ArticlePerspectives on science : historical, philosophical, social2014
Data Interpretation in the Digital Age.
Article in Perspectives on science : historical, philosophical, social, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- A roadmap to equity in pandemic preparedness, prevention and response.Journal of global health · 2024Article
- Digitising biopiracy? The global governance of plant genetic resources in the age of digital sequencing information.Third world quarterly · 2022Article
- The effect of preregistration on trust in empirical research findings: results of a registered report.Royal Society open science · 2020Article
- Data Work: Meaning-Making in the Era of Data-Rich Medicine.Journal of medical Internet research · 2019Article
- A Distributed Computing Platform for fMRI Big Data Analytics.IEEE transactions on big data · 2019Article
- The Future of Digital Sequence Information for Plant Genetic Resources for Food and Agriculture.Frontiers in plant science · 2019Article
- Article
- Exploring and visualizing multidimensional data in translational research platforms.Briefings in bioinformatics · 2017Article
- Big data, open science and the brain: lessons learned from genomics.Frontiers in human neuroscience · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
The consultation of internet databases and the related use of computer software to retrieve, visualise and model data have become key components of many areas of scientific research. This paper focuses on the relation of these developments to understanding the biology of organisms, and examines the conditions under which the evidential value of data posted online is assessed and interpreted by the researchers who access them, in ways that underpin and guide the use of those data to foster discovery. I consider the types of knowledge required to interpret data as evidence for claims about organisms, and in particular the relevance of knowledge acquired through physical interaction with actual organisms to assessing the evidential value of data found online. I conclude that familiarity with research
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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.