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Using a Researcher Profile and Understanding the Impact of the Author’s

Dju-Lyn Chng 11th May 2021 Importance of showcasing your research

Discovery • Get noticed by potential collaborators

• Enhance the reputation of yourself, your Assessment Analysis department and your institution

• Demonstrate the breadth of your research to: • Hiring committees • Funding agencies • Tenure evaluators Outreach Publication • Identify researchers for mentorship or collaboration

2 Making sure you are noticed

and not mixed up with someone else

3 What is Author disambiguation? Name ambiguity is a frequently encountered problem in the scholarly community: Also published as: • Avram Noam Chomsky • Different researchers • N. Chomsky ﻧﻌﻮم ي�ﺸﻮﻣﺴ� • publish under the same נועם חומסקי • .name • Individual researchers FACT: A mere hundred surnames still make up over 85% of China's 1.3 billion citizens. publish under many names. The top three—Wang, Li , and Zhang—cover more than 20% of the population. • Languages and cultural naming conventions introduce additional Author disambiguation is a process that aims challenges. to find all publications that belong to a given author and distinguish them from publications of other authors who share the same name.

4 What drives the need for author profiling systems?

INDIVIDUALS RESEARCH PRODUCING INSTITUTIONS RESEARCH FUNDERS SCHOLARLY PUBLISHERS

• Learn (e.g. get familiar • Showcase faculty expertise • Recruit grant • Recruit with someone else’s − Attract the attention of funders, reviewers reviewers work) industry, and media • Identify subject • Vet the publications • Find mentors − Demonstrate ROI to the public matter experts for record of submitting • Vet collaborators − Promote collaboration across board/advisory authors • Gain exposure, build a departments positions • Identify & vet career • Recruit the “best” candidates • Vet the publications editors/editorial board • Own their scholarly • See and assess the research activity record of grant members identity that is occurring within. applicants

DISCOVERY Librarians support all of these stakeholders and often bear the burden of wrestling with ambiguous author data in systems. EVALUATION

5 Correctly getting noticed

6 Correctly getting noticed

7 8 9 10 Bringing it all together

A unique experience for An easier way to unique author identifiers. manage profiles.

Web of / has a Update your ORCID and corrections will will automatically unique Identifying number. Core Collection sync with Web of Science. Author Records Web of Science ResearcherID links (powered by Distinct Author Identification System) the disambiguated data across systems in a bidirectional relationship. Web of Science ResearcherID Creating a Publons profile will generate a Web of Science ResearcherID. Publons Update your Publons profile and Authors can adjust which Web of changes can be sent to ORCiD Science publications are theirs in - or - Publons and those changes are Update your ORCiD and changes automatically reflected in Web of can be sent to Publons. Science.

11 Is a set of output better than another?

Insert footer 12 Current Forms of Assessing Impact:

Absolute Like for Like Normalization

Measure of productivity Allow limited comparisons Put data in context & allow comparisons

Number of Documents H-index Normalized Impact Times cited Percentile Indicators Percent Cited Journal ESI Highly Cited Papers

13 Publication Level Metrics

Our InCites Benchmarking & Analytics tool provides many indicators based around citational analysis. The “Percentile in Subject Area” is one of these and it is now also providing context to the received by publications in the Web of Science.

The “Percentile in Subject Area” will change on 28th May 2021.

Current Definition: 0 is best, 100 is worst (lower the value, the better it is) DetailsRevised Are Definition Static (in May 28 release): 0 is worst, 100 is best (higherMetrics the value, Are the better Dynamic it is)

Percentile This example is for publications in 2015, in the research field of Organic Chemistry. Calculation Each document is compared to their YEAR, CATEGORY (research field) and document type.

Using this comparison, they are each given a set of normalised metrics.

This figure is from a ISI produced recently, which can be downloaded here.

Additional information on how we use normalized indictors can be found here. The highest number of citations received by a publication was 462, lowest 0. The figure demonstrates how skewed the distribution is and how useful a percentile is.

16 Each purple node represents an article or group of articles. Its position Author Record Beamplot shows its year of publication (y-axis) and its citation percentile (x-axis).

A beamplot is a type of graph that plots an author’s publications citation percentile values on a ‘beam’. The default time period shown is the last 10 years, this can be change to their whole career. They were proposed by Lutz Bornmann and Robin Haunschild of the Max Planck Institute and were supported by the Institute for Scientific Information (ISI) in the Profiles, not Metrics (2018) report, as an alternative indicator to the H-index, as a measure of a researcher’s citation profile.

We have now introduced them into Author Records in the Web of Science.

They allow you to:  View article performance in appropriate context  See performance change over time The Median for all their publications is shown as a dotted vertical line. In Web of Science, a higher percentile value means better performance. A paper with a percentile of value of 99, is in the top 1% of ‘like’ publications.

17 Author Profiles

Each document is compared to their YEAR and CATEGORY of A single records percentile publication. Using this comparison, they are each given a set of normalised Median percentile for the year metrics.

A Beamplot allows one to visualise in a single figure Median percentile for the career the normalised percentile of every document a researcher has produced over the course of their career. Author Profiles

Each document is compared to their YEAR and CATEGORY of publication. Using this comparison, they are each given a set of normalised metrics.

A Beamplot allows one to visualise in a single figure the normalised percentile of every document a researcher has produced over the course of their career. Author Record Beamplot

THINGS TO KNOW

. Percentile values are sourced from InCites Benchmarking & Analytics (including ESCI data). . Beamplots only include publications with the Web of Science document type, Article or Review. . Percentiles are calculated for publications back to 1980. Current and previous year publications are excluded from the beamplot (due to low number of citations). . Publications may be assigned more than one subject category. The category displayed is the highest performing.

20 Blog posts https://clarivate.com/webofsciencegroup/blog/

A researcher’s complete guide to papers The | your definitive guide Research paper search tips you'll wish you knew Three tips to save hundreds of hours writing research papers How to write a How to find the right journal for your research (using actual data) Find top journals in a research field: a step-by-step guide Find and advance the hottest new research in your field, step-by-step Find the top authors in a research field: What you need to know tips every librarian should know

21 Additional resources

Web of Science Learning > Web of Science Academy > Events & Webinars > LibGuides > Videos > Web of Science Blog > Web of Science news hub > Researcher Recognition >

22 Thank you

Dju-Lyn Chng, Regional Solution Consultant

[email protected] clarivate.com

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