Comprising nearly 120 million publications linked to grants, patents, clinical trials, datasets and policy documents, Dimensions’ enriched publication data make it a powerful tool for publishers looking to evaluate the research publishing landscape at scale and to develop a comprehensive, data-driven editorial strategy.
To get a full picture of the impact of your editorial acceptance and review strategy, it is important to be able to track the outcomes and impacts of rejected submissions. Tyler Ruse, Director of Publisher Solutions at Digital Science showed how publishers can use Dimensions to track and report on their rejected submissions in one of our recent webinars.
The publication dataset
Publication data in Dimensions come from a number of different databases, including Crossref, PubMed and Europe PMC, and Dimensions works directly with publishers to ensure that the data are as comprehensive and as complete as possible. Dimensions also has nearly 50 preprint servers indexed in the database, so the publications available to you are not limited to published peer-reviewed papers.
Furthermore, Dimensions links these publications to other data points such as Altmetric attention score, patents and policy documents, meaning that you can not only identify whether submissions you rejected were published but you can also evaluate the kind of impact that those papers have had.
Single title search
Dimensions’ advanced search capabilities and full array of measurements enable you to accurately locate publications. To find results for single rejected submissions, you can use the search function in Dimensions Analytics, considering the the following variables to locate the submissions precisely:
- Adding minimum publication year threshold
- Including corresponding author, or any author
- Using wild-cards, proximity searches and other available tools
You can also ensure that you are only reporting on outcomes of value to you. For example, you can filter by specific source titles to immediately determine whether the submission was published in a competitor journal or another publication of interest, or by publication type so that you only see whether the submission was eventually published in a format relevant to you.
With Dimensions’ filters you can not only be certain you are identifying submissions with precision, but also that your search effectively aligns with your editorial submissions strategy.
Reporting and analysing at scale
If you are looking to report on rejected submissions at scale such as per year or on an ongoing basis, Dimensions APIs and Dimensions on Google Big Query have the capabilities to make this a seamless process.
The Dimensions API is a powerful transactional tool, which supports extraction of Dimensions data for use in complex analyses and visualizations in support of internal analytical tools and reporting. Its flexibility gives you a few options to generate reports on rejected submissions:
- Building a python script to iterate through an entire list of different criteria – including title, corresponding author, publication year – giving you an output in a spreadsheet that is the result of hundreds of rejected submission inputs. We have a host of resources to help you develop something like this, including the API Lab.
- Building a connector between your submissions system and the API so that on a periodic basis, or as you report through your system, you can make direct calls between your submissions system and the API to see whether rejections you have made in the past have been published.
Dimensions on Google BigQuery provides full and direct access to the underlying dataset of Dimensions and its flexibility and performance makes it ideal for custom analytics, AI applications, automated reports and dashboards. Below you can see an example of a working integration with a pre-made query using the search criteria that we covered previously.
If you are interested in learning how Dimensions can benefit your organization, please contact us, and we’ll be in touch soon.