On adopting Ontology Alignment techniques within the Phenotype Acquisition Process

The work presented in this paper is framed within the context of the BigMed project, aproject funded by the Norwegian Research Council. One of the objectives of BigMed isto enhance the phenotype acquisition process in newborns with a monogenetic disorder,one of the four patient groups studied in the project. The use of the Human PhenotypeOntology (HPO) [1] to tag phenotypes and systems like PhenoTips have substantiallycontributed to the overall phenotype acquisition workflow. PhenoTips [2] is a systemfor the acquisition of phenotypic information in patients with a genetic disease. Phe-noTips also suggests, given a selected set of HPO terms, candidate diagnoses usingOMIM (Online Mendelian Inheritance in Man) codes, and related genes for a subse-quent genetic test. Although PhenoTips represents a fantastic effort, we believe it couldbe extended with suitable Semantic Web solutions. In this paper, we present the firststeps to adopt ontology alignment techniques to contribute to the diagnostic process

Finding Data Should be Easier than Finding Oil

The competitiveness of modern enterprises heavily depends on their ability to make the right business decisions by relying on efficient and timely analysis of the right business critical data. In large and data intensive companies such as Equinor, a Norwegian multinational oil and gas company with more than 20,000 employees, gathering such data is not a trivial task due to the growing size and complexity of corporate information sources. As a result, the data gathering task is often the most time-consuming part of the decision making process, in particular when it comes to the work processes of Equinor's exploration geologists that should find in a timely manner new exploitable accumulations of oil or gas in given areas by analysing data about these areas. In this work we present our experience in addressing this data challenge tast at Equinor. We have developed and deployed at Equinor a semantic data access system that relies on the Ontology Based Data Access (OBDA) approach. Our system is based on our solid theoretical contributions and has been extensively evaluated at Equinor

Matching disease and phenotype ontologies in the ontology alignment evaluation initiative

Background: The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease. Results: Eleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track. AML, FCA-Map, LogMap(Bio) and PhenoMF systems produced the top results for ontology matching in comparison to consensus alignments. The results against manually curated mappings proved to be more difficult most likely because these mapping sets comprised mostly subsumption relationships rather than equivalence. Manual assessment of unique equivalence mappings showed that AML, LogMap(Bio) and PhenoMF systems have the highest precision results. Conclusions: Four systems gave the highest performance for matching disease and phenotype ontologies. These systems coped well with the detection of equivalence matches, but struggled to detect semantic similarity. This deserves more attention in the future development of ontology matching systems. The findings of this evaluation show that such systems could help to automate equivalence matching in the workflow of curators, who maintain ontology mapping services in numerous domains such as disease and phenotype

Optique: Zooming in on Big Data

Despite the dramatic growth of data accumulated by enterprises, obtaining value out of it is extremely challenging. In particular, the data access bottleneck prevents domain experts from getting the right piece of data within a constrained time frame. The Optique Platform unlocks the access to Big Data by providing end users support for directly formulating their information needs through an intuitive visual query interface. The submitted query is then transformed into highly optimized queries over the data sources, which may include streaming data, and exploiting massive parallelism in the backend whenever possible. The Optique Platform thus responds to one major challenge posed by Big Data in data-intensive industrial settings

Ontology Based Data Access in Statoil

Ontology Based Data Access (OBDA) is a prominent approach to query databases which uses an ontology to expose data in a conceptually clear manner by abstracting away from the technical schema-level details of the underlying data. The ontology is ‘connected’ to the data via mappings that allow to automatically translate queries posed over the ontology into data-level queries that can be executed by the underlying database management system. Despite a lot of attention from the research community, there are still few instances of real world industrial use of OBDA systems. In this work we present data access challenges in the data-intensive petroleum company Statoil and our experience in addressing these challenges with OBDA technology. In particular, we have developed a deployment module to create ontologies and mappings from relational databases in a semi-automatic fashion; a query processing module to perform and optimise the process of translating ontological queries into data queries and their execution over either a single DB of federated DBs; and a query formulation module to support query construction for engineers with a limited IT background. Our modules have been integrated in one OBDA system, deployed at Statoil, integrated with Statoil’s infrastructure, and evaluated with Statoil’s engineers and data

International variation in prescribing antihypertensive drugs: Its extent and possible explanations

BACKGROUND: Inexpensive antihypertensive drugs are at least as effective and safe as more expensive drugs. Overuse of newer, more expensive antihypertensive drugs is a poor use of resources. The potential savings are substantial, but vary across countries, in large part due to differences in prescribing patterns. We wanted to describe prescribing patterns of antihypertensive drugs in ten countries and explore possible reasons for inter-country variation. METHODS: National prescribing profiles were determined based on information on sales and indications for prescribing. We sent a questionnaire to academics and drug regulatory agencies in Canada, France, Germany, UK, US and the Nordic countries, asking about explanations for differences in prescribing patterns in their country compared with the other countries. We also conducted telephone interviews with medical directors of drug companies in the UK and Norway, the countries with the largest differences in prescribing patterns. RESULTS: There is considerable variation in prescribing patterns. In the UK thiazides account for 25% of consumption, while the corresponding figure for Norway is 6%. In Norway alpha-blocking agents account for 8% of consumption, which is more than twice the percentage found in any of the other countries. Suggested factors to explain inter-country variation included reimbursement policies, traditions, opinion leaders with conflicts of interests, domestic pharmaceutical production, and clinical practice guidelines. The medical directors also suggested hypotheses that: Norwegian physicians are early adopters of new interventions while the British are more conservative; there are many clinical trials conducted in Norway involving many general practitioners; there is higher cost-awareness among physicians in the UK, in part due to fund holding; and there are publicly funded pharmaceutical advisors in the UK. CONCLUSION: Two compelling explanations the variation in prescribing that warrant further investigation are the promotion of less-expensive drugs by pharmaceutical advisors in UK and the promotion of more expensive drugs through "seeding trials" in Norway

Changes in BMI-distribution from 1966–69 to 1995–97 in adolescents. The Young-HUNT study, Norway

Background The aim of this study was to explore changes in the BMI-distribution over time among Norwegian adolescents. Methods Height and weight were measured in standardised ways and BMI computed in 6774 adolescents 14–18 years who participated in the Young-HUNT study, the youth part of the Health-study of Nord-Trondelag County, Norway in 1995–97. The results were compared to data from 8378 adolescents, in the same age group and living in the same geographical region, collected by the National Health Screening Service in 1966–69. Results From 1966–69 to 1995–97 there was an increased dispersion and a two-sided change in the BMI-distribution. Mean BMI did not increase in girls aged 14–17, but increased significantly in 18 year old girls and in boys of all ages. In both sexes and all ages there was a significant increase in the upper percentiles, but also a trend towards a decrease in the lowest percentiles. Height and weight increased significantly in both sexes and all ages. Conclusion The increased dispersion of the BMI-distribution with a substantial increase in upper BMI-percentiles followed the same pattern seen in other European countries and the United States. The lack of increase in mean BMI among girls, and the decrease in the lowest percentiles has not been acknowledged in previous studies, and may call for attention

The Impact of Realistic Age Structure in Simple Models of Tuberculosis Transmission

Background : Mathematical models of tuberculosis (TB) transmission have been used to characterize disease dynamics, investigate the potential effects of public health interventions, and prioritize control measures. While previous work has addressed the mathematical description of TB natural history, the impact of demography on the behaviour of TB models has not been assessed. Methods : A simple model of TB transmission, with alternative assumptions about survivorship, is used to explore the effect of age structure on the prevalence of infection, disease, basic reproductive ratio and the projected impact of control interventions. We focus our analytic arguments on the differences between constant and exponentially distributed lifespans and use an individual-based model to investigate the range of behaviour arising from realistic distributions of survivorship. Results : The choice of age structure and natural (non-disease related) mortality strongly affects steady-state dynamics, parameter estimation and predictions about the effectiveness of control interventions. Since most individuals infected with TB develop an asymptomatic latent infection and never progress to active disease, we find that assuming a constant mortality rate results in a larger reproductive ratio and an overestimation of the effort required for disease control in comparison to using more realistic age-specific mortality rates. Conclusions : Demographic modelling assumptions should be considered in the interpretation of models of chronic infectious diseases such as TB. For simple models, we find that assuming constant lifetimes, rather than exponential lifetimes, produces dynamics more representative of models with realistic age structure