In this paper, we propose a novel approach to measure inconsistencies in ontologies based on Shapley values, which are originally proposed for game theory. This measure can be used to identify which axioms in an input ontology or which parts of these axioms need to be removed or modified in order to make the input consistent. We also propose optimization techniques to improve the efficiency of ...

An important role of statistical analysis in science is for interpreting and communicating statistical evidente per se showing “what the data say.” Although standard methods (hypothesis testing, estimation, confidence intervals) are routinely used for this purpose, the theory behind those methods contains no defined concept of evidente, and no answer to the basic question, “When is it correct t...

BACKGROUND A recent paper found that terminal digits of statistical values in Nature deviated significantly from an equiprobable distribution, indicating errors or inconsistencies in rounding. This finding, as well as the discovery that a large percentage of p values were inconsistent with reported test statistics, led to a great deal of concern in the popular press and scientific community. Th...

Here we provide a biologically relevant proof of the well-known result from economics and statistical decision theory that having more information never reduces the expected payoff to a decision-making agent. We then go on to illustrate this with an ecologically motivated example based on a model of growth under uncertain predation risk. Throughout we use the central result that the fitness (re...

Discovering and exploiting statistical features in relational datasets is key to query optimization in a relational database management system (rdbms), and is also needed for database design, cleaning, and integration. This paper surveys a variety of methods for automatically discovering important statistical features such as correlations, functional dependencies, keys, and algebraic constraint...

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