Abstract

Measures for research activity and impact have become integral ingredients in the assessment of a wide range of entities. 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 lifecycle, 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 read patterns possible. Clickstream logs allow us to follow information access by the entire research community in real time. Publication and citation datasets just reflect activity by authors. In addition, download statistics, derived from these clickstreams, will help us identify publications with significant impact, but which do not attract many citations. Clickstream 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 random browsing behavior. We will discuss the complexities associated with clickstream data and how, with proper filtering, statistically significant relations and conclusions can be inferred from download statistics. We will 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 strong correlation with socioeconomic indicatorsindicatorsocioeconomic, like the gross domestic product ). A comparison will be made with traditional bibliometric indicators. Since we will be using clickstream data from the Astrophysics Data System ), we will argue that astronomy is representative for more general trends.