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      Usage Bibliometrics as a Tool to Measure Research Activity

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          Abstract

          Measures for research activity and impact have become an integral ingredient in the assessment of a wide range of entities (individual researchers, organizations, instruments, regions, disciplines). Traditional bibliometric indicators, like publication and citation based indicators, provide an essential part of this picture, but cannot describe the complete picture. Since reading scholarly publications is an essential part of the research life cycle, it is only natural to introduce measures for this activity in attempts to quantify the efficiency, productivity and impact of an entity. Citations and reads are significantly different signals, so taken together, they provide a more complete picture of research activity. Most scholarly publications are now accessed online, making the study of reads and their patterns possible. Click-stream logs allow us to follow information access by the entire research community, real-time. Publication and citation datasets just reflect activity by authors. In addition, download statistics will help us identify publications with significant impact, but which do not attract many citations. Click-stream signals are arguably more complex than, say, citation signals. For one, they are a superposition of different classes of readers. Systematic downloads by crawlers also contaminate the signal, as does browsing behavior. We discuss the complexities associated with clickstream data and how, with proper filtering, statistically significant relations and conclusions can be inferred from download statistics. We describe how download statistics can be used to describe research activity at different levels of aggregation, ranging from organizations to countries. These statistics show a correlation with socio-economic indicators. A comparison will be made with traditional bibliometric indicators. We will argue that astronomy is representative of more general trends.

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          Measuring contextual citation impact of scientific journals

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            Galaxy Zoo : Morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey

            In order to understand the formation and subsequent evolution of galaxies one must first distinguish between the two main morphological classes of massive systems: spirals and early-type systems. This paper introduces a project, Galaxy Zoo, which provides visual morphological classifications for nearly one million galaxies, extracted from the Sloan Digital Sky Survey (SDSS). This achievement was made possible by inviting the general public to visually inspect and classify these galaxies via the internet. The project has obtained more than 40,000,000 individual classifications made by ~100,000 participants. We discuss the motivation and strategy for this project, and detail how the classifications were performed and processed. We find that Galaxy Zoo results are consistent with those for subsets of SDSS galaxies classified by professional astronomers, thus demonstrating that our data provides a robust morphological catalogue. Obtaining morphologies by direct visual inspection avoids introducing biases associated with proxies for morphology such as colour, concentration or structual parameters. In addition, this catalogue can be used to directly compare SDSS morphologies with older data sets. The colour--magnitude diagrams for each morphological class are shown, and we illustrate how these distributions differ from those inferred using colour alone as a proxy for morphology.
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              Usage impact factor: The effects of sample characteristics on usage-based impact metrics

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                Author and article information

                Journal
                2017-06-07
                Article
                1706.02153
                852aa225-1844-4345-a7e2-067da71eb67d

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                25 pages, 11 figures, accepted for publication in Handbook of Quantitative Science and Technology Research, Springer
                cs.DL astro-ph.IM cs.CY cs.IR physics.soc-ph

                General physics,Applied computer science,Information & Library science,Instrumentation & Methods for astrophysics

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