ArticleThe Journal of animal ecology2021
Four key challenges in the open-data revolution.
Article in The Journal of animal ecology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Integrating animal tracking and trait data to facilitate global ecological discoveries.The Journal of experimental biology · 2025Article
- Article
- Advancing Maternal Transfer of Organic Pollutants across Reptiles for Conservation and Risk Assessment Purposes.Environmental science & technology · 2024Article
- A General Primer for Data Harmonization.Scientific data · 2024Article
- Islands of data: cultivating an open data landscape for sustainable development in the Caribbean.Revista panamericana de salud publica = Pan American journal of public health · 2024Article
- MOSAIC - A Unified Trait Database to Complement Structured Population Models.Scientific data · 2023Article
- Four key challenges in the open-data revolution.The Journal of animal ecology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
In Focus: Culina, A., Adriaensen, F., Bailey, L. D., et al. (2021) Connecting the data landscape of long-term ecological studies: The SPI-Birds data hub. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13388. Long-term, individual-based datasets have been at the core of many key discoveries in ecology, and calls for the collection, curation and release of these kinds of ecological data are contributing to a flourishing open-data revolution in ecology. Birds, in particular, have been the focus of international research for decades, resulting in a number of uniquely long-term studies, but accessing these datasets has been historically challenging. Culina et al. (2021) introduce an online repository of individual-level, long-term bird records with ancillary data (e.g. genetics), which will enable key ecological questions to be answered on a global scale. As well as these opportunities, however, we argue that the ongoing open-data revolution comes with four key challenges relating to the (1) harmonisation of, (2) biases in, (3) expertise in and (4) communication of, open ecological data. Here, we discuss these challenges and how key efforts such as those by Culina et al. are using FAIR (Findable, Accessible, Interoperable and Reproducible) principles to overcome them. The open-data revolution will undoubtedly reshape our understanding of ecology, but with it the ecological community has a responsibility to ensure this revolution is ethical and effective.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.