapping technique is therefore feasible with open data and open source software.</p>

scholarly journals Using Open Source, Open Data, and Civic Technology to Address the COVID-19 Pandemic and Infodemic

2021 ◽  
Author(s):  
Shinji Kobayashi ◽  
Luis Falcón ◽  
Hamish Fraser ◽  
Jørn Braa ◽  
Pamod Amarakoon ◽  
...  
Keyword(s):  
Open Source ◽  
Medical Informatics ◽  
Open Source Software ◽  
Collective Intelligence ◽  
Collaborative Work ◽  
Open Data ◽  
Theme Issue ◽  
Health Organizations ◽  
The World ◽  
Civic Technology

Objectives: The emerging COVID-19 pandemic has caused one of the world’s worst health disasters compounded by social confusion with misinformation, the so-called “Infodemic”. In this paper, we discuss how open technology approaches - including data sharing, visualization, and tooling - can address the COVID-19 pandemic and infodemic. Methods: In response to the call for participation in the 2020 International Medical Informatics Association (IMIA) Yearbook theme issue on Medical Informatics and the Pandemic, the IMIA Open Source Working Group surveyed recent works related to the use of Free/Libre/Open Source Software (FLOSS) for this pandemic. Results: FLOSS health care projects including GNU Health, OpenMRS, DHIS2, and others, have responded from the early phase of this pandemic. Data related to COVID-19 have been published from health organizations all over the world. Civic Technology, and the collaborative work of FLOSS and open data groups were considered to support collective intelligence on approaches to managing the pandemic. Conclusion: FLOSS and open data have been effectively used to contribute to managing the COVID-19 pandemic, and open approaches to collaboration can improve trust in data.

scholarly journals CREGIS-Q: a GIS tool to support decision making in case of aquifer contamination emergency

2016 ◽  
Author(s):  
Anna Bruna Petrangeli ◽  
Elisabetta Preziosi ◽  
Francesco Campopiano ◽  
Angelo Corazza ◽  
Andrea Duro
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Open Source ◽  
Open Source Software ◽  
Aquifer Contamination ◽  
Gis Technology ◽  
Structure Programming ◽  
Spatial Decision Making ◽  
Environmental Risk Analysis ◽  
Support Decision Making

GIS technology has been used for many years in environmental risk analysis due to its capability to focus on the management and analysis of geographic and alphanumeric data to support spatial decision-making (Vairavamoorthy et al, 2007). Especially in emergency management, a DSS (Decision Support System) constitutes an important task to provide quick responses, though not completely exhaustive, to immediately handle a critical scenario and limit the possible damage. In the framework of a collaboration between the Water Research Institute and the National Civil Protection Department, a customized tool called CREGIS (ContaminazioneRisorseEvento-GIS) has been developed in order to facilitate the emergency management of accidental contamination of aquifers and support decision making (Preziosi et al, 2013). The tool is aimed at both national and local authorities in order to improve response capability for a better emergency management. Originally, the tool has been developed programming Python in an ArcGIS environment; but due to the great development and dissemination of open source software, our aim is to replicate the same structure programming Python in a GIS open source environment (QGIS). The review of the tool's code is still in progress. The goal is to make the tool (now named CREGIS-Q) free and accessible to a greater number of people and stakeholders.

scholarly journals CREGIS-Q: a GIS tool to support decision making in case of aquifer contamination emergency

2016 ◽  
Author(s):  
Anna Bruna Petrangeli ◽  
Elisabetta Preziosi ◽  
Francesco Campopiano ◽  
Angelo Corazza ◽  
Andrea Duro
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Open Source ◽  
Open Source Software ◽  
Aquifer Contamination ◽  
Gis Technology ◽  
Structure Programming ◽  
Spatial Decision Making ◽  
Environmental Risk Analysis ◽  
Support Decision Making

GIS technology has been used for many years in environmental risk analysis due to its capability to focus on the management and analysis of geographic and alphanumeric data to support spatial decision-making [Vairavamoorthy et al, 2007]. Especially in emergency management, a DSS (Decision Support System) constitutes an important task to provide quick responses, though not completely exhaustive, to immediately handle a critical scenario and limit the possible damage. In the framework of a collaboration between the Water Research Institute and the National Civil Protection Department, a customized tool called CREGIS (ContaminazioneRisorseEvento-GIS) has been developed in order to facilitate the emergency management of accidental contamination of aquifers and support decision making [Preziosi et al, 2013]. The tool is aimed at both national and local authorities in order to improve response capability for a better emergency management. Originally, the tool has been developed programming Python in an ArcGIS environment; but due to the great development and dissemination of open source software, our aim is to replicate the same structure programming Python in a GIS open source environment (QGIS). The review of the tool's code is still in progress. The goal is to make the tool (now named CREGIS-Q) free and accessible to a greater number of people and stakeholders.

Conquery: an Open Source Application to analyze High Content Healthcare Data (Preprint)

2021 ◽  
Author(s):  
Fabian Kovacs ◽  
Max Thonagel ◽  
Marion Ludwig ◽  
Alexander Albrecht ◽  
Manuel Hegner ◽  
...  
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Medical Records ◽  
Healthcare Sector ◽  
Study Cohort ◽  
Decision Making Processes ◽  
Analytical Approaches

BACKGROUND Big data in healthcare must be exploited to achieve a substantial increase in efficiency and competitiveness. Especially the analysis of patient-related data possesses huge potential to improve decision-making processes. However, most analytical approaches used today are highly time- and resource-consuming. OBJECTIVE The presented software solution Conquery is an open-source software tool providing advanced, but intuitive data analysis without the need for specialized statistical training. Conquery aims to simplify big data analysis for novice database users in the medical sector. METHODS Conquery is a document-oriented distributed timeseries database and analysis platform. Its main application is the analysis of per-person medical records by non-technical medical professionals. Complex analyses are realized in the Conquery frontend by dragging tree nodes into the query editor. Queries are evaluated by a bespoke distributed query-engine for medical records in a column-oriented fashion. We present a custom compression scheme to facilitate low response times that uses online calculated as well as precomputed metadata and data statistics. RESULTS Conquery allows for easy navigation through the hierarchy and enables complex study cohort construction whilst reducing the demand on time and resources. The UI of Conquery and a query output is exemplified by the construction of a relevant clinical cohort. CONCLUSIONS Conquery is an efficient and intuitive open-source software for performant and secure data analysis and aims at supporting decision-making processes in the healthcare sector.

Model to Estimate the Human Factor Quality in FLOSS Development

2015 ◽  
pp. 219-236
Author(s):  
Zulaima Chiquin ◽  
Kenyer Domínguez ◽  
Luis E. Mendoza ◽  
Edumilis Méndez
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Open Source ◽  
Open Source Software ◽  
Human Factor ◽  
Three Dimensions ◽  
Decision Making Process ◽  
Self Evaluation ◽  
Systemic Quality

This chapter presents a Model to Estimate the Human Factor Quality in Free/Libre Open Source Software (FLOSS) Development, or EHFQ-FLOSS. The model consists of three dimensions: Levels (individual, community, and foundation), Aspects (internal or contextual), and Forms of Evaluation (self-evaluation, co-evaluation, and hetero-evaluation). Furthermore, this model provides 145 metrics applicable to all three levels, as well as an algorithm that guides their proper application to estimate the systemic quality of human resources involved in the development of FLOSS, guide the decision-making process, and take possible corrective actions.

scholarly journals Canadian Public Libraries and their Interest in Open Source Software (OSS)

2018 ◽  
Author(s):  
Dinesh Rathi
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Public Libraries ◽  
Evaluation Criteria ◽  
Prise De Décision ◽  
Use Of Resources ◽  
Insight Into

This study presents findings of research conducted in the Open Source Software (OSS) domain in a Canadian public libraries context. The findings from the survey will provide insight into various facets such as use, benefits and challenges of OSS from Canadian libraries’ perspective, OSS evaluation criteria, use of resources to learn about OSS, and decision-making associated with OSS in Canadian libraries context.Cette étude présente les résultats de recherches menées dans le domaine des logiciels libres (Open Source Software - OSS) dans le contexte des bibliothèques publiques canadiennes. Les résultats du sondage fourniront un aperçu de diverses facettes telles que l'utilisation, les avantages et les défis des logiciels libres, du point de vue des bibliothèques canadiennes, des critères d'évaluation des logiciels libres, de l'utilisation des ressources pour en apprendre davantage sur les logiciels libres, et la prise de décision associée aux logiciels libres dans le contexte des bibliothèques canadiennes.

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