Hajo Rijgersberg

Ontology of units of measure and related concepts

This paper describes the Ontology of units of Measure and related concepts OM, an OWL ontology of the domain of quantities and units of measure. OM supports making quantitative research data more explicit, so that the data can be integrated, verified and reproduced. The various options for modeling the domain are discussed. For example, physical quantities can be modeled either as classes, instances or properties. The design choices made are based on use cases from our own projects and general experience in the field. The use cases have been implemented as tools and web services. OM is compared with QUDT, another active effort for an OWL model in this domain. We note possibilities for integration of these efforts. We also discuss the role OWL plays in our approach.

Quantitative Microbial Risk Assessment for Escherichia coli O157:H7, Salmonella, and Listeria monocytogenes in Leafy Green Vegetables Consumed at Salad Bars

Fresh vegetables are increasingly recognized as a source of foodborne outbreaks in many parts of the world. The purpose of this study was to conduct a quantitative microbial risk assessment for Escherichia coli O157:H7, Salmonella, and Listeria monocytogenes infection from consumption of leafy green vegetables in salad from salad bars in The Netherlands. Pathogen growth was modeled in Aladin (Agro Logistics Analysis and Design Instrument) using time-temperature profiles in the chilled supply chain and one particular restaurant with a salad bar. A second-order Monte Carlo risk assessment model was constructed (using @Risk) to estimate the public health effects. The temperature in the studied cold chain was well controlled below 5 degrees C. Growth of E. coli O157:H7 and Salmonella was minimal (17 and 15%, respectively). Growth of L. monocytogenes was considerably greater (194%). Based on first-order Monte Carlo simulations, the average number of cases per year in The Netherlands associated the consumption leafy greens in salads from salad bars was 166, 187, and 0.3 for E. coli O157:H7, Salmonella, and L. monocytogenes, respectively. The ranges of the average number of annual cases as estimated by second-order Monte Carlo simulation (with prevalence and number of visitors as uncertain variables) were 42 to 551 for E. coli O157:H7, 81 to 281 for Salmonella, and 0.1 to 0.9 for L. monocytogenes. This study included an integration of modeling pathogen growth in the supply chain of fresh leafy vegetables destined for restaurant salad bars using software designed to model and design logistics and modeling the public health effects using probabilistic risk assessment software.

How semantics can improve engineering processes: A case of units of measure and quantities

Science and engineering heavily depend on the ability to share data and models. The World Wide Web provides even greater opportunity to reuse such information from disparate sources. Moreover, if the information is digitized it can to a large extent be processed automatically. However, information sharing requires the availability of proper formal standards. Ontologies provide such standards. Creating an ontology of units of measure is a crucial first step in unambiguously exchanging and processing quantitative information. The next step is to make this ontology available for software applications. In this paper we evaluate prevailing ontologies of units by comparing them to a semi-formal description of the domain of units of measure. This description was drafted from textual descriptions of standards in the field. An important result of the analysis is that existing ontologies only define subsets of the necessary concepts and relations identified in our reference description. We therefore propose a new ontology, called OM (Ontology of units of Measure and related concepts). The ontology is based on the description and the corresponding parts of the analyzed ontologies. OM defines the complete set of concepts in the domain as distinguished in the textual standards. As a result the ontology can answer a wider range of competency questions than the existing approaches do. Moreover, to make OM available for arbitrary software systems, we have developed a number of web services that offer a standardized interface. Three applications demonstrate the usefulness of OM and its services. First, a web application checks dimension and unit consistency of formulas. Second, an engineering application for agricultural supply chains computes product respiration quantities and measures. Third, a Microsoft Excel add-in assists in data annotation and unit conversion. Preliminary user evaluations indicate that OM and the associated services provide a useful component for software applications in science and engineering.

Application of a transmission model to estimate Performance Objectives for Salmonella in the broiler supply chain

The aim of the present study was to demonstrate how Performance Objectives (POs) for Salmonella at various points in the broiler supply chain can be estimated, starting from pre-set levels of the PO in finished products. The estimations were performed using an analytical transmission model, based on prevalence data collected throughout the chain in The Netherlands. In the baseline (current) situation, the end PO was set at 2.5% of the finished products (at end of processing) being contaminated with Salmonella. Scenario analyses were performed by reducing this baseline end PO to 1.5% and 0.5%. The results showed the end PO could be reduced by spreading the POs over the various stages of the broiler supply chain. Sensitivity analyses were performed by changing the values of the model parameters. Results indicated that, in general, decreasing Salmonella contamination between points in the chain is more effective in reducing the baseline PO than increasing the reduction of the pathogen, implying contamination should be prevented rather than treated. Application of both approaches at the same time showed to be most effective in reducing the end PO, especially at the abattoir and during processing. The modelling approach of this study proved to be useful to estimate the implications for preceding stages of the chain by setting a PO at the end of the chain as well as to evaluate the effectiveness of potential interventions in reducing the end PO. The model estimations may support policy-makers in their decision-making process with regard to microbiological food safety.

A Model for Setting Performance Objectives for Salmonella in the Broiler Supply Chain

A stochastic model for setting performance objectives for Salmonella in the broiler supply chain was developed. The goal of this study was to develop a model by which performance objectives for Salmonella prevalence at various points in the production chain can be determined, based on a preset final performance objective at the end of the processing line. The transmission of Salmonella through the broiler production chain was modeled. The prevalence at flock level was calculated from the measured prevalence at sample level. The transmission model is based on data on the occurrence of Salmonella collected in the Dutch broiler production chain during several years. The developed model can be used by policymakers and industry to determine economically and politically acceptable performance objectives for various points of the production chain and to draw conclusions about which interventions are most appropriate.

Semantic Support for Quantitative Research Processes

Collaboration in science requires a shared model of underlying workflows and concepts. In addition to leveraging information exchange between scientists, the shared model should enable automated invocation of computational (numerical) methods from a conceptual level. In this way, the model fills the gap between humans interpreting textual information and computers processing the underlying data and mathematical models. To this end, the authors propose an ontology of quantitative research (OQR). The OQR is based on established tenets of the philosophy of science. Scientific quantities expressed in OQR can be used directly as input to computational methods. The authors demonstrate the OQRs quality by applying it to a case of quantitative food research. Finally, they describe an application in Quest, a prototype quantitative e-science tool.

Combining information on structure and content to automatically annotate natural science spreadsheets

In this paper we propose several approaches for automatic annotation of natural science spreadsheets using a combination of structural properties of the tables and external vocabularies. During the design process of their spreadsheets, domain scientists implicitly include their domain model in the content and structure of the spreadsheet tables. However, this domain model is essential to unambiguously interpret the spreadsheet data. The overall objective of this research is to make the underlying domain model explicit, to facilitate evaluation and reuse of these data.We present our annotation approaches by describing five structural properties of natural science spreadsheets, that may pose challenges to annotation, and at the same time, provide additional information on the content. For example, the main property we describe is that, within a spreadsheet table, semantically related terms are grouped in rectangular blocks. For each of the five structural properties we suggest an annotation approach, that combines heuristics on the property with knowledge from external vocabularies. We evaluate our approaches in a case study, with a set of existing natural science spreadsheets, by comparing the annotation results with a baseline based on purely lexical matching.Our case study results show that combining information on structural properties of spreadsheet tables with lexical matching to external vocabularies results in higher precision and recall of annotation of individual terms. We show that the semantic characterization of blocks of spreadsheet terms is an essential first step in the identification of relations between cells in a table. As such, the annotation approaches presented in this study provide the basic information that is needed to construct the domain model of scientific spreadsheets. HighlightsWe describe five structural properties of scientific spreadsheet tables.Within a spreadsheet table, semantically related terms are grouped in blocks.We annotate tables using information on their structure and external vocabularies.Including information on table structure improves annotation of spreadsheet terms.We identify relations within a table by semantically categorizing blocks of terms.

Modeling the impact of the indigenous microbial population on the maximum population density of Salmonella on alfalfa

Within a microbial risk assessment framework, modeling the maximum population density (MPD) of a pathogenic microorganism is important but often not considered. This paper describes a model predicting the MPD of Salmonella on alfalfa as a function of the initial contamination level, the total count of the indigenous microbial population, the maximum pathogen growth rate and the maximum population density of the indigenous microbial population. The model is parameterized by experimental data describing growth of Salmonella on sprouting alfalfa seeds at inoculum size, native microbial load and Pseudomonas fluorescens 2–79. The obtained model fits well to the experimental data, with standard errors less than ten percent of the fitted average values. The results show that the MPD of Salmonella is not only dictated by performance characteristics of Salmonella but depends on the characteristics of the indigenous microbial population like total number of cells and its growth rate. The model can improve the predictions of microbiological growth in quantitative microbial risk assessments. Using this model, the effects of preventive measures to reduce pathogenic load and a concurrent effect on the background population can be better evaluated. If competing microorganisms are more sensitive to a particular decontamination method, a pathogenic microorganism may grow faster and reach a higher level. More knowledge regarding the effect of the indigenous microbial population (size, diversity, composition) of food products on pathogen dynamics is needed in order to make adequate predictions of pathogen dynamics on various food products.

Exchanging crop trials information: standardization by means of data model templates

A crop variety trial typically yields a large number of data. A datamodel is needed to describe the structure of these data and to explain the meaning of the data. Without using an explicit datamodel it is impossible to interpret the data correctly. In addition, a datamodel offers the opportunity for discussion about the experimental methods and goals, to be applied in new trials. The problem however with data models is to find the right trade-off between standardization and flexibility. In this paper we describe the construction of new, application specific layers on top of any standard data model language. Such a new layer consists of carefully chosen data model templates. By using data model templates the freedom of the datamodel designer is kept, yet data exchange and interpretation can be further supported. In addition we describe two alternative languages and their mutual relation, SFD and EXPRESS. We compare these languages and show that SFD can indeed be translated to EXPRESS descriptions.