International Journal of Population Data Science

SJR Rank #12,790H-index: 25SJR: 0.460Best quartile: Q2Open AccessAPC: US$1,747Listed in DOAJ
Journal website: aims, scope and author guidelines
Publisher

Swansea University

Country

United Kingdom

Type

journal

SJR by Edition

2022202500.250.50.751

Subject Categories

  • DemographyQ2
  • Information SystemsQ2
  • Information Systems and ManagementQ2
  • Health InformaticsQ3

Areas: Computer Science · Decision Sciences · Medicine · Social Sciences

Most published research topics

Data Quality and ManagementHealth disparities and outcomesChronic Disease Management Strategiesdemographic modeling and climate adaptationPrimary Care and Health OutcomesMedical Coding and Health InformationHealth, Environment, Cognitive AgingEthics in Clinical ResearchData Analysis and ArchivingResearch Data Management Practices

Source: OpenAlex

Publication Statistics

2025 Docs3-Year DocsCitable Docs060120180240

Documents per Year

20222025015304560

Detailed Information

ISSN

2399-4908

SJR Best Quartile

Q2

Region

Western Europe

Citations per Document (2 years)

0.93

References per Document

29.37

Coverage

2017-2026

Scope

The International Journal of Population Data Science (IJPDS) is an electronic, open‑access, peer-reviewed journal focussing on the science pertaining to population data. It publishes articles on all aspects of research, development and evaluation connected with data about people and populations. These include: technological advances in data storage and management; architectures and infrastructures; legal and regulatory issues; ethical, legal and societal implications (ELSI); privacy-protection methodologies; data and linkage quality; analytical advances; accessing distributed data; linking to emerging/complex data types; using big data; outcomes-based research; epidemiology; service evaluations; public involvement and engagement; capacity building; and delivering and measuring impact. The creation of the IJPDS was inspired by the International Population Data Linkage Network (IPDLN). The journal has a regular section for topics of particular interest to the IPDLN sub-edited by the Director(s) of the network.

Metrics from SCImago Journal Rank 2025. View on SCImago