Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

503
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
503
Cross-Sectional Research01:50

Cross-Sectional Research

12.1K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
12.1K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

189
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
189
Centroid of a Body: Problem Solving01:03

Centroid of a Body: Problem Solving

1.5K
The centroid of a body is a crucial concept in engineering and physics. Finding the centroid of a body can help determine its stability, its balance point, and even its design. In this context, consider a thin wire bent in the form of a quarter circular arc. Polar coordinates are used to calculate the centroid. The wire is first divided into small differential elements of a length equal to the radius multiplied by the differential angle.
The x-coordinates and y-coordinates of each element's...
1.5K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

118
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
118
Population Growth00:57

Population Growth

26.3K
Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
26.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Search for Wives.

Hall's journal of health·2022
Same author

Data Resource: population level family justice administrative data with opportunities for data linkage.

International journal of population data science·2021
Same author

A Profile of the SAIL Databank on the UK Secure Research Platform.

International journal of population data science·2021
Same author

Surprising impact of stromal TIL's on immunotherapy efficacy in a real-world lung cancer study.

Lung cancer (Amsterdam, Netherlands)·2021
Same author

Maternal health, pregnancy and birth outcomes for women involved in care proceedings in Wales: a linked data study.

BMC pregnancy and childbirth·2020
Same author

Why the Public Need a Say in How Patient Data are Used for Covid-19 Responses.

International journal of population data science·2020

Related Experiment Video

Updated: Nov 2, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.5K

Exploring barriers and solutions in advancing cross-centre population data science.

K H Jones1, S M Heys1, H Daniels1

  • 1Population Data Science, Swansea University Medical School, Singleton Park, Swansea SA2 8PP.

International Journal of Population Data Science
|June 7, 2021
PubMed
Summary

Cross-centre working enhances research by linking health and administrative data. Success requires dedicated resources, collaboration, and cultural change for effective data sharing across centers.

More Related Videos

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.6K
Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

Published on: May 9, 2017

9.4K

Related Experiment Videos

Last Updated: Nov 2, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.5K
ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.6K
Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

Published on: May 9, 2017

9.4K

Area of Science:

  • Health Informatics
  • Data Science
  • Population Health Research

Background:

  • Population health and administrative data are valuable for research, especially when linked.
  • Cross-centre working can expand data availability for research purposes.
  • Limited information exists on addressing challenges and ensuring success in cross-centre data initiatives.

Purpose of the Study:

  • To explore perceived barriers and solutions for cross-centre working.
  • To inform the development of effective cross-centre data collaborations.
  • To identify key factors for successful data sharing between research centers.

Main Methods:

  • A narrative literature review on data sharing and cross-centre working.
  • Mixed methods approach including public opinion assessment on cross-centre data sharing.
  • Gathering views and experiences from data centre staff within the UK Farr Institute for Health Informatics Research.

Main Results:

  • Literature review identified practical and cultural challenges in cross-centre working.
  • Public engagement indicated acceptance of anonymised data sharing between centres.
  • Data centre staff highlighted the need for dedicated resourcing, addressing practical issues, information governance, and cultural considerations.

Conclusions:

  • Advancing cross-centre working necessitates dedicated resourcing and indicators for data reuse.
  • Collaboration is crucial for resolving common issues in data sharing.
  • Balancing barrier removal with incentivisation and fostering an academic culture change are essential for progress.