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Electronic lab notebooks: can they replace paper?

Overview of attention for article published in Journal of Cheminformatics, May 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#4 of 958)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
6 news outlets
blogs
2 blogs
policy
1 policy source
twitter
42 X users
facebook
1 Facebook page
wikipedia
3 Wikipedia pages
googleplus
1 Google+ user

Citations

dimensions_citation
53 Dimensions

Readers on

mendeley
231 Mendeley
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Title
Electronic lab notebooks: can they replace paper?
Published in
Journal of Cheminformatics, May 2017
DOI 10.1186/s13321-017-0221-3
Pubmed ID
Authors

Samantha Kanza, Cerys Willoughby, Nicholas Gibbins, Richard Whitby, Jeremy Graham Frey, Jana Erjavec, Klemen Zupančič, Matjaž Hren, Katarina Kovač

Abstract

Despite the increasingly digital nature of society there are some areas of research that remain firmly rooted in the past; in this case the laboratory notebook, the last remaining paper component of an experiment. Countless electronic laboratory notebooks (ELNs) have been created in an attempt to digitise record keeping processes in the lab, but none of them have become a 'key player' in the ELN market, due to the many adoption barriers that have been identified in previous research and further explored in the user studies presented here. The main issues identified are the cost of the current available ELNs, their ease of use (or lack of it) and their accessibility issues across different devices and operating systems. Evidence suggests that whilst scientists willingly make use of generic notebooking software, spreadsheets and other general office and scientific tools to aid their work, current ELNs are lacking in the required functionality to meet the needs of the researchers. In this paper we present our extensive research and user study results to propose an ELN built upon a pre-existing cloud notebook platform that makes use of accessible popular scientific software and semantic web technologies to help overcome the identified barriers to adoption.

X Demographics

X Demographics

The data shown below were collected from the profiles of 42 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 231 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 230 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 47 20%
Student > Bachelor 31 13%
Student > Ph. D. Student 24 10%
Student > Master 20 9%
Librarian 12 5%
Other 43 19%
Unknown 54 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 36 16%
Agricultural and Biological Sciences 24 10%
Computer Science 24 10%
Chemistry 23 10%
Engineering 11 5%
Other 48 21%
Unknown 65 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 88. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 November 2023.
All research outputs
#479,622
of 25,349,035 outputs
Outputs from Journal of Cheminformatics
#4
of 958 outputs
Outputs of similar age
#9,858
of 319,894 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 21 outputs
Altmetric has tracked 25,349,035 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 958 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 319,894 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.