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A Security Perspective on Publication Metrics
Author(s) -
Hugo Jonker,
Sjouke Mauw
Publication year - 2017
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
DOI - 10.1007/978-3-319-71075-4_21
Subject(s) - computer science , measure (data warehouse) , incentive , perspective (graphical) , value (mathematics) , index (typography) , computer security , operations research , risk analysis (engineering) , data mining , world wide web , microeconomics , economics , business , artificial intelligence , mathematics , machine learning
The importance of publication metrics, such as the h-index [9], has increased dramatically in recent years. Unfortunately, as Goodhart [7] already remarked: “when a measure becomes a target, it ceases to be a good measure”. And indeed: hiring, grants and tenure decisions depend more and more on performing well in publication metrics. This leads to a perverse incentive for individual researchers and journals to “optimise” their perfomance. However, such behaviour undermines the utility of the measure itself, in the extreme case nullifying its value. The underlying cause is that besides the functional requirements on a measurement, there are also security requirements on them. As is often the case, these security objectives remain implicit. In this paper, we provide a much-needed security perspective on publication metrics.

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