Evidence map›Paper›PMID 30485260›Full record

ArticlePLoS biology2018

Building a local community of practice in scientific programming for life scientists.

Sarah L R Stevens, Mateusz Kuzak, Carlos Martinez, Aurelia Moser, Petra Bleeker, Marc Galland

Abstract read
In one paragraph

Article in PLoS biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Psychological Science in the Wake of COVID-19: Social, Methodological, and Metascientific Considerations.Perspectives on psychological science : a journal of the Association for Psychological Science · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sarah L R StevensDepartment of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Mateusz KuzakDutch Techcentre for Life Sciences, Utrecht, Netherlands.
Carlos MartinezNetherlands eScience Center, Amsterdam, Netherlands.
Aurelia MoserMozilla Foundation, Mountain View, California, United States of America.
Petra BleekerDepartment of Plant Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.
Marc GallandDepartment of Plant Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we describe why and how to build a local community of practice in scientific programming for life scientists who use computers and programming in their research. A community of practice is a small group of scientists who meet regularly to help each other and promote good practices in scientific programming. While most life scientists are well trained in the laboratory to conduct experiments, good practices with (big) data sets and their analysis are often missing. We propose a model on how to build such a community of practice at a local academic institution, present two real-life examples, and introduce challenges and implemented solutions. We believe that the current data deluge that life scientists face can benefit from the implementation of these small communities. Good practices spread among experimental scientists will foster open, transparent, and sound scientific results beneficial to society.

Indexed as

Big DataCommunity ParticipationData AnalysisData ScienceEducation, ProfessionalHumansModels, TheoreticalResearchResearch Design

Identifiers

PMID30485260
PMCPMC6287879

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.