Worldwide Use and Impact of the NASA Astrophysics Data System Digital Library

By combining data from the text, citation, and reference databases with data from the ADS readership logs we have been able to create Second Order Bibliometric Operators, a customizable class of collaborative filters which permits substantially improved accuracy in literature queries. Using the ADS usage logs along with membership statistics from the International Astronomical Union and data on the population and gross domestic product (GDP) we develop an accurate model for world-wide basic research where the number of scientists in a country is proportional to the GDP of that country, and the amount of basic research done by a country is proportional to the number of scientists in that country times that country's per capita GDP. We introduce the concept of utility time to measure the impact of the ADS/URANIA and the electronic astronomical library on astronomical research. We find that in 2002 it amounted to the equivalent of 736 FTE researchers, or $250 Million, or the astronomical research done in France. Subject headings: digital libraries; bibliometrics; sociology of science; information retrievalComment: ADS bibcode: 2005JASIS..56...36K This is a portion (The bibliometric properties of article readership information is the other part) of the article: The NASA Astrophysics Data System: Sociology, bibliometrics and impact, which went on-line in the summer of 200

Geoscience after IT: Part N. Cumulated references

Cumulated references for papers in Geoscience after IT: A view of the present and future impact of Information Technology on Geoscienc

Semi-parametric goodness-of-fit test for clustered point processes with a shape-constrained pair correlation function

Specification of a parametric model for the intensity function is a fundamental task in statistics for spatial point processes. It is, therefore, crucial to be able to assess the appropriateness of a suggested model for a given point pattern data set. For this purpose, we develop a new class of semi-parametric goodness-of-fit tests for the specified parametric first-order intensity, without assuming a full data generating mechanism that is needed for the existing popular Monte-Carlo tests. The proposed tests crucially rely on accurate nonparametric estimation of the second-order properties of a point process. To address this we propose a new nonparametric pair correlation function (PCF) estimator for clustered spatial point processes under some mild shape constraints, which is shown to achieve uniform consistency. The proposed test statistics are computationally efficient owing to closed-form asymptotic distributions and achieve the nominal size even for testing composite hypotheses. In practice, the proposed estimation and testing procedures provide effective tools to improve parametric intensity function modeling, which is demonstrated through extensive simulation studies as well as a real data analysis of street crime activity in Washington DC