Authors
Affiliation

N. Manola

Athena Research Center

I. Grypari

Athena Research Center

P. Stavropoulos

Athena Research Center

H. Papageorgiou

Athena Research Center

Prevalence of preprinting

History

Version Revision date Revision Author
1.1 2023-08-29 Draft for initial publication I. Grypari
1.0 2023-05-09 First draft N. Manola, I. Grypari, P. Stavropoulos, H. Papageorgiou

Description

Description:

  • The “prevalence of preprinting” indicator measures the frequency of preprints that are made publicly available prior to peer review and publication in a journal. Preprinting allows researchers to share their work quickly and receive feedback from their peers before publication, and it also provides Open Access to research that might otherwise be locked behind journal paywalls.

Usefulness:

  • The “prevalence of preprinting” indicator can help assess the impact of preprinting on scholarly communication and the dissemination of research findings.
  • It provides insight into the growing trend of sharing research findings before they are formally published in a peer-reviewed journal.
  • It can hep measure the effectiveness of preprinting in speeding up the dissemination of research results.

Limitations:

  • Not all fields or research areas may have a culture of preprinting, which can affect the applicability of the indicator in different contexts.
  • As a standalone this indicator also does not account for other forms of informal communication, such as conference presentations, personal communications, or social media discussions, which can also play a role in the dissemination of research findings.

Metrics

Number of preprints

Description:

  • The “number of preprints” metric measures the absolute quantity of preprints.

Usefulness:

  • The “number of preprints” metric provides a quantitative measure of the prevalence of preprints in a particular field or research area or any other unit of analysis.

Limitations:

  • The pre-prints that are early in the research cycle (early work in progress) may not be ready for dissemination and may not be useful in a repository (not written in a clear away, too much of a rough draft).
  • View also the limitations in section I.

Measurement.

Count

Datasources
OpenAIRE Graph
  1. Identify the preprints in the OpenAIRE graph using the publication classification type “Preprint”
  2. Identify any repositories that only take preprints (preprint servers) and use those publications.
  3. In addition, find all the Green OA publications in OpenAIRE and
    1. From those, those that are published in Closed Access (but Green OA) they are preprints.
    2. Add to those, those that are not published yet, they are a preprint
    3. For the rest, if they are published check the date of deposition in repository, if it is earlier than the publication date, it is most likely a preprint and not the version of record. Checking how far before publication it was deposited is a useful measure in itself.
  4. Count

Limitations - Coverage of data for 1. (in other words, many preprints that are not described as preprints). If there are repositories that only accept preprints - For 2. Different preprint servers may have different policies regarding the types of preprints they accept, the length of time they allow preprints to be available, and the types of metadata that are included with preprints. These variations can affect the completeness and accuracy of the data used to calculate the metric. - For step 3.c. date of deposition is not a metadata element regularly exposed by repositories. This provides an additional problem as this metric is most meaningful if one can identify how long before publication something was deposited (if it is right before it shouldn’t be counted for this indicators).

% of Publications that have preprints

Description:

  • The “share of publications that have a preprint” metric measures the proportion of articles that are available as preprints.

Usefulness:

  • The “share of publications that have a preprint” metric can help assess the adoption of preprinting as a form of scholarly communication in a particular field or research area, and using a share as opposed to a relative value is more useful for comparisons, e.g. over time.

Limitations:

      • See limitations in previous metric.

Measurement.

% = 100*(pubs with preprint)/(total number of pubs)

Datasources
OpenAIRE Graph
  1. Take all the publications for unit of analysis
  2. Identify those with a preprint available, from the set of preprints as in previous metric
  3. Calculate share

Limitations

  • Like previous metric

% of preprints that are published

Description:

  • The “% of preprints that are published” metric measures the proportion of preprints that are eventually published in peer-reviewed journals.

Usefulness:

  • The “% of preprints that are published” metric provides insight into the effectiveness of preprinting as a tool for disseminating research findings and as a precursor to formal publication in peer-reviewed journals.
  • It can help researchers, institutions, and funding agencies to evaluate the impact of preprinting on the overall scholarly communication landscape.
  • This metric can also be used to identify trends in preprint adoption and publishing across different fields or research areas.

Limitations:

  • The “% of preprints that are published” metric has limitations because it does not account for the time lag between preprinting and formal publication in a peer-reviewed journal, which can vary widely depending on the field or research area.
  • This metric also does not account for the quality or impact of the preprint, which can affect its likelihood of being published in a peer-reviewed journal.

Measurement.

% = 100*(preprints that are published)/(total number of preprints)

Datasources
OpenAIRE Graph
  1. Identify preprints as in previous metrics
  2. Find those that are published
  3. Calculate share

Limitations

      • Like previous metric

Known correlates

We are unsure whether these are known but we would assume the following are correlates:

  • Field of research (preprint culture)
  • Time (adoption over time)
  • Funding source and Open Access policies of institutions(if it is a mandate)
  • Stage of career (preprint culture)
  • Collaboration networks, e.g. if large social media presence of network maybe likely to adopt preprinting practices.

Reuse

Open Science Indicator Handbook © 2024 by PathOS is licensed under CC BY 4.0 (View License)

Citation

BibTeX citation:
@online{apartis2023,
  author = {Apartis, S. and Catalano, G. and Consiglio, G. and Costas,
    R. and Delugas, E. and Dulong de Rosnay, M. and Grypari, I. and
    Karasz, I. and Klebel, Thomas and Kormann, E. and Manola, N. and
    Papageorgiou, H. and Seminaroti, E. and Stavropoulos, P. and Stoy,
    L. and Traag, V.A. and van Leeuwen, T. and Venturini, T. and
    Vignetti, S. and Waltman, L. and Willemse, T.},
  title = {PathOS - {D2.1} - {D2.2} - {Open} {Science} {Indicator}
    {Handbook}},
  date = {2023},
  url = {https://handbook.pathos-project.eu/indicator_templates/quarto/1_open_science/prevalence_preprinting.html},
  doi = {10.5281/zenodo.8305626},
  langid = {en}
}
For attribution, please cite this work as:
Apartis, S., G. Catalano, G. Consiglio, R. Costas, E. Delugas, M. Dulong de Rosnay, I. Grypari, et al. 2023. “PathOS - D2.1 - D2.2 - Open Science Indicator Handbook.” Zenodo. 2023. https://doi.org/10.5281/zenodo.8305626.