This book is written for members of the scholarly research community, and for persons involved in research evaluation and research policy. More specifically, it is directed towards the following four main groups of readers: – All scientists and scholars who have been or will be subjected to a quantitative assessment of research performance using citation analysis. – Research policy makers and managers who wish to become conversant with the basic features of citation analysis, and about its potentialities and limitations. – Members of peer review committees and other evaluators, who consider the use of citation analysis as a tool in their assessments. – Practitioners and students in the field of quantitative science and technology studies, informetrics, and library and information science. Citation analysis involves the construction and application of a series of indicators of the ‘impact’, ‘influence’ or ‘quality’ of scholarly work, derived from citation data, i.e. data on references cited in footnotes or bibliographies of scholarly research publications. Such indicators are applied both in the study of scholarly communication and in the assessment of research performance. The term ‘scholarly’ comprises all domains of science and scholarship, including not only those fields that are normally denoted as science – the natural and life sciences, mathematical and technical sciences – but also social sciences and humanities.

The 2018 MPDI Writing Prize invited early stage researchers who are not native English speakers to write on the subject of "the global benefits of open research". Six prizes were awarded, however there were many more entries. This book collates many of those entries and contains inspiring, thought-provoking and original viewpoints of open science through the eyes of those conducting research on a daily basis

Zeke Armstrong goes to New York for an inline skate-off. After another racer robs an aging heiress in Central Park, the police call it a mugging. 13 year old Zeke suspects that it's a more sinister plot.