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Related Experiment Video

Updated: Nov 9, 2025

Resurrection of Dormant Daphnia magna: Protocol and Applications

Resurrection of Dormant Daphnia magna: Protocol and Applications

Published on: January 19, 2018

Data Freshness in Ecology and Conservation.

Nicholas J Murray¹, Emma V Kennedy², Jorge G Álvarez-Romero³

¹College of Science and Engineering, James Cook University, Townsville, Queensland 4811, Australia.

Trends in Ecology & Evolution

|April 17, 2021

Summary

This summary is machine-generated.

Environmental data is increasingly used, but its age, known as data freshness, is often not reported. This missing information can increase uncertainty in research findings.

Keywords:

data reporting environmental modeling open-access data replication reproducibility

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Area of Science:

Environmental science
Data science
Information quality

Background:

Advancements in environmental data collection, sharing, and processing facilitate diverse data utilization.
Data freshness, a critical quality dimension, is frequently underreported in environmental research.
Inadequate reporting of data age introduces uncertainty into research outcomes.

Purpose of the Study:

To highlight the importance of data freshness in environmental research.
To underscore the need for improved reporting standards for data age.
To address the impact of data freshness on research uncertainty.

Main Methods:

Literature review on data quality dimensions.
Analysis of reporting practices for data freshness in environmental studies.
Assessment of the impact of data age on research findings.

Main Results:

Data freshness is a poorly documented aspect of environmental data quality.
Lack of data freshness information contributes to uncertainty in scientific findings.
Standardized reporting of data age is not consistently implemented.

Conclusions:

Emphasize the critical role of data freshness in ensuring the reliability of environmental research.
Advocate for the integration of data freshness reporting into data quality frameworks.
Promote best practices for documenting and communicating data age to mitigate research uncertainty.