Using journal-level indicators, such as a journal’s impact factor, when assessing individual articles, produces an imprecise estimate of that article’s quality. In such a scenario, the article is lumped in with hundreds or thousands of other articles in the same journal, whose quality may vary widely. In humanities, publications receive too few citations to be appropriately analyzed using bibliometrics. Conference proceedings and books often lack the citation data necessary to be analyzed in this way. Furthermore, typical bibliometric indicators are not field-normalized and thus cannot be used to compare research in different fields or to assess multidisciplinary research.
When using a relatively small panel of reviewers to assess research within an institution, it is unlikely that all of the publications in need of assessment will fall within the reviewers’ core areas of expertise, or that the reviewers will have the time to read in depth all of these publications. In instances where reviewers are not able to assess the actual content of a publication, they are typically forced to rely on bibliometric indicators or other imprecise measures, like a journal’s reputation. This is a decidedly less rigorous and dependable process than true peer review.
Epistemio has developed intelligent algorithms that crunch “big data” about citation networks in order to suggest the most suitable reviewers. The suggested reviewers will be experts in the core field of the publications under assessment, and they may even have already read the publications as part of their own line of work. Thus, the effort spent reviewing the publications is minimized, and the reviewers will be able to quickly provide relevant ratings and reviews.
Our platform automates tedious manual tasks such as sending reminder emails to reviewers or aggregating statistics about the review process.
The assessed scientists or units provide a sample of their best publications;
Epistemio’s intelligent algorithms suggest the most suitable editors or reviewers. Final reviewers may then be selected from this refined pool or manually added;
Reviewers assess publications and provide ratings and reviews for each publication;
The ratings enable comparing the research performance of individuals, laboratories, departments, etc. within the assessed organization.
The processes can be customized according to your organization's needs.
Interested in deploying the Epistemio Research Assessment Exercise? Contact us to set up a call and get started.