Institutionalising Ontology-Based Semantic Integration

We address what is still a scarcity of general mathematical foundations for ontology-based semantic integration underlying current knowledge engineering methodologies in decentralised and distributed environments. After recalling the first-order ontology-based approach to semantic integration and a formalisation of ontological commitment, we propose a general theory that uses a syntax-and interpretation-independent formulation of language, ontology, and ontological commitment in terms of institutions. We claim that our formalisation generalises the intuitive notion of ontology-based semantic integration while retaining its basic insight, and we apply it for eliciting and hence comparing various increasingly complex notions of semantic integration and ontological commitment based on differing understandings of semantics

The Information-Flow Approach to Ontology-Based Semantic Integration

In this article we argue for the lack of formal foundations for ontology-based semantic alignment. We analyse and formalise the basic notions of semantic matching and alignment and we situate them in the context of ontology-based alignment in open-ended and distributed environments, like the Web. We then use the mathematical notion of information flow in a distributed system to ground three hypotheses that enable semantic alignment. We draw our exemplar applications of this work from a variety of interoperability scenarios including ontology mapping, theory of semantic interoperability, progressive ontology alignment, and situated semantic alignment

Progressive Ontology Alignment for Meaning Coordination: an Information-Theoretic Foundation

We elaborate on the mathematical foundations of the meaning coordination problem that agents face in open environments. We investigate to which extend the Barwise-Seligman theory of information flow provides a faithful theoretical description of the partial semantic integration that two agents achieve as they progressively align their underlying ontologies through the sharing of tokens, such as instances. We also discuss the insights and practical implications of the Barwise-Seligman theory with respect to the general meaning coordination proble

Ontology mapping: the state of the art

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mapping has beeb the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping

A formal foundation for ontology alignment interaction models

Ontology alignment foundations are hard to find in the literature. The abstract nature of the topic and the diverse means of practice makes it difficult to capture it in a universal formal foundation. We argue that such a lack of formality hinders further development and convergence of practices, and in particular, prevents us from achieving greater levels of automation. In this article we present a formal foundation for ontology alignment that is based on interaction models between heterogeneous agents on the Semantic Web. We use the mathematical notion of information flow in a distributed system to ground our three hypotheses of enabling semantic interoperability and we use a motivating example throughout the article: how to progressively align two ontologies of research quality assessment through meaning coordination. We conclude the article with the presentation---in an executable specification language---of such an ontology-alignment interaction model

Residual analysis methods for space--time point processes with applications to earthquake forecast models in California

Modern, powerful techniques for the residual analysis of spatial-temporal point process models are reviewed and compared. These methods are applied to California earthquake forecast models used in the Collaboratory for the Study of Earthquake Predictability (CSEP). Assessments of these earthquake forecasting models have previously been performed using simple, low-power means such as the L-test and N-test. We instead propose residual methods based on rescaling, thinning, superposition, weighted K-functions and deviance residuals. Rescaled residuals can be useful for assessing the overall fit of a model, but as with thinning and superposition, rescaling is generally impractical when the conditional intensity $\lambda$ is volatile. While residual thinning and superposition may be useful for identifying spatial locations where a model fits poorly, these methods have limited power when the modeled conditional intensity assumes extremely low or high values somewhere in the observation region, and this is commonly the case for earthquake forecasting models. A recently proposed hybrid method of thinning and superposition, called super-thinning, is a more powerful alternative.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS487 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

On the Mathematical Foundations of Semantic Interoperability and Integration

We report on the issues discussed at the breakout session held at the Dagstuhl Seminar on Semantic Interoperability and Integration on September 23, 2004

Monitoring Radiation Damage in the ATLAS Pixel Detector

Radiation hardness is one of the most important features of the ATLAS pixel detector in order to ensure a good performance and a long lifetime. Monitoring of radiation damage is crucial in order to assess and predict the expected performance of the detector. Key values for the assessment of radiation damage in silicon, such as the depletion voltage and depletion depth in the sensors, are measured on a regular basis during operations. This thesis summarises the monitoring program that is conducted in order to assess the impact of radiation damage and compares it to model predictions. In addition, the physics performance of the ATLAS detector highly depends on the amount of disabled modules in the ATLAS pixel detector. A worrying amount of module failures was observed during run I. Thus it was decided to recover repairable modules during the long shutdown (LS1) by extracting the pixel detector. The impact of the module repairs and module failures on the detector performance is analysed in this thesis

Effects of person-environment fit of gender-role orientation on burnout, engagement and hair steroids as stress biomarkers among women

Background: Analysis on gender related differences in occupational stress and burnout levels usually reveal higher occupational stress and burnout levels for women compared to men, especially in male-dominated working environments. In opposition to group differentiation, more specific gender-related dimensions feminity and masculinity were used in the study to describe individual and work environment characteristics and analyze their effects. Methods: In a cross-sectional design, survey results were linked to steroid levels in hair samples. Data was collected in a German medical services company with 146 employed women age 22-66 years (M = 40.48, SD = 10.38), 58 of them provided hair samples for steroid detection. Feminity and masculinity were measured by Gender Role Orientation Scale GTS+. Two Person-Environment fit scores in feminity and masculinity were calculated by subtracting individual from environment values. Both fit scores were proved as predictors in hierarchical linear regression models predicting burnout and work engagement as well as hair steroids cortisol, cortisone, DHEA, testosterone and progesterone detected by Liquid Chromatography-Mass Spectrometry (LC-MS/MS) as stress biomarkers. Bivariate correlations as well as moderator and mediator analysis were implemented. Results: After considering age, role clarity, and work organization, Person-Environment fit in feminity still added significant variance explanation (beta = .23, increment R-2 = .05, p = .003) for burnout. Person-Environment fit in feminity also explained poor variance in work engagement (beta = -.29, R-2 = .09, p < .001). Person-Environment fit in masculinity added considerable variance explanation (beta = .34, increment R-2 = .12, p = 0.018) to cortisol levels after including quantitative demands to the model. Conclusions: Person-Environment fit in feminity might be inspected as a predictor for burnout and work engagement. Person-Environment fit in masculinity can be taken into consideration as a predictor for hair cortisol as stress biomarker. Feminity and masculinity can be used as personality traits as well as characteristics of work environment, thus providing a particular gender-role related method of differentiation within gender groups. Also, specific methods could be derived for stress and burnout prevention and promotion of work engagement. Representative population studies with bigger samples and longitudinal surveys are needed to better explore the benefits and limitations of this approach

Asperity-based earthquake likelihood models for Italy

The Asperity Likelihood Model (ALM) hypothesizes that small-scale spatial variations in the b-value of the Gutenberg-Richter relationship have a central role in forecasting future seismicity. The physical basis of the ALM is the concept that the local b-value is inversely dependent on the applied shear stress. Thus low b-values (b 1.1), which can be found, for example, in creeping sections of faults, suggest a lower probability of large events. To turn this hypothesis into a forecast model for Italy, we first determined the regional b-value (b = 0.93 ±0.01) and compared it with the locally determined b-values at each node of the forecast grid, based on sampling radii ranging from 6 km to 20 km. We used the local b-values if their Akaike Information Criterion scores were lower than those of the regional b-values. We then explored two modifications to this model: in the ALM.IT, we declustered the input catalog for M ≥2 and smoothed the node-wise rates of the declustered catalog with a Gaussian filter. Completeness values for each node were determined using the probability-based magnitude of completeness method. In the second model, the hybrid ALM (HALM), as a «hybrid» between a grid-based and a zoning model, the Italian territory was divided into eight distinct regions that depended on the main tectonic regimes, and the local b-value variability was thus mapped using the regional b-values for each tectonic zone