A Generic Method and Implementation to Evaluate and Improve Data Quality in Distributed Research Networks

D Juárez1,2, E E Schmidt1,2, S Stahl-Toyota3

  • 1Federated Information Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Abstract

Related Concept Videos

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time06:05

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time

This protocol describes a novel method for collecting and analyzing data related to ongoing implementation called the Participant-Reported Implementation Update and Score (PRIUS). The PRIUS method allows for the efficient and systematic capture of data over time and from multiple viewpoints in healthcare settings.
1.6K
Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling07:18

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

A method for transcriptome profiling of cereals is presented. The microarray-based gene expression profiling starts with the isolation of high-quality total RNA from cereal grains and continues with the generation of cDNA. After cRNA labelling and microarray hybridization, recommendations are given for signal detection and quality...
7.9K
CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

We present CorrelationCalculator and Filigree, two tools for data-driven network construction and analysis of metabolomics data. CorrelationCalculator supports building a single interaction network of metabolites based on expression data, while Filigree allows building a differential network, followed by network clustering and enrichment analysis.
3.3K
Data: Types and Distribution01:19

Data: Types and Distribution

In biostatistics, data are the observations collected for analysis. There are two main types: parametric and non-parametric. Parametric data, which include continuous (e.g., weight) and discrete numerical data (e.g., number of tablets), assume a particular distribution pattern, often the normal distribution. Non-parametric data do not adhere to a specific distribution and typically comprise nominal (e.g., gender) and ordinal categorical data (e.g., pain scale ratings).
Distributions in...
1.5K
Turbulence Sphere Method: Evaluating Wind Tunnel Flow Quality09:23

Turbulence Sphere Method: Evaluating Wind Tunnel Flow Quality

Source: Jose Roberto Moreto and Xiaofeng Liu, Department of Aerospace Engineering, San Diego State University, San Diego, CA
Wind tunnel tests are useful in the design of vehicles and structures that are subjected to airflow during their use. Wind tunnel data are generated by applying a controlled air flow to a model of the object being studied. The test model usually has a similar geometry but is a smaller scale compared to the full-sized object. To ensure accurate and useful data is collected...
9.2K
Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology06:24

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

This manuscript describes a generic approach for tailor-made design of microbial cultivation media. This is enabled by an iterative workflow combining Kriging-based experimental design and microbioreactor technology for sufficient cultivation throughput, which is supported by lab robotics to increase reliability and speed in liquid handling media...
10.6K