The peer review process is vital to helping funders and Editors of scholarly publications make critical decisions. The NIH alone receives over 50,000 grant applications per year, and the number of research articles submitted to scholarly journals continues to grow annually, making this task extremely time consuming. Funders and Editors alike need fast access to accurate data-driven search results pulled across millions of data assets to successfully organize and manage the grant application process.

The primary reason funders use Dimensions is to find reviewers for grant applications. But it isn’t just about finding reviewers, Funders also rely on Dimensions to inform them on the global landscape of a specific research topic, identify rising stars and potential editors as well as new colleagues and scientific advisory board members.

Top 7 time-saving strategies for finding reviewers

Dimensions data grows every single day. Today, Dimensions supports more than 200 global funders, saving them valuable time in their daily workflows.

Here are our top 7 time-saving tips, you can also watch a live demo of how to use Dimensions to find new reviewers and to help with peer reviews from our on-demand webinar.

#1 Traditional search strategy

Even the simplest of searches can uncover fast potential reviewer data. In figure 1, we are looking at 4 very simple filters:

  1. Topic: cancer prevention lung blood
  2. Recency: last 4 years
  3. Location: US
  4. Funded by: NIH

The results from this basic, traditional search can offer very useful and quick insights.

We can immediately review a list of researchers as well as some of their activity (publications, awarded grants etc.) in the field.

Figure 1: Traditional Search: Topic + Recency + Location + Funded By

By clicking on an individual, you get a quick view of who they are (Figure 2), what they are working on and where their expertise lies.

Figure 2: Traditional Search: Researcher Profiile

You might also be interested to look at a heat map (Figure 3) that shows grant funds received per lab/institute and per Funder. This can be useful from a landscape point of view but also to try and find new reviewers and step away from your usual suspect list of potential reviewers.

Figure 3: Heatmap results

#2 Funding abstract strategy

Sometimes overlooked but still very useful is an abstract search. Using the funding application abstract or funding announcement you can simply drop it into the Dimensions abstract search function (figure 4). This will result in an interconnected and very precise set of data between people, research outputs, networks and more. This type of search is more advanced in comparison to a traditional search. Whereas a traditional search relies mainly on keyword search data, an abstract search pulls out all the connected subtopics in an abstract and matches them very precisely to researchers in the field.

Figure 4: Funding abstract search

#3 Single application search strategy

Using the Dimensions Application workflow tool, Funders can group their applications into topic areas (figure 5).

Figure 5: Grouping single applications into topics.

By clicking on ‘Reviewer Identification’ you can review (per single application) a list of reviewer candidates based on the science presented, potential conflicts, relevancy score and more (figure 6). There are many filters you can also add to further refine your results like region, recency, funded by and more.

Figure 6: Relevancy score, potential conflicts and more

When you click on ‘Details’ for an individual (figure 7), you can review some quick relevancy data to help understand if this person is a potentially good fit as a reviewer for the grant application.

Figure 7: Quick relevancy data and links per candidate

By selecting an individual researcher from the main list, you can dig even deeper (figure 8). Here you can see a list of the person’s publications and grants, but also their co-authors. This is very useful to a Funder if the individual has a potential conflict or is not available and they need to find an alternative candidate to review the application.

Figure 8: Individual reviewer candidate network and topics of expertise

#4 Multiple application search strategy

Using the multiple application reviewer identification tool can save Funders huge amount of time. Instead of clicking on ‘Reviewer Identification’ per application, simply select ‘Reviewer Identification’ at the group level instead (figure 9).

Figure 9: Group level/multiple application review identification

Using this function will produce a rank ordered list (figure 10) based on the topics contained within all the applications inside the group. Very granular filtering is also possible, by selecting potential candidates to find out if they cover some or all of the topics included in the group and what their availability is.

Figure 10: Group application candidate relevancy

#5 Single topic search strategy

The funding abstract or application search strategy uses a very precise set of (sub) topics. However, sometimes it is more useful to run a single topic search (figure 11). Using this function, you can build out your own search topics, subtopics and more. Again, the results list is ranked in order of relevancy and you can quickly explore the search results to find more information.

Figure 11: Single topic and subtopic search to find reviewer candidates

#6 Clustering search strategy

The clustering search strategy is extremely helpful when you manage a large group of applications. Using the ‘Clustering’ function allows you to sub categorize the applications within a certain group. The Dimensions tool will do this automatically for you based on the application abstract, but you can control the number of clusters within a group. Figure 12 shows a group with 9 different clusters of subcategories extracted from the entire group. Clusters can be saved as new groups and using this function helps Funders to drill down deeply into main and subtopics at just the click of a button.

Figure 12: Clustering

#7 Matrix matching search strategy

This makes a previously labour-intensive task incredibly fast. All you need to do is share your list of existing reviewer candidates and applications with us. We then match those candidates with your grant applications and provide you with a complete matrix of candidate relevancy scores (figure 13).

Figure 13: Matrix matching for reviewer candidacy and relevancy

Talk to us to learn more

To find out how Dimensions can help with finding researchers and helping with peer reviews, contact us and we’ll be in touch soon.