Necessary but not sufficient: unique author identifiers

Harrison, Andrew; Harrison, Anthony

doi:10.1136/bmjinnov-2016-000135

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…It is widely known that a considerable proportion of authors share the same last name and first initial (Falagas 2006 ) which is a big problem for correctly identifying individuals and networks in PMCs database. Besides that, the use of the Western-driven (surname/family name|given/first name|middle initial) system is particularly problematic for Asian biomedical researchers in general: Japan, China and especially Korea, where only a few surnames predominate and middle names often do not exist (Harrison and Harrison 2016 ).…”

Section: Resultsmentioning

confidence: 99%

“…Several registers that supply a nomenclature for a clear author distinction exist. Harrison and Harrison ( 2016 ) have highly recommended their use. A comparably small but steadily increasing amount of articles in PMC supplies an author identification number for at least one author.…”

Section: Resultsmentioning

confidence: 99%

“…The frequent absence of an author identification number is still a crucial element for analyses on publications by a specific author or network. Before the U.S. National Institutes of Health (NIH) and its National Library of Medicine (NLM) launched the modern PubMed system, the math, physics and computer science community already solved this problem with the creation of ’arXiv’ in the early 1990s (Harrison and Harrison 2016 ). Harrison and Harrison ’s claim: ”The time has come for ’DOIs for authors” ought to be implemented for authors and editors as soon as possible.…”

Section: Discussionmentioning

confidence: 99%

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Software review: The JATSdecoder package—extract metadata, abstract and sectioned text from NISO-JATS coded XML documents; Insights to PubMed central’s open access database

Böschen¹

2021

Scientometrics

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JATSdecoder is a general toolbox which facilitates text extraction and analytical tasks on NISO-JATS coded XML documents. Its function JATSdecoder() outputs metadata, the abstract, the sectioned text and reference list as easy selectable elements. One of the biggest repositories for open access full texts covering biology and the medical and health sciences is PubMed Central (PMC), with more than 3.2 million files. This report provides an overview of the PMC document collection processed with JATSdecoder(). The development of extracted tags is displayed for the full corpus over time and in greater detail for some meta tags. Possibilities and limitations for text miners working with scientific literature are outlined. The NISO-JATS-tags are used quite consistently nowadays and allow a reliable extraction of metadata and text elements. International collaborations are more present than ever. There are obvious errors in the date stamps of some documents. Only about half of all articles from 2020 contain at least one author listed with an author identification code. Since many authors share the same name, the identification of person-related content is problematic, especially for authors with Asian names. JATSdecoder() reliably extracts key metadata and text elements from NISO-JATS coded XML files. When combined with the rich, publicly available content within PMCs database, new monitoring and text mining approaches can be carried out easily. Any selection of article subsets should be carefully performed with in- and exclusion criteria on several NISO-JATS tags, as both the subject and keyword tags are used quite inconsistently.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Software review: The JATSdecoder package—extract metadata, abstract and sectioned text from NISO-JATS coded XML documents; Insights to PubMed central’s open access database

Böschen¹

2021

Scientometrics

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Defining the Scholarly Record

Dougherty

2018

Research Ethics Forum

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Aggregating large-scale databases for PubMed author name disambiguation

Zhang

Huang

Yang

et al. 2021

Journal of the American Medical Informatics Association

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Objective PubMed has suffered from the author ambiguity problem for many years. Existing studies on author name disambiguation (AND) for PubMed only used internal metadata for development. However, some of them are incomplete (eg, a large number of names are only abbreviated and their full names are not available) or less discriminative. To this end, we present a new disambiguation method, namely AggAND, by aggregating information from external databases. Materials and Methods We address this issue by exploring Microsoft Academic Graph, Semantic Scholar, and PubMed Knowledge Graph to enhance the built-in name metadata, and extend the internal metadata with some external and more discriminative metadata. Results Experimental results on enhanced name metadata demonstrate comparable performance to 3 author identifier systems, as well as show superiority over the original name metadata. More importantly, our method, AggAND, incorporating both enhanced name and extended metadata, yields F1 scores of 95.80% and 93.71% on 2 datasets and outperforms the state-of-the-art method by a large margin (3.61% and 6.55%, respectively). Conclusions The feasibility and good performance of our methods not only help better understand the importance of external databases for disambiguation, but also point to a promising direction for future AND studies in which information aggregated from multiple bibliographic databases can be effective in improving disambiguation performance. The methodology shown here can be generalized to broader bibliographic databases beyond PubMed. Our code and data are available online (https://github.com/carmanzhang/PubMed-AND-method).

show abstract

Necessary but not sufficient: unique author identifiers

Cited by 4 publications

References 19 publications

Software review: The JATSdecoder package—extract metadata, abstract and sectioned text from NISO-JATS coded XML documents; Insights to PubMed central’s open access database

Software review: The JATSdecoder package—extract metadata, abstract and sectioned text from NISO-JATS coded XML documents; Insights to PubMed central’s open access database

Defining the Scholarly Record

Aggregating large-scale databases for PubMed author name disambiguation

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