Philosophy of Master Planned Test and Evaluation .

Test and evaluation, in some form or the other, has always been a major component of the development and operation programmes relating to major defence systems. The traditional process is based on a largely unaccountable and non-inheritable process in which professionalism is thought to be sufficient to ensure that the programmes achieve performance targets. After years of evolution, the US Congress legislated around 1983, for the 'master-planned test and evaluation' process to be used under compulsion of law. This much improved test and evaluation process is outlined using a major defence procurement failure-that of the seventeenth century warship the 'Vasa'-as a case study to highlight the main features of the test and evaluation master-planned (TEMP) method

The Relevance of Measurement Data in Environmental Ontology Learning

Part 4: Semantics and EnvironmentInternational audienceOntology has become increasingly important to software systems. The aim of ontology learning is to ease one of the major problems in ontology engineering, i.e. the cost of ontology construction. Much of the effort within the ontology learning community has focused on learning from text collections. However, environmental domains often deal with numerical measurement data and, therefore, rely on methods and tools for learning beyond text. We discuss this characteristic using two relations of an ontology for lakes. Specifically, we learn a threshold value from numerical measurement data for ontological rules that classify lakes according to nutrient status. We describe our methodology, highlight the cyclical interaction between data mining and ontologies, and note that the numerical value for lake nutrient status is specific to a spatial and temporal context. The use case suggests that learning from numerical measurement data is a research area relevant to environmental software systems