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      A standardized citation metrics author database annotated for scientific field

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          Abstract

          Citation metrics are widely used and misused. We have created a publicly available database of 100,000 top scientists that provides standardized information on citations, h-index, coauthorship-adjusted hm-index, citations to papers in different authorship positions, and a composite indicator. Separate data are shown for career-long and single-year impact. Metrics with and without self-citations and ratio of citations to citing papers are given. Scientists are classified into 22 scientific fields and 176 subfields. Field- and subfield-specific percentiles are also provided for all scientists who have published at least five papers. Career-long data are updated to end of 2017 and to end of 2018 for comparison.

          Abstract

          Citation metrics are widely used and misused. This Community Page article presents a publicly available database that provides standardized information on multiple citation indicators and a composite thereof, annotating each author according to his/her main scientific field(s).

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          Assessing scientists for hiring, promotion, and tenure

          David Moher, Florian Naudet, Ioana Cristea … (2018)
          Assessment of researchers is necessary for decisions of hiring, promotion, and tenure. A burgeoning number of scientific leaders believe the current system of faculty incentives and rewards is misaligned with the needs of society and disconnected from the evidence about the causes of the reproducibility crisis and suboptimal quality of the scientific publication record. To address this issue, particularly for the clinical and life sciences, we convened a 22-member expert panel workshop in Washington, DC, in January 2017. Twenty-two academic leaders, funders, and scientists participated in the meeting. As background for the meeting, we completed a selective literature review of 22 key documents critiquing the current incentive system. From each document, we extracted how the authors perceived the problems of assessing science and scientists, the unintended consequences of maintaining the status quo for assessing scientists, and details of their proposed solutions. The resulting table was used as a seed for participant discussion. This resulted in six principles for assessing scientists and associated research and policy implications. We hope the content of this paper will serve as a basis for establishing best practices and redesigning the current approaches to assessing scientists by the many players involved in that process.
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            Meta-research: Evaluation and Improvement of Research Methods and Practices

            John Ioannidis, Daniele Fanelli, Debbie Dunne … (2015)
            As the scientific enterprise has grown in size and diversity, we need empirical evidence on the research process to test and apply interventions that make it more efficient and its results more reliable. Meta-research is an evolving scientific discipline that aims to evaluate and improve research practices. It includes thematic areas of methods, reporting, reproducibility, evaluation, and incentives (how to do, report, verify, correct, and reward science). Much work is already done in this growing field, but efforts to-date are fragmented. We provide a map of ongoing efforts and discuss plans for connecting the multiple meta-research efforts across science worldwide.
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              The inconsistency of the h-index

              Ludo Waltman, Nees Jan van Eck (2012)
              Article 0 comments Cited 79 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): PLoS Biol
                Journal ID (iso-abbrev): PLoS Biol
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosbiol
                Title: PLoS Biology
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Print): 1544-9173
                ISSN (Electronic): 1545-7885
                Publication date (Electronic): 12 August 2019
                Publication date Collection: August 2019
                Publication date PMC-release: 12 August 2019
                Volume: 17
                Issue: 8
                Electronic Location Identifier: e3000384
                Affiliations
                [1 ] Departments of Medicine, Health Research and Policy, Biomedical Data Science, and Statistics and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, United States of America
                [2 ] Research Intelligence, Elsevier B.V., Amsterdam, the Netherlands
                [3 ] SciTech Strategies, Inc., Wayne, Pennsylvania, United States of America
                [4 ] SciTech Strategies, Inc., Albuquerque, New Mexico, United States of America
                Author notes

                The authors have declared that no competing interests exist. JPAI is a member of the editorial board of PLoS Biology. Jeroen Baas is an Elsevier employee. Elsevier runs Scopus, which is the source of this data, and also runs Mendeley Data where the database is now stored.

                Author information
                http://orcid.org/0000-0003-3118-6859
                http://orcid.org/0000-0001-8005-4153
                http://orcid.org/0000-0001-7814-8951
                Article
                Publisher ID: PBIOLOGY-D-19-01244
                DOI: 10.1371/journal.pbio.3000384
                PMC ID: 6699798
                PubMed ID: 31404057
                SO-VID: 6cccec3a-1be9-4200-9122-3c12aea6d0a2
                Copyright © © 2019 Ioannidis et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Figures: 0, Tables: 1, Pages: 6
                Funding
                The Meta-Research Innovation Center at Stanford (METRICS) has been funded by the Laura and John Arnold Foundation (funding to JPAI). The work of JPAI is also funded by an unrestricted gift from Sue and Bob O’Donnell. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Community Page
                Subject: Science Policy
                Subject: Science and Technology Workforce
                Subject: Careers in Research
                Subject: Scientists
                Subject: People and Places
                Subject: Population Groupings
                Subject: Professions
                Subject: Scientists
                Subject: Research and Analysis Methods
                Subject: Research Assessment
                Subject: Citation Analysis
                Subject: Research and Analysis Methods
                Subject: Research Assessment
                Subject: Bibliometrics
                Subject: Research and Analysis Methods
                Subject: Scientific Publishing
                Subject: Medicine and Health Sciences
                Subject: Clinical Medicine
                Subject: Biology and Life Sciences
                Subject: Immunology
                Subject: Medicine and Health Sciences
                Subject: Immunology
                Subject: Engineering and Technology
                Subject: Telecommunications
                Subject: Social Sciences
                Subject: Sociology
                Subject: Communications
                Custom metadata
                PLOS Publication Stage vor-update-to-uncorrected-proof
                Publication Update 2019-08-19

                ScienceOpen disciplines: Life sciences
                Data availability:
                ScienceOpen disciplines: Life sciences

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