scholarly journals A Secure CDM-Based Data Analysis Platform (SCAP) in Multi-Centered Distributed Setting

2021 ◽  
Vol 11 (19) ◽  
pp. 9072
Author(s):  
Seungho Jeon ◽  
Chobyeol Shin ◽  
Eunnarae Ko ◽  
Jongsub Moon
Keyword(s):  
Data Analysis ◽  
Data Model ◽  
Web Application ◽  
Communication Protocols ◽  
Common Data Model ◽  
Web Based ◽  
Cryptographic Algorithm ◽  
Authentication Server ◽  
Analysis Platform ◽  
Analyze Data

Hospitals have their own database structures and maintain their data in a closed manner. For this reason, it is difficult for researchers outside of institutions to access multi-center data. Therefore, if the data maintained by all hospitals follow a commonly shared format, researchers can analyze multi-center data using the same method. To safely analyze data using a common data model (CDM) in a distributed multi-center network environment, the objective of this study is to propose and implement the processes for distribution, executing the analysis codes, and returning the results. A secure CDM-based data analysis platform (SCAP) consists of a certificate authority (CA), authentication server (AS), code signer (CS), ticket-granting server (TGS), relaying server (RS), and service server (SS). The AS, CS, TGS, and RS form the central server group of the platform. An SS is stored on a hospital server as an agent for communication with the server group. We designed the functionalities and communication protocols among servers. To safely conduct the intended functions, the proposed protocol was implemented based on a cryptographic algorithm. An SCAP was developed as a web application running on this protocol. Users accessed the platform through a web-based interface.

scholarly journals Using SWISH to Realize Interactive Web-based Tutorials for Logic-based Languages

2019 ◽  
Vol 19 (2) ◽  
pp. 229-261 ◽  
Author(s):  
JAN WIELEMAKER ◽  
FABRIZIO RIGUZZI ◽  
ROBERT A. KOWALSKI ◽  
TORBJÖRN LAGER ◽  
FARIBA SADRI ◽  
...  
Keyword(s):  
Data Analysis ◽  
User Interfaces ◽  
Web Application ◽  
Web Server ◽  
Educational Material ◽  
Graphical User Interfaces ◽  
Probabilistic Logic ◽  
Programming Environments ◽  
Web Based ◽  
Front End

AbstractProgramming environments have evolved from purely text based to using graphical user interfaces, and now we see a move toward web-based interfaces, such as Jupyter. Web-based interfaces allow for the creation of interactive documents that consist of text and programs, as well as their output. The output can be rendered using web technology as, for example, text, tables, charts, or graphs. This approach is particularly suitable for capturing data analysis workflows and creating interactive educational material. This article describes SWISH, a web front-end for Prolog that consists of a web server implemented in SWI-Prolog and a client web application written in JavaScript. SWISH provides a web server where multiple users can manipulate and run the same material, and it can be adapted to support Prolog extensions. In this article we describe the architecture of SWISH, and describe two case studies of extensions of Prolog, namely Probabilistic Logic Programming and Logic Production System, which have used SWISH to provide tutorial sites.

scholarly journals MetaR: simple, high-level languages for data analysis with the R ecosystem

2015 ◽  
Author(s):  
Fabien Campagne ◽  
William ER Digan ◽  
Manuele Simi
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Language Design ◽  
Intelligent Data Analysis ◽  
Analysis Tools ◽  
High Level ◽  
Analysis Platform ◽  
Analyze Data

Data analysis tools have become essential to the study of biology. Tools available today were constructed with layers of technology developed over decades. Here, we explain how some of the principles used to develop this technology are sub-optimal for the construction of data analysis tools for biologists. In contrast, we applied language workbench technology (LWT) to create a data analysis language, called MetaR, tailored for biologists with no programming experience, as well as expert bioinformaticians and statisticians. A key novelty of this approach is its ability to blend user interface with scripting in such a way that beginners and experts alike can analyze data productively in the same analysis platform. While presenting MetaR, we explain how a judicious use of LWT eliminates problems that have historically contributed to data analysis bottlenecks. These results show that language design with LWT can be a compelling approach for developing intelligent data analysis tools.

scholarly journals Extract, Transform, Load Framework for the Conversion of Health Databases to OMOP

2021 ◽  
Author(s):  
Juan C. Quiroz ◽  
Tim Chard ◽  
Zhisheng Sa ◽  
Angus Ritchie ◽  
Louisa Jorm ◽  
...  
Keyword(s):  
Data Model ◽  
Web Application ◽  
Research Community ◽  
Common Data Model ◽  
Medical Outcomes ◽  
Data Manipulation ◽  
Community Needs ◽  
Mapping Process ◽  
The Cost ◽  
Manipulation Language

ABSTRACTObjectiveDevelop an extract, transform, load (ETL) framework for the conversion of health databases to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) that supports transparency of the mapping process, readability, refactoring, and maintainability.Materials and MethodsWe propose an ETL framework that is metadata-driven and generic across source datasets. The ETL framework reads mapping logic for OMOP tables from YAML files, which organize SQL snippets in key-value pairs that define the extract and transform logic to populate OMOP columns.ResultsWe developed a data manipulation language (DML) for writing the mapping logic from health datasets to OMOP, which defines mapping operations on a column-by-column basis. A core ETL pipeline converts the DML in YAML files and generates an ETL script. We provide access to our ETL framework via a web application, allowing users to upload and edit YAML files and obtain an ETL SQL script that can be used in development environments.DiscussionThe structure of the DML and the mapping operations defined in column-by-column operations maximizes readability, refactoring, and maintainability, while minimizing technical debt, and standardizes the writing of ETL operations for mapping to OMOP. Our web application allows institutions and teams to reuse the ETL pipeline by writing their own rules using our DML.ConclusionThe research community needs tools that reduce the cost and time effort needed to map datasets to OMOP. These tools must support transparency of the mapping process for mapping efforts to be reused by different institutions.

scholarly journals Perancangan Aplikasi Web Penyewaan Lapangan Futsal (Studi Kasus :Sumber Jaya Futsal Tangerang)

2020 ◽  
Vol 8 (1) ◽  
pp. 31-35
Author(s):  
Ika Yuniva ◽  
Andriansah Andriansah ◽  
Yoga Nur Ikhsan
Keyword(s):  
Programming Language ◽  
Data Model ◽  
Web Application ◽  
Web Based ◽  
Development Method ◽  
Transaction Scheduling ◽  
Report System ◽  
Entity Relationship ◽  
Entity Relationship Diagram ◽  
Web Based System

Futsal sports have developed and are popular in Indonesia. Sumber Jaya Futsal is one of the providers of futsal field rental business in Tangerang. Sumber Jaya Futsal currently does not have a web-based system, the system for leasing futsal fields in Sumber Jaya Futsal is still conventional, where customers come directly or by calling to find out the schedule of available futsal fields. The rental transaction scheduling and report system is still using a notebook. Based on the problem, the purpose of this research is to produce a draft web application for futsal field rental at Sumber Jaya Futsal Tangerang. In this study to collect data the author uses case studies with methods of observation and literature. The design of this web application is made using the PHP programming language, assisted by xampp as a web server, MySQL for database management, ERD (Entity Relationship Diagram) and LRS (Logical Record Structure) to describe the data model. While the author's software development method uses the Waterfall Method.

scholarly journals A New Web-Based Tool for RTO-Focused Animal Shelter Data Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Tom Kremer
Keyword(s):  
Data Analysis ◽  
Web Application ◽  
Hold Time ◽  
Similar Data ◽  
Web Based ◽  
Animal Shelters ◽  
The Relationship ◽  
The City ◽  
Large Adult

Animal shelters are increasingly interested in reducing their intake and helping their communities keep and care for animals. Improving Return-to-Owner (RTO) rates of stray dogs is one path to save significant shelter space, time, and costs and keep animals with their caregivers and communities. Aggregating and visualizing RTO data spatially are useful for identifying trends and highlighting areas for potential interventions. Since shelters collect similar data, an interactive web application was developed to make such an analysis easily reproducible. This paper presents the tool's capabilities via a case study of 2019 data from the Dallas Animal Services shelter, covering the relationship between stray intake and RTO rate, the distances traveled from home by RTOed strays, microchip use across the city and its relationship with RTO rate, and the length of stay of RTOs and other outcome groups. Findings include showing that 70% of RTOed strays traveled at most 1 mile away from home and 42% up to block away, and that at-large, adult strays that had a microchip had a 71% RTO rate compared with 39% without one. The results affected the shelter's hold time for strays, highlighted target areas for microchip programs, and motivated neighborhood-based methods to locate found dogs' owners. Shelters are welcome to use the tool and participate in the development of new analytical lenses and visualizations that would best suit their needs.

scholarly journals MetaR: simple, high-level languages for data analysis with the R ecosystem

2015 ◽  
Author(s):  
Fabien Campagne ◽  
William ER Digan ◽  
Manuele Simi
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Language Design ◽  
Intelligent Data Analysis ◽  
Analysis Tools ◽  
High Level ◽  
Analysis Platform ◽  
Analyze Data

Data analysis tools have become essential to the study of biology. Tools available today were constructed with layers of technology developed over decades. Here, we explain how some of the principles used to develop this technology are sub-optimal for the construction of data analysis tools for biologists. In contrast, we applied language workbench technology (LWT) to create a data analysis language, called MetaR, tailored for biologists with no programming experience, as well as expert bioinformaticians and statisticians. A key novelty of this approach is its ability to blend user interface with scripting in such a way that beginners and experts alike can analyze data productively in the same analysis platform. While presenting MetaR, we explain how a judicious use of LWT eliminates problems that have historically contributed to data analysis bottlenecks. These results show that language design with LWT can be a compelling approach for developing intelligent data analysis tools.

scholarly journals CITYJSON + WEB = NINJA

2020 ◽  
Vol VI-4/W1-2020 ◽  
pp. 167-173
Author(s):  
S. Vitalis ◽  
A. Labetski ◽  
F. Boersma ◽  
F. Dahle ◽  
X. Li ◽  
...  
Keyword(s):  
Data Model ◽  
Web Application ◽  
Web Applications ◽  
Decision Makers ◽  
Web Browser ◽  
Web Based ◽  
Technical Aspects ◽  
Web Technologies ◽  
3D City Models ◽  
City Models

Abstract. As web applications become more popular, 3D city models would greatly benefit from a proper web-based solution to visualise and manage them. CityJSON was introduced as a JSON encoding of the CityGML data model and promises, among several benefits, the ability to be integrated with modern web technologies. In order to provide an implementation of a web application for CityJSON data, that can be used as a reference for other applications, we developed ninja. It is a web application that allows the user to easily load and investigate a CityJSON model through a web browser. In addition, it offers support for a complex feature of CityJSON: the experimental versioning mechanism. In this paper, we describe the motivation, requirements, technical aspects and achieved functionality of ninja. We believe that such a web application can facilitate the adoption of 3D city models by more practitioners and decision makers.

scholarly journals ProVision: a web-based platform for rapid analysis of proteomics data processed by MaxQuant

2020 ◽  
Vol 36 (19) ◽  
pp. 4965-4967
Author(s):  
James Luke Gallant ◽  
Tiaan Heunis ◽  
Samantha Leigh Sampson ◽  
Wilbert Bitter
Keyword(s):  
Data Analysis ◽  
Web Application ◽  
Label Free ◽  
Proteomics Data ◽  
Web Based ◽  
Protein Protein Interaction ◽  
Tandem Mass Tag ◽  
Protein Interaction Prediction ◽  
Core Facilities ◽  
User Friendly

Abstract Summary Proteomics is a powerful tool for protein expression analysis and is becoming more readily available to researchers through core facilities or specialized collaborations. However, one major bottleneck for routine implementation and accessibility of this technology to the wider scientific community is the complexity of data analysis. To this end, we have created ProVision, a free open-source web-based analytics platform that allows users to analyze data from two common proteomics relative quantification workflows, namely label-free and tandem mass tag-based experiments. Furthermore, ProVision allows the freedom to interface with the data analysis pipeline while maintaining a user-friendly environment and providing default parameters for fast statistical and exploratory data analysis. Finally, multiple customizable quality control, differential expression plots as well as enrichments and protein–protein interaction prediction can be generated online in one platform. Availability and implementation Quick start and step-by-step tutorials as well as tutorial data are fully incorporated in the web application. This application is available online at https://provision.shinyapps.io/provision/ for free use. The source code is available at https://github.com/JamesGallant/ProVision under the GPL version 3.0 license.

scholarly journals MetaR: simple, high-level languages for data analysis with the R ecosystem

2015 ◽  
Author(s):  
Fabien Campagne ◽  
William ER Digan ◽  
Manuele Simi
Keyword(s):  
Data Analysis ◽  
User Interface ◽  
Language Design ◽  
Intelligent Data Analysis ◽  
Analysis Tools ◽  
High Level ◽  
Analysis Platform ◽  
Analyze Data

Data analysis tools have become essential to the study of biology. Tools available today were constructed with layers of technology developed over decades. Here, we explain how some of the principles used to develop this technology are sub-optimal for the construction of data analysis tools for biologists. In contrast, we applied language workbench technology (LWT) to create a data analysis language, called MetaR, tailored for biologists with no programming experience, as well as expert bioinformaticians and statisticians. A key novelty of this approach is its ability to blend user interface with scripting in such a way that beginners and experts alike can analyze data productively in the same analysis platform. While presenting MetaR, we explain how a judicious use of LWT eliminates problems that have historically contributed to data analysis bottlenecks. These results show that language design with LWT can be a compelling approach for developing intelligent data analysis tools.

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