A Survey of Multilingual OWL Ontologies in BioPortal

The internationalisation goal for OWL sought to offer support for multilingual ontologies. User-displayable labels were suggested as a way to realise this, by means of rdfs:label. However, because each label is a language-tagged string, this hampers accurate representation of strings in languages that require grammatical features such as inflected forms and gender. At least eight linguistic models have been proposed to address this key shortcoming, with OntoLex-Lemon now the de facto standard. The purpose of this survey was to determine if there has been any adoption of linguistic models within OWL ontologies. As OWL ontologies are widely used in the biomedical domain, the survey was limited to those ontologies in NCBO BioPortal, a biomedical repository. The results indicate that OntoLex-Lemon was not used in any production OWL ontology at time of review, nor that of any other linguistic model. In addition, the adoption rate of multilingualism in OWL ontologies in BioPortal was observed to be 5%, with English the primary language, followed by French and German

A computational framework for harnessing data and knowledge for bioprocess design

Bioprocess design requires substantial resources for the required experimental investigation of the options for each bioprocess step. With the aim of reducing the amount of experimentation needed for bioprocess development, a new computational framework called Bioprocess Data and Knowledge Framework (BDKF) has been developed to explore the data and knowledge systematically. In BDKF, the representation of four types of data and knowledge i.e. experimental data, ontologies, theoretical knowledge and empirical knowledge, have been established. The experimental data is the data that comes from previous experiments. The ontologies are the systematic description of the bioprocess terminologies used in the experimental data and knowledge. It can organize the terminologies of a domain as a hierarchy that allows the experimental data to be searched. The theoretical knowledge is the knowledge represented by formal definitions in the bioprocess, such as fundamental equations. The empirical knowledge is the knowledge obtained from practical studies, e.g. the relationships between different scales established through ultra scale-down experimentation. Three reasoning functionalities, search, prediction and suggestion, have been established to imitate human reasoning on using data and knowledge. The search functionality finds relevant experimental data to the bioprocess design problems. With this data, the prediction functionality analyses the data and estimates the possible performance of the bioprocess step. The suggestion functionality produces solutions for further experiments that either confirm the solutions or narrow down the design space. A prototype applying the BDKF approach to illustrate how to capture data and knowledge and how reasoning functionalities work for the operating conditions identification was developed for a case study on centrifugation. Design queries that represented relevant process material information and separation requirements were generated to initiate the BDKF approach. The prototype demonstrated that data from strain variants and data from different scales can be utilized through ontologies, theoretical knowledge and empirical knowledge. A more complicated prototype was developed for the chromatography case study. The prototype introduced a hierarchical heuristic approach to solve the chromatographic process design problems, such as column selection, buffer composition identification and operating conditions determination. This prototype demonstrated that BDKF can be used for both screening and optimisation to propose several potential bioprocess solutions. Evaluation results of each prototype showed that the BDKF approach can make good performance predictions and suggestions for further experiments. It is very promising as an early stage process development tool. Finally, a method for finding a design solution for a giving sequence by using mass balance calculations has been developed. A case study including centrifugation, filtration and chromatography has been examined. This demonstrated that BDKE method had the potential to allow all of the data and knowledge to be used for the whole bioprocess design. Therefore, the BDKF approach can provide a systematic way to harness bioprocess data and knowledge to enhance the efficiency of bioprocess development

The NeOn Ontology Models

Interoperability on multiple levels, concerning both the ontologies themselves and their engineering activities, is a key requirement for ontology networks to be efficient, with minimal redundancy and high reuse. This requirement has a strict binding for software tools that can support some interoperability levels, yet they can be hindered by a lack of shared models and vocabularies describing the resources to be handled, as well as the ways of handling them. Here, three examples of metalevel vocabularies are proposed, each covering at least one peculiar interoperability aspect: OMV for modeling the artifacts themselves, LIR for managing a multilingual layer on top of them, and C-ODO Light for modeling collaboration-supportive life cycle management tasks and processes. All of these models lend themselves to handling by dedicated software tools and are all being employed within NeOn products