title: The Question of Data Integrity in Article-Level Metrics.
abstract: Interest in and use of article-level metrics (ALMs) has grown rapidly amongst the research community, by researchers, publishers, funders, and research institutions. As this happens, it is critical to ensure secure and reliable data that is trustworthy and can be used by all. Two case studies are presented, which illustrate different approaches to establishing ALM data integrity.
authors: Social Science Research Network, Rochester, New York, United States of America.
authors: Gregg
authors: G
authors: Gordon
authors: Public Library of Science, San Francisco, California, United States of America.
authors: Jennifer
authors: J
authors: Lin
authors: Public Library of Science, San Francisco, California, United States of America; Independent, San Francisco, California, United States of America.
authors: Richard
authors: R
authors: Cave
authors: Social Science Research Network, Rochester, New York, United States of America.
authors: Ralph
authors: R
authors: Dandrea
mesh_terms: D015706:Bibliometrics; D035843:Biomedical Research / Q000592:standards*; D000068598:Data Accuracy; D035081:Editorial Policies; D006801:Humans; D055811:Journal Impact Factor; D015871:Scientific Misconduct