ArticlePeerJ. Computer science2022
The role of software in science: a knowledge graph-based analysis of software mentions in PubMed Central.
Article in PeerJ. Computer science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Quantifying the impact of biobanks and cohort studies.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- FAIRsoft-a practical implementation of FAIR principles for research software.Bioinformatics (Oxford, England) · 2024Article
- [FAIR health data in the national and international data space].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024Article
- Special issue on software citation, indexing, and discoverability.PeerJ. Computer science · 2024Article
- detectCilia: An R Package for Automated Detection and Length Measurement of Primary Cilia.Bioinformatics and biology insights · 2024Article
- Article
- A data-centric way to improve entity linking in knowledge-based question answering.PeerJ. Computer science · 2023Article
- Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities.Journal of big data · 2023Article
- Understanding progress in software citation: a study of software citation in the CORD-19 corpus.PeerJ. Computer science · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Science across all disciplines has become increasingly data-driven, leading to additional needs with respect to software for collecting, processing and analysing data. Thus, transparency about software used as part of the scientific process is crucial to understand provenance of individual research data and insights, is a prerequisite for reproducibility and can enable macro-analysis of the evolution of scientific methods over time. However, missing rigor in software citation practices renders the automated detection and disambiguation of software mentions a challenging problem. In this work, we provide a large-scale analysis of software usage and citation practices facilitated through an unprecedented knowledge graph of software mentions and affiliated metadata generated through supervised information extraction models trained on a unique gold standard
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.