Researcher Corner

 
  • Dimensions – A new tool for citation metrics

Over the years, Web of Science and Scopus have always been the two major citation databases for exploring articles and indicating the research impact of research outputs. Early this year in January, a new platform - Dimensions was released, which covers more than 94 million publication records and provides citation metrics of publications, researchers and institutions on a partly free basis.
 
Different from Web of Science and Scopus, Dimensions integrates both a citation database and research analytics suite at one platform, trying to give users a simpler and integrated discovery experience. Researchers will be able to search within full text of the research output and not be limited to just the abstract, title or keywords, e.g. to find the research that adopts a particular experimental instrument. Because Dimensions has more than publications in their collection, researchers will also be able to explore patents on top of relevant articles by tracking the cited and citing documents. Dimensions’ emphasis on integrated discovery means that you will be directed to the fully licensed version of full text PDFs directly, bypassing publisher’s website. Dimensions’ superior algorithm means that Researcher Profiles are accurate and easy to use, providing accurate publication and citation information easily, and linking with ORCID and other available identifiers.
 
The Analytics feature in Dimensions offers ranking information on field of research, researchers and source titles (journal titles) by the number of publications, Field Citation Ratio (FCR) and Relative Citation Ratio (RCR). FCR and RCR are two new metrics available in Dimensions, which measure the relative citation performance of an article when compared to similar-aged articles in its subject area, and when compared to all other articles in its area of research, respectively. Researchers will be able to identify key publications, authors or journal titles in a research field out of these metrics. It can also be an alternative tool for researchers to measure the impact of a particular research paper, or a list of publications from a researcher’s profile.
Dimensions

When you explore a researcher profile, the analytics feature gives you deeper insights into the publication profile of the author – Fields of Research, co-authors (researchers) and source titles. What is different in Dimensions is that the classification for Fields of Research (FOR) is not based on journal classifications as used in Web of Science and Scopus. Instead, FOR in Dimensions is based on the Australian and New Zealand Standard Research Classification (ANZSRC) system. Therefore, FOR gives a more precise picture of the research portfolio of the author instead of using the proxy measure based on the subject of journals in which the author has published in.
 
 
Analytics
 

Refer to our guides to learn more about Research Impact, Article Impact & Author Impact.
 
 
  • Enhanced interface of Journal Citation Report (JCR)

Journal Citation Report (JCR), a platform providing journal impact factor and ranking information for approximately 12,000 scholarly journals in various fields, has released its enhanced interface recently with new analyses that help researchers gain more insights on the journal performance.

The enhanced interface provides a re-designed journal profile page for each journal, which allows researchers to view the top contributing articles, countries/regions and organizations that affect the journal’s performance. The contributing articles are now more visible for researchers as well, making it easier to link to Web of Science. The articles are sorted by Times Cited, which allows researchers to quickly identify which are the most influential articles to the journal.
 
 
JCR
 

These updates of JCR bring a full range of data and analyses for researchers helping them understand how a journal performs in a field in order to make better decisions in journal selection for publishing.

Researcher as Peer Reviewer

  • What is peer review?
Peer review is at the heart of the process of scholarly publishing, as it ensures the standards of originality and significance that papers need to meet before they get published. When a publisher receives a manuscript, usually two to four fellow experts in the area will be invited to examine the work before the editor makes a decision on whether the manuscript can be accepted, rejected, or needs revision. The “peers”, or reviewers, therefore play a vital role in maintaining the quality of the scientific publications.

Experienced researchers review papers mostly for the good of community and science, or to return “the favor” for their papers being reviewed by others. Some early career researchers do that because they can also learn from others thus makes them become a better author. Both are volunteering their time in improving others’ manuscripts. With the dramatic increase in research outputs in the past decade, the review work has gradually become a workload for many researchers, especially those with top expertise in the field, who are more likely to be selected as “good” reviewers.

Despite the many extra hours researchers have contributed, researchers unfortunately do not get sufficient recognition in doing reviews – they may simply receive an acknowledgement email, plus some free quota to download papers. In recent years, couple of new initiatives have emerged, including Elsevier’s Review Recognition Platform and Publons, a platform that centrally records peer review contributions for researchers. The former one, unfortunately only recognizes reviews done for Elsevier’s journals, while the latter can record reviews regardless of the journal publishers. Nevertheless, both are aiming to generate more incentives and credits for researchers in performing reviews.
 
  • Publons – Making reviews count
Publons tries to make every review count. By setting up a Publons profile, researchers will be able to track all their peer review and editorial contributions. The platform is easy to use too – Researcher can record a review by simply forwarding a “Thank you for reviewing” email to Publons, who will then verify the records and add them to the researcher’s profile. As Publons partners with more than 2,000 journals and offers options to integrate with the manuscript submission systems like ScholarOne and Editorial Manager, reviews from these journals can be added automatically, if the reviewer prefers to do so.

Your effort as a reviewer will be acknowledged and recorded, even if the paper is never published. You can also choose to make your review public in your profile if the journal allows. All the contributions displayed will turn to measurable and rewarding activities (by gaining “merit” in the system), which shows the volunteering efforts you have made in your research area. For early career researchers, this profile may also be used as a proof of your expertise in the field for career advancement.

Publons though is for reviewers, editors can also benefit from it. Not only to acknowledge their editorial work for journals, they can also use the platform to find and contact proper reviewers.
 

Over 140 PolyU researchers have registered with Publons. An example from one of our top reviewers in terms of the merit gained by doing reviews and serving on editorial board.

Fair Data vs Open Data

  • Research Data Sharing
An article published in the Economist mentioned that the most valuable resource on the world is no longer oil but data. In the scholarly world, data is far more valuable once it is being shared because it becomes “renewable”, allowing new analysis, new research to take place by reusing the data.

Data sharing is an emerging topic in recent years, and FAIR data is recognized worldwide as the guiding principle which maximizes the value of the shared data.
 

Image CC-BY-SA by SangyaPundir
  • What is FAIR Data?

    FAIR Data is the data with the following characteristics:
    • Findable- with a unique and persistent identifier.
    • Accessible- retrievable via a standard protocol open and free.
    • Interoperable- with metadata using a formal, accessible, shared, and broadly applicable language.
    • Reusable- with a clear usage license and have plurality of accurate and relevant attributes in metadata.

You may find the full description from here.

 
  • Is FAIR Data identical to Open Data?

    Data can be made open but not FAIR, and vice versa.

    Open data allows everyone to access, use, and share without restrictions arising from licenses, copyright and patents. However, not all of them are FAIR, in terms of their findability and reusability, e.g. when the data are lacking of unique and persistent identifier, or insufficient documentation and metadata. Therefore, in order to maximize the value of the shared data, data need to be FAIR.

    On the other hand, FAIR data does not mean they have to be made open before they can be shared. Restrictions can be adopted to shield data when it involves commercial interest, personal privacy, national security, and public interest. Data must be well managed before it can be FAIR and effectively shared.

    Wish to know how to manage your data effectively? Learn some tips from our Research Data Management LibGuide.