Update Jan. 20, 2020

Thank you to those who provided comments. No changes were suggested for the dataset per se; the documentation has been revised to reflect the comments and the final version is now available here.

OA APC Main 2019 dataset documentation final

This is an invitation to participate in an open peer review of the OA APC Main 2019 dataset, its documentation and the value of research blogposts made possible through this project. While feedback on the OA APC project is appreciated at any time, the formal open peer review period is Dec. 1, 2019 – Jan. 15, 2020. My perspective is that open peer review is in an early phase where experimentation with different approaches could be useful to develop future best practices.

For this reason, reviewers are welcome to submit comments in the format or venue of their choice. Comments on this blogpost are the most convenient approach for the author. Signed comments are preferred. At the end of the formal open peer review period (Jan. 15), I will write a summary of the open peer review process, including all comments and responses where warranted. Comments to date and replies are posted here.

Links:

• Dataset: Morrison, Heather, et al. 2019, “OA APC longitudinal study dataset 2019”, https://doi.org/10.5683/SP2/0DIPGE, Scholars Portal Dataverse, V1
• Documentation (pre-open-peer-review): OA APC Main 2019 dataset documentation
• Examples of recent research blogposts can be found through the OA APC longitudinal survey 2019 post https://sustainingknowledgecommons.org/2019/11/27/oa-apc-longitudinal-survey-2019/

Questions to consider in the open peer review process:

The following are meant as guidelines only. Please feel free to focus on one or more specific questions that you find of interest and/or feel qualified to comment on, including questions not asked.

1. Importance and relevance of the research questions: the project’s research question and sub-questions (from the documentation) are as follows:

Research question

What trends can be observed in APCs over time? Subquestions:

• • Will competition emerge, or will an inelastic market transition or reappear?
  • Will the percentage of journals that are charging and non-charging remain the same or change?
  • Will fully OA journals continue to actively publish, cease, change to partially OA (hybrid) or non-OA journals?
  • What are the OA publishing and charging / non-charging trends and practices of particular publishers? (Note: results of individual research project done sustainingknowledgecommons.org)

Are any of the research questions important, relevant, or otherwise? Do you have any advice for the research team or potential downstream researchers using the dataset about research that you think will be important and relevant in future? Do you have any suggestions for further research?

2. Adequacy of the documentation: is the documentation of the dataset sufficient so that a downstream researcher could continue this research if desired and/or use a subset of the dataset for further research?

3. Limitations: Are the limitations of the dataset sufficiently well described? Is anything missing?

4. Alternative approaches: Are the alternative approaches sufficiently well described?

5. Errors in the dataset: Please note any errors found in the dataset (be specific).

6. Other: please provide feedback on any aspects of the dataset or its documentation not covered in the above questions.

Second update January 8: thanks to Heather Staines from MIT’s Knowledge Futures Group for initiating a conversation on open peer review processes via e-mail and agreeing to publish on the blog. This conversation (which prompted the initial procedural update) can be found here.

Procedural update January 8: there are diverse approaches to data documentation and open peer review. Peer review of an earlier version of this dataset and documentation was published in MDPI’s innovative journal Data, designed for this purpose (Morrison et al. 2017). Tools have been, and are being, developed to provide technical support for new, more open approaches to peer review such as hypothes.is, which facilitates online annotations. I see tremendous potential for open peer review, online annotations, and collaborative online writing. However, I see the process of transformation as in an early stage where experiments (like this one) and open discussion are more important than technical solutions. In other words, my choice of this approach – blogpost and open-ended invitation –  is deliberate. Discussion about open peer review process and potential is welcome, although it is a side-conversation to reviewing this dataset designed to facilitate study of longitudinal trends in article processing charges.

Cite as:

Morrison, H. (2019). OA Main 2019: Dataset, documentation and open peer review invitation. Sustaining the Knowledge Commons. Retrieved from https://sustainingknowledgecommons.org/2019/11/20/oa-main-2019-dataset-documentation-and-open-peer-review-invitation/

Rev. Jan. 20, 2020